Collection and analysis of environmental biological materials

Abstract

There is provided a method of generating information about biology within a survey zone, the method comprising: i) harvesting biological material from an exposed (e.g., external) impingement surface that has been carried through the survey zone by a vehicle, the surface having been exposed to air, the air is displaced as a result of the movement of the vehicle through the survey zone; ii) performing a molecular analysis on the biological material to generate data regarding the source of the biological material. There is also provided a method of generating information about biological presence of a geographic area, the method comprising: i) collecting biological material on an exposed impact surface of a land vehicle moving over the area; ii) harvesting the collected biological material from the impingement surface (e.g., directly on site or by carrying or transporting the collection element to a remote laboratory); iii) performing a molecular analysis on the harvested biological material to generate data regarding the source of the biological material. Preferably, the vehicle is a public transport vehicle, such as a bus, an electric car or a train, or a road transport or delivery vehicle.

Description

Technical Field

[0001] This invention relates to improved sampling methods for collecting environmental biological materials such as DNA, RNA, or more generally nucleic acids, as well as methods for processing and using data obtained from such materials. Background Technology

[0002] It is now believed that biodiversity is declining faster than ever before in human history. The International Union for Conservation of Nature (IUCN) reports that 42,100 species worldwide—almost a third of all species assessed—are threatened with extinction. This problem affects both developed and developing countries. In the UK, populations of mammals, birds, fish, reptiles, and amphibians have reportedly declined by an average of 70% since 1970, while flying insect populations have declined by as much as 60% in the past 20 years. Up to 40% of the world's insect species, including bees, ants, and butterflies, are reportedly at risk of extinction. This extreme loss of pollinators could lead to significantly reduced yields in insect-pollinated crops—further tightening the already strained global food supply.

[0003] Invasive alien species (IAS) are among the top five contributors to global biodiversity decline (IPBES, 2023), further exacerbating many known drivers of ecosystem destruction and species extinction rates. To address the challenges posed by IAS, a combination of national and international guiding policies, regulations, and frameworks is appropriate (e.g., the International Convention on Biological Diversity (CBD), the International Plant Protection Convention (IPPC), the Global Invasive Species Programme (GISP), and the European Network on Invasive Alien Species (NOBANIS)). In Europe, EU Regulation 1143 / 2014 is the most important environmental strategy for meeting Aichi Target 9 and EU Biodiversity Strategy 2030 Target 12 as part of the European Green Deal. The backbone of this strategy relies on evidence-based risk assessments of IAS to prioritize resource allocation and enhance the effectiveness of detection, prevention, management, and eradication actions. However, these strategies face significant challenges due to the lack of comprehensive and up-to-date information on the distribution, abundance, and invasive pathways of all identified IAS, particularly for newly introduced, less studied, or even unidentified IAS.

[0004] The 2022 UN Biodiversity Conference agreed on a historic package of measures to address the dangerous loss of biodiversity and restore natural ecosystems. This package (known as the Kunming-Montreal Biodiversity Framework (GBF)) includes four targets and 23 objectives to be achieved by 2030. The first objective statement is as follows: "The integrity, connectivity, and resilience of all ecosystems are maintained, enhanced, or restored, thereby significantly increasing the area of ​​natural ecosystems by 2050." Human-induced extinction of known threatened species ceases, and by 2050, the rate of extinction and risk of all species is reduced tenfold, and the abundance of natural wild species increases to healthy and resilient levels. This has maintained genetic diversity within both wild and captive species populations, protecting their adaptive potential. And here is one of the 23 goals: i) Effective protection and management of at least 30% of the world’s land, inland waters, coastal areas, and oceans, with a focus on areas of particular importance to biodiversity and ecosystem functions and services. GBF prioritizes ecological representation of protected areas, well-connected and equitably managed systems, and other effective area-based conservation, recognizing inherent and traditional territories and practices. Currently, 17% and 10% of the world’s land and ocean areas, respectively, are protected.

[0005] ii) Restoration has been completed or is being carried out on at least 30% of degraded terrestrial, inland water, and coastal and marine ecosystems; iii) Reduce the loss of important areas with high biodiversity (including ecosystems with high ecological integrity) to near zero; iv) Prevent the introduction of priority invasive alien species and reduce the introduction and establishment of other known or potential invasive alien species by at least half, and eradicate or control invasive alien species on islands and other priority sites; and v) Require large multinational corporations and financial institutions to monitor, assess, and transparently disclose their risks, dependencies, and biodiversity impacts through their operations, supply and value chains, and portfolios.

[0006] Therefore, it is evident that governments and businesses will need biodiversity data to monitor progress and make informed decisions to mitigate decline and risks. Currently, many governments have appropriate survey programs to monitor general wildlife, protected species, invasive species, agricultural pests, and disease vectors. Many of these programs focus on single species or target groups and are designed to manage specific risks or performance indicators; therefore, they do not provide a clear picture of overall biodiversity.

[0007] Environmental DNA (eDNA) is a promising technology for delivering biodiversity data in a cost-effective manner. eDNA is genetic material released into the environment by animals. Fragments of DNA or RNA from sources such as skin cells, scales, and feces can be sequenced and compared with reference databases to obtain taxonomic (species) identification. eDNA samples can come from anywhere and are relatively easy to obtain. Unlike current ecological monitoring techniques, which rely heavily on visual identification of species and often require field surveys and capture, eDNA technology is non-invasive and is generally more sensitive to detecting rare and evasive species, as well as those organisms that are very small or difficult to visually identify.

[0008] Currently, eDNA is primarily used in (freshwater) aquatic environments. This is largely driven by the fact that aquatic environments are difficult to survey using conventional methods, and that fish and amphibians excrete large amounts of eDNA, which is subsequently distributed throughout the water body. In such cases, eDNA is typically used in ponds or lakes to provide a local but very detailed snapshot. Furthermore, in flowing currents and oceans where eDNA is used, it is assumed that the eDNA has its origin upstream or is influenced by water currents. Automated sampler devices exist to mitigate sampling efforts, but in many cases, eDNA collection still requires a physical human presence to obtain samples. This hinders uptake and deployment on a larger regional scale or over a considerable period of time.

[0009] In their paper “Measuring Biodiversity from Airborne DNA” (Current Biology 32, 693-700, February 7, 2022), Clare et al. reported a project of filtering air samples in a zoo to collect DNA, which was then used to identify species and their ecological interactions. They found that the air samples contained DNA from 25 mammal and bird species, including 17 known terrestrial zoo-resident species. They also identified food items from air samples taken from animal enclosures, as well as localized natural taxa, including the dangerous Eurasian Hedgehog.

[0010] In a similar study, “Airborne Environmental DNA for Monitoring Terrestrial Vertebrate Populations” (Current Biology 32, 701-707, February 7, 2022), Lynggard et al. reported obtaining eDNA from filtered air samples at Copenhagen Zoo. Filtering air at three locations (between outdoor animal enclosures and the stable exterior of Rainforest House) allowed for the capture of eDNA, from which 49 vertebrate species spanning 26 grades and 37 families were detected: 30 mammals, 13 birds, 4 carnivores, 1 amphibian, and 1 reptile. These species encompassed animals kept in the zoo, species present in the zoo environment, and species used as feed in the zoo. The detected species included a range of taxonomic orders and families, sizes, behaviors, and abundances.

[0011] Although both studies demonstrate that air filtration can be used to isolate eDNA, the methods employed require frequent in-situ visits to modify and collect the filter elements on which the eDNA is collected, posing logistical challenges for large-scale deployment.

[0012] Therefore, alternative solutions are needed to address the problem of collecting biological materials (such as eDNA) from terrestrial animals and other organisms for centralized surveys and to support research on biodiversity.

[0013] WO2022 / 271,799A1 relates to systems and methods for manufacturing wearable articles (such as clothing or footwear) with microstructures configured to capture, retain, and / or collect materials containing environmental nucleic acids (eNAs). The microstructures have a size of less than about 1 mm and include at least one of the following: barbule, channels, cavities within the article, sponges, pores, pillars extending from the article, hairs, bristles, fibers, perforations, depressions, bumps, lattices, and textures. A matrix and / or microorganisms can be applied to the microstructure to collect eNAs, which are then analyzed to determine biodiversity in the sampled area. In one embodiment, the microorganisms incorporate the eNAs into their genome. It is also mentioned that "the articles and methods described herein are not limited to footwear, textiles, or clothing, and the principles of the invention can be applied to any kind of wearable articles that can be used to collect genetic material, such as hats, shirts, trousers, belts, glasses, jewelry, or masks. In a further embodiment, the invention can be implemented in the form of structures removably applied to articles that can be transported to sample biodiversity information, such as patches, covers, shields, or stickers attached to backpacks, walking poles, walkers, or vehicles." That is, the microstructures proposed at the focus of this disclosure can be used not only in the form of 3D-printed wearable articles, but also applied to carryable or wearable articles (also known as wearable clothing accessories), and potentially to microstructures that can be attached to vehicles.

[0014] US2022 / 349,804A1 discloses an apparatus that uses an electrically driven fan (negative pressure device) to draw air into a housing, where airborne particles are filtered by a cyclone separator and collected on a collection plate or in a removable hopper. The cyclone separator causes the air to vortex within the fluid housing to deposit materials, such as viruses, bacteria, fungi, and other particles, from the air in a manner that can be later analyzed. This apparatus can be used to provide information on the properties of airborne organisms or materials. The cyclone separator is said to be capable of filtering up to 393 liters per minute.

[0015] The paper "Bioaerosols in public and tourist buses" published by Amaia Fernandez-Iriarte et al. in Aerobiologia (2021) 37: 525-541 considers the air quality inside buses, particularly the composition and abundance of airborne microorganisms. These were assessed in buses powered by five different fuel types during both summer and winter. It was determined that biodiversity inside buses is greatly influenced by the presence of humans inside, but also by outdoor sources at the time of sampling and the seasonal period, rather than by the type of energy source. Samples were collected using 37 mm glass fiber filters with a 0.8 μm pore size housed in a sealed face box connected to a personal air sampling pump. Among the bus types sampled were open-top travel buses, and for these buses, samples were obtained using air sampling pumps both inside and outside the bus (i.e., on the open upper deck of the bus).

[0016] The paper "Isolation of Airborne Fungi from the Soil Microbiome of San Joaquim Valley, California," published by Robert Wagner et al. in *Molecular Ecology*, Vol. 31, No. 19, August 2022, pp. 4962-4978, reports a study of fungal communities in soil and air on underdeveloped and agricultural land in the San Joaquim Valley. Soil samples were collected using a hemispherical collector, and air samples were obtained by passively settling airborne dust into empty, sterile Piper dishes mounted 50 cm above the ground and protected from rain by plastic cones. The paper concludes that the airborne microbiome in the San Joaquim Valley differs from the soil microbiome, and that the assemblages of airborne fungi from remote locations are more similar to each other than they would be to the fungal communities in their native soils. Summary of the Invention

[0017] According to a first aspect of the present invention, a method for generating information about the biology within a survey area is provided, the method comprising: i) Harvesting biomaterial from an exposed impact surface that has been carried through the survey area by a land vehicle, the surface being exposed to air displaced by the movement of the vehicle through the survey area, the biomaterial being deposited from the displaced air due to the inertia of the biomaterial rather than due to the filtration of the air; ii) Perform molecular analysis on the biomaterial to generate data about the source of the biomaterial.

[0018] In other words, instead of using microstructures to filter particles from the environment as in WO2022 / 271799, in this aspect of the invention, particles are deposited on an impact surface, which is actually driven into the particles when they are suspended in the air.

[0019] In this aspect of the invention, as optionally in all other aspects of the invention, the impact surface is substantially or completely free of pores, hairs, and other microstructures.

[0020] According to the second aspect, a method for generating biological information about a survey area is provided, the method comprising: i) Harvest biological material from the exposed impact surfaces of the land vehicle that have been carried through the survey area, the surfaces having been exposed to air displaced due to the movement of the land vehicle through the survey area; ii) Perform molecular analysis on the biomaterial to generate data about the source of the biomaterial.

[0021] According to the third aspect, a method for generating information about the biology within a survey area is provided, the method comprising: i) Harvesting biomaterial from an exposed impact surface that has been carried through the survey area by a land vehicle and exposed to air displaced by the movement of the vehicle through the survey area, from which the biomaterial is deposited; ii) Perform molecular analysis on the biomaterial to generate data about the source of the biomaterial, wherein the impact surface is substantially free of pores and other microstructures.

[0022] By providing an exposed (e.g., external) impact surface instead of a filter through which air must pass, this method avoids the need to replace clogged filters. This means that the exposed impact surface can handle very large volumes of air, thus offering the opportunity to capture more biological material in each exploration attempt. It also means that considerations and limitations associated with specific design features of filter “pore size” or microstructure can be avoided: there is no defined minimum particle size, and particles of any size can adhere to the impact surface. Using air impact on an exposed surface also eliminates the need to provide and maintain a vacuum pump to draw air through a filter.

[0023] Preferably, the impact surface is a forward-facing surface supported on or carried by the vehicle, as this arrangement may increase the likelihood of biological particles adhering to the impact surface rather than simply being deflected. Alternatively, for the same reason, the impact surface is also arranged substantially transversely to (e.g., orthogonally to) the longitudinal axis of the vehicle. Optionally, the impact surface may be located at the front of the vehicle, such as at or on the front of the vehicle. Preferably, the impact surface has a diameter of at least 0.5 m. 2Choose at least 0.75m 2 Choose at least 1m 2 Choose any length of at least 1.2m 2 Choose at least 1.4m 2 Choose at least 1.5m 2 Choose at least 1.6m 2 Choose at least 1.8m 2 Choose any 2m or more 2 Choose at least 2.4m 2 Choose at least 2.8m 2 Choose any 3m or more 2 Choose any 4m 2 Or a larger surface area.

[0024] In the field of air sampling, it is known to collect particulate samples from viscous surfaces by means of impact caused by airflow. Active air samplers (as opposed to passive samplers that collect samples by “sedimentation”) can use the principle of inertial impaction to capture particles on viscous surfaces (particles that would easily adhere to adhesives or something similar to a culture medium such as agar), as in the case of cascaded impactors. In such capture devices, a vacuum source (e.g., a pump) is used to generate an airflow, which is directed through nozzles to the viscous surface within a protected / sheltered environment (i.e., inside a housing). In contrast, we are interested in using impact caused by airflow generated by the movement of a vehicle rather than a suction source, thus distinguishing ourselves from the methods employed by Clare et al., Lynggard et al., Fernandez-Iriarte et al., and US2022 / 349,804 A1. We are also interested in capturing samples as deposits on exposed surfaces, such as those of vehicles or visible outer surfaces on vehicles. The impact velocity of particles on our impact surface is a function of the vehicle's (primary) (non-zero) velocity and the air velocity due to weather conditions (although in practice this is a very minor factor, and in fact usually negligible).

[0025] In any of the methods of the first to third aspects, harvesting may involve wiping an exposed impact surface to transfer biological material from the exposed impact surface to an article used for wiping the exposed impact surface. Optionally, a paint roller or similar device may be used to perform the wiping. The efficiency of harvesting using wiping may be increased if the impact surface is generally smooth rather than significantly textured (e.g., which would be impossible to wipe effectively as taught in WO2022 / 271799). Therefore, wiping vehicle windshields and body panels, as well as foils, films, or sheets carried by or adhered to vehicles, has great potential for efficiency because these surfaces are generally substantially smooth. These impact surfaces may be flat and smooth, but wavy and / or shaped and / or textured surfaces may also be used, provided that the scale of the wavy, shaped, and / or textured surface allows for the use of a reasonably sized swab. Due to the texture of the surface, we do not want to reduce the requirement to harvesting biological material using cotton buds or similar devices, and small paint rollers may be as small as we desire in maximizing harvesting efficiency, and ideally, we want to achieve high harvesting efficiency even if the amount of time available for harvesting is relatively short. When using public transport or commercial vehicles for sample collection, there is typically a very short time window for harvesting samples and preparing the vehicle for another sample collection run. This usually must be completed within about half an hour, and ideally, we want to be able to perform these tasks within about 15 minutes. If we are wiping an impact surface (rather than replacing the impact surface carrying the sample with a fresh / clean impact surface to be used in the next run), for high harvesting efficiency, we want the wiper to be in contact with all or substantially all of the impact surface's surfaces that are collecting biological material during use. This does not preclude the use of shaped or textured impact surfaces, but it does impose constraints on scale or any shaped texture, making anything approaching the surface complexity of the microstructures proposed in WO2022 / 271799 (including pores, rods, hairs, filaments, channels, cavities, and other features) unsuitable. Therefore, we generally want to avoid using impact surfaces that are porous or otherwise configured with microstructures such as fibers, hairs, etc. Preferably, the impact surface does not have microstructures of the type described in WO2022 / 271799 (“Microstructures may include at least one barb, channel, cavity inside the article, sponge, hole, column extending from the article, hair, bristles, fiber, perforation, depression, protrusion, grid and texture”), and these microstructures are 1 mm or smaller in size.

[0026] In any of the methods of the first to third aspects, harvesting may involve washing the exposed impact surface to transfer biological material from the surface to a liquid used for washing the surface. Washing may be performed while the impact surface is in situ on the vehicle or after the impact surface has been removed from the vehicle.

[0027] In any variation of the method according to the foregoing aspects, the exposed impact surface may be provided by a body portion of the vehicle. Optionally, the impact surface may be selected from one or more of glass surfaces, plastic surfaces, metal surfaces, and painted surfaces, and optionally, the impact surface may include a variety of different material types. For example, in the methods according to various aspects of the invention, a large portion of the front surface of the vehicle (optionally consisting of a windshield and / or different body panels) may be used as the impact surface.

[0028] In any variation of the foregoing method, the exposed impact surface may be part of a collection element mounted on the exterior of the vehicle. Optionally, the collection element is a flexible membrane or sheet. Any such flexible membrane or sheet may be adhered to the exterior surface of the vehicle, for example, using adhesives, hook and loop fasteners, one or more threaded fasteners, one or more clamps, and / or using magnetic attraction.

[0029] In any variation of the method according to the foregoing aspects, the collecting element may include a glass or metal panel.

[0030] The method according to any variation of the foregoing aspects may also include the following steps: collecting biological material on the external impact surface of a land vehicle that moves across one or more first transects of the survey area. That is, the vehicle's passage through the survey area may be under the control of the same party as the harvesting of the biological material.

[0031] Alternatively, the vehicle's passage through the survey area can be under the control of a first party, while the harvesting of biological material collected on the impact surface can be the responsibility of a different party—for example, the vehicle could be a public transport vehicle or a delivery or transport vehicle, and the harvesting of biological material from the vehicle can be performed by an entity responsible for maintaining a database of biodiversity data or for providing information on biodiversity to third parties (or their subcontractors). The method of carrying samples on a journey already paid for by someone (and often someone else) can facilitate extremely cost-effective capture of environmental nucleic acid samples, which in turn means that more extensive and / or more frequent, and optionally speculative, sampling may become cost-effective. This is a particularly significant advantage of this new approach.

[0032] Conversely, the same or linked entities can be responsible for the initial collection phase (where biological material is captured on the impact surface), as well as at least the subsequent harvesting phase and possibly the molecular analysis phase (although the latter phase can be contracted out to a specialist supplier).

[0033] The method according to any variation of the foregoing aspects may also include creating a database based on the results of the molecular analysis performed in step ii). The method may also include populating the database with biopresence data from multiple iterations of the method. The method may also include populating the database with biopresence data derived from iterations of the method performed for different geographic regions.

[0034] In any variation of the method according to the foregoing aspects, the survey area or geographical region may be a building, commercial or industrial site, and the method may further include collecting biological material on the external impact surface of a vehicle moving over one or more geographical regions outside the periphery of the site, and the harvesting and molecular analysis steps are also performed on the biological material so collected.

[0035] Any variation of the method according to the foregoing may also include the following steps: iii) Perform one or more additional captures of biological material on one or more second transverse bands passing through the survey area, each of the one or more second transverse bands intersecting one or more first transverse bands; iv) Harvesting the collected biological material from the external impact surface (the harvesting can be performed, for example, directly in the field or by carrying / transporting the collection element to a dedicated laboratory); v) Perform molecular analysis on the harvested biological material to generate data on the origin of the biological material; vi) Generate probability maps of the identified species and / or taxa based at least in part on the results of the molecular analyses performed in steps ii) and v).

[0036] In such methods, at least one of one or more second transverse bands may be selected based at least in part on the results of the analysis performed in step ii).

[0037] In any variation of the method according to the foregoing aspects, the monitoring of the survey area or geographical region can be the detection of DNA, RNA, or protein-based markers indicating the presence or function of biological targets, the method comprising: The molecular analysis is performed to generate data indicating the presence or absence or function of the biological target.

[0038] In this approach, the biological target can be a rare, threatened, or dangerous species. Alternatively, in such an approach, the biological target can be an invasive alien species, or a species targeted for control or eradication. Optionally, the biological target can be termites, wood-boring beetles, or fungi such as dry rot.

[0039] According to the fourth aspect, a method for generating biodiversity data for a geographic region is provided, the method comprising: i) Collect biomaterials from the external impact surfaces of land vehicles moving in the area. ii) Harvesting the collected biological material from the external impact surface (the harvesting can be performed, for example, directly in the field or by carrying / transporting the collection element to a dedicated laboratory); iii) Perform molecular analysis on the harvested biological material to generate data on the origin of the biological material.

[0040] The method according to the fourth aspect may further include creating a database based on the results of the molecular analysis performed in step iii), optionally including populating the database with biodiversity data from multiple iterations of the method, and optionally populating the database with biodiversity data derived from iterations of the method performed for different geographic regions.

[0041] In any variation of the fourth aspect, the geographic area may be at least one of an industrial site, a construction site, or a commercial site, and the method further includes collecting biological material on the impact surface of a vehicle moving over one or more geographic areas outside the periphery of the site, and the collection and molecular analysis steps are also performed on the biological material so collected.

[0042] According to a fifth aspect, a method is provided for monitoring a geographic area based on the presence of biomarkers indicating the presence of biological targets, the method comprising: i) Collect biomaterials from the external impact surfaces of land vehicles moving across a geographic area. ii) Harvesting the biological material collected from the external impact surface (the harvesting can be performed, for example, directly in the field or by carrying / transporting the collection element to a dedicated laboratory); iii) Perform molecular analysis on the harvested biological material to generate data indicating the presence or absence of the biological target.

[0043] In the fifth approach, biological targets can be rare, threatening, or dangerous species.

[0044] Alternatively, in the fifth approach, the biological target could be an invasive alien species, or a species targeted for control or eradication.

[0045] In the fifth aspect of the method, the biological targets could be termites, wood-boring beetles, or fungi such as dry rot, each of which poses a potentially significant threat to timber used in construction. This aspect of the invention provides a potential early warning system for use by timber merchants, importers, and stockholders, as well as for developers, managers, and owners of homes constructed using large quantities of timber—e.g., timber-framed buildings. Such an early warning system would enable property owners and managers to intervene promptly and strategically to eradicate the relevant pests, without relying on the potentially harmful long-term preventative use (or frequent “blind” reapplication) of pesticides and fungicides—something long associated with chronic disease conditions in people exposed to chemicals.

[0046] According to a sixth aspect, a method for generating information about the presence of organisms within a geographically surveyed area is provided, the method comprising: i) Collect biomaterial from the impact surfaces of land vehicles moving through one or more first transverse zones of the survey area; ii) Harvesting the collected biological material from the external impact surface (the harvesting can be performed, for example, directly in the field or by carrying / transporting the collection element to a dedicated laboratory); iii) Perform molecular analysis on the collected biological material to generate data about the source of the biological material; iv) Perform one or more additional captures of biological material on one or more second transverse bands passing through the survey area, each of the one or more second transverse bands intersecting one or more first transverse bands; v) Harvesting the collected biological material from the impact surface; vi) Perform molecular analysis on the harvested biological material to generate data on the origin of the biological material; vii) Generate a probability map of the identified species and / or taxa based at least in part on the results of the molecular analyses performed in steps iv) and vi).

[0047] According to the seventh aspect, a method for generating a potential occurrence map of biological species of interest within a geographical survey area is provided, the method comprising: i) Collect biomaterial from the impact surfaces of land vehicles moving through one or more first transverse zones of the survey area; ii) Harvesting the collected biomaterial from the impact surface; iii) Perform molecular analysis on the harvested biological material to generate data on the source of the biological material; iv) Perform one or more further captures of biological material on one or more second transverse bands passing through the survey area; v) Harvesting the collected biological material from the impact surface; vi) Perform molecular analysis on the biological material harvested in step v) to generate data on the source of the biological material; vii) Generate a probability map of the biological species of interest based at least in part on the results of the molecular analyses performed in steps iv) and vi).

[0048] According to the eighth aspect, a method is provided for generating a probability map of identified species and / or taxa within a geographic survey area, the method comprising: i) Collect biomaterial from the impact surfaces of land vehicles moving through one or more first transverse zones of the survey area; ii) Harvesting the collected biomaterial from the impact surface; iii) Perform molecular analysis on the harvested biological material to generate data on the source of the biological material; iv) Harvesting the collected biological material from the external impact surface (the harvesting can be performed, for example, directly in the field or by carrying / transporting the collection element to a dedicated laboratory); v) Perform molecular analysis on the harvested biological material to generate data about the source of the biological material; vi) Perform one or more additional captures of biological material on one or more second transverse bands passing through the survey area, each of the one or more second transverse bands intersecting one or more first transverse bands; vii) Harvesting the biomaterial collected in step vi) from the impact surface; viii) Perform molecular analysis on the biological material harvested in step vii) to generate data on the source of the biological material; (ix) Generate probability maps of the identified species and / or taxa based at least in part on the results of the molecular analyses performed in steps (iv) and (viii).

[0049] In the method of the eighth aspect, the method may further include dividing the geographic survey area into a matrix of unit-sized grid cells, and determining the collection probability of a given species or taxa for each grid cell based on comparisons of multiple routes and sample events. Optionally, for each grid cell traversed by a given route, an initial collection probability is assigned to a given species or taxa, which is equal to 1 divided by the number of grid cells traversed by the given route if the given species or taxa is detected somewhere along the given route, or zero or a factor f is adjusted to reflect the chance of a false negative if the given species or taxa is not detected somewhere along the given route. Optionally, for cells that the route does not traverse on a large scale (the size of the average route length), a moving average is applied using the probabilities of all routes for collection sampling. Optionally, this moving average may be applied to the probability of each collection grid cell linked to each route, optionally based on the probabilities of other collection grid cells that the route does traverse. Optionally, the moving average algorithm can also be another exploratory algorithm, such as Kriging (Gaussian process regression) or multipoint statistics, and / or guided by secondary data (e.g., vegetation cover, land use maps, wind speed, other species occurrence databases). Optionally, an average can be applied to all cells farther from the route than a grid cell, and for all cells within a grid cell distance, a "neighboring" average can be used as the average of all such neighboring cells (cells near the route). Optionally, the base probability of cells far from (all) routes is calculated based on the average probability of routes in the (total) survey area. Optionally, moving averages can be applied at larger scales where some routes are shorter than the total survey area. Optionally, for a given species or taxonomy S1(p) of each grid cell... S1 The collection probability of the aggregated / modeled grid cell is the product of the probabilities of that cell for each route considered. This means that if a given species or taxa is not detected on one or more routes, the collection probability of a cell whose other routes intersect with that route is also set to 0 or f (if such a factor is applied). Optionally, for each grid cell adjacent to a route (but not part of the route), the average probability of the magnified square around the relevant cell can be calculated to reflect the available additional information about the area around the relevant grid cell. Optionally, for subsequent sampling moments, the probability of the grid cell can be recalculated and added to the previous probability plot.

[0050] Optionally, in the methods of the seventh and eighth aspects, each of the one or more second transverse segments may intersect with one or more of the one or more first transverse segments. In the methods of the seventh and eighth aspects, the impact surface may be an outer surface.

[0051] According to the ninth aspect, a method is provided for monitoring a geographic area in response to the presence of disease vectors such as tiger mosquitoes or Asian hornets, the method comprising: i) Collect biomaterials from the external impact surfaces of land vehicles moving in the geographic area. ii) Harvesting the collected biomaterial from the impact surface; iii) Perform molecular analysis on the harvested biological material to generate data on the source of the biological material; and iv) Determine the presence or absence of the disease vector.

[0052] According to the tenth aspect, a method for monitoring the geographic area where airborne viruses are present is provided, the method comprising: i) Collect biomaterials from the external impact surfaces of land vehicles moving in the geographic area. ii) Harvesting the collected biomaterial from the impact surface; iii) Perform molecular analysis on the harvested biological material to generate data on the source of the biological material; and iv) Determine the presence or absence of the virus based on the results of step iii).

[0053] In any variation of any aspect of the invention, the land vehicle may be a public transport vehicle, such as a bus, tram, or train, or a delivery vehicle, such as a cherry truck, truck, van, or small vehicle.

[0054] In any variation of any aspect of the invention, the method may be performed using more than one type of vehicle, and optionally, the method may be performed using both ground-based collection vehicles and airborne collection aircraft.

[0055] In any method according to an aspect of the invention for generating a map of the presence, activity, or absence of organisms in a survey area, the initial step of the method may include determining the availability of one or more of the following: Public transport routes that traverse the survey area; The postal vehicle routes that traverse the survey area; Delivery vehicle warehouses or centers in or near the survey area.

[0056] In any such method, subsequent process steps may involve identifying a suitable selection of vehicle travel routes that, when combined, create a set of cross-sections of the measurement area that are sufficiently extensive to provide the desired level of coverage for the measurement area.

[0057] In any such method, subsequent process steps may involve modifying the selection of vehicle travel routes to increase the density of transverse bands and / or the extent to which the survey area is covered by transverse bands (e.g., to reduce the number and / or size of gaps in the sample recovery across the survey area). Attached Figure Description

[0058] Embodiments of the invention will now be described by way of example only with reference to the accompanying drawings, in which: Figure 1 This is a flowchart illustrating methods according to various aspects of the present invention; Figure 2 A front view of a pair of vehicles is shown, which can be used to collect eDNA and other airborne biological materials in a method according to an aspect of the invention; Figure 3 This is a schematic diagram illustrating an idealized transport network for collecting biological samples; Figure 4 This is a graph showing the determination of detection probabilities based on findings from investigations conducted on intersecting transverse bands; Figure 5 This is a flowchart illustrating a method according to one aspect of the present invention; and Figure 6 This is a flowchart illustrating another method according to one aspect of the present invention. Detailed Implementation

[0059] In various aspects of this invention, airborne eDNA (more generally, biomaterial) is collected on an impact surface that moves along a transverse band (i.e., route) through a space or area to be monitored using a land vehicle, the impact surface being exposed to air flowing over and / or passing over the vehicle due to its movement. The air contains bioaerosols, including living organisms such as viruses and bacteria, vegetative forms such as pollen and spores, and fragments of cells and tissues from a variety of life forms, including multicellular life forms, including insects and other invertebrates, reptiles, birds, mammals, etc. Biomaterial that collides with the impact surface due to the inertia of the biomaterial is harvested from the impact surface and then processed, as described later. The impact surface may also be referred to as a collection surface. The length of the transverse band can be several kilometers, typically greater than 10 kilometers, and can be tens or hundreds of kilometers. Depending on the length of the transect, the same transect can be traversed multiple times between consecutive harvest events, which can occur on the same day or within 12 or 24 hours of each other, although in some cases, harvesting can occur after only a single traversal of the transect, and consecutive harvest events can occur multiple times within 24 hours.

[0060] Unlike the methods taught in the papers by Clare et al., Lynggard et al., and Fernandez-Iriarte et al., where air is pumped through a porous filter to allow eDNA to be collected from the air, we propose using an impact surface that moves through space to induce relative movement between the surface and the air. The air is deflected by the surface, and the biomaterial is deposited on the surface due to the surface's movement through space. We can use an airflow to deposit bioparticles on a solid surface without requiring air to pass through it, instead of using porous materials where the captured particles are too large to pass through the pores through which the airflow passes. That is, the airflow is deflected by the surface rather than passing through it. In this way, we can use substantially non-porous surfaces, such as glass, metal, painted metal, and plastic, as our impact surface from which the captured biomaterial can then be harvested. In this way, we avoid the problem of filters becoming clogged and needing to be replaced with new filters. Of course, impact surfaces made of porous materials can also be provided, or even, for example, made of a material that will be used as a filter but is "blind" (i.e., does not utilize the depth of the airflow through the filter material).

[0061] The impact surfaces we expose typically lack the adhesive surfaces to which sample particles adhere, as the use of adhesive surfaces can be problematic when sample collection is being conducted using a vehicle that is also used in parallel with other activities such as public transportation or freight transport. However, in some cases, utilizing a substrate that provides an exposed adhesive layer to which sample particles adhere due to the nature of the adhesive, for example, a plastic film can be used to provide the adhesive impact surface, optionally fixed to the screen or panel of the vehicle, and optionally secured by a second adhesive layer on the back of the film.

[0062] For example, our impact surface can be a glass surface such as a window or windshield, or a body surface or panel of a land vehicle such as a motor vehicle (e.g., a car, bus, van, truck, or train), or it can be a cover surface supported or carried on the main surface of such a vehicle. This method allows the use of impact surfaces with areas of tens or hundreds of square centimeters, but typically up to several square meters. The possibility of using an impact surface of one square meter or larger, together with the possibility of maintaining an average speed of 60 km / h or greater for many hours at a time, means that extremely large volumes of air can be sampled relatively easily. For example, even assuming the impact surface is only 10 cm × 10 cm, at an average speed of 60 km / h, the effective volume of air processed is 10 m³ / s. 3 Or 3,600m per hour 3This is compared to the rate of only 300 ml / min reported in Clare et al.'s paper, which allows it to maintain a flow rate of only 30 minutes (9 liters of total air volume = 0.009 m³) before the filter needs to be replaced. 3 (Clare et al. used filters with 0.22 μm and 0.45 μm pore sizes in the air inlet of a peristaltic pump tube from Geotech). Lynggard et al.'s paper reported the use of three air sampling devices—a water vacuum (flowing at 8.8 m / min). 3 The process lasted 30 or 60 minutes, with samples collected in 1.7 liters of sterile milligram water in a vortex chamber, and 24-volt and 5-volt blower fans (flowing at 0.8 m / min). 3 The flow rates were 0.03 m / min for 30 minutes, 60 minutes, or 5 hours, respectively. 3 (Continued for 30 hours), the latter two used F8 type pleated fiber filters for airborne particulate matter. No significant differences in detection were found among the three air sampling devices, but practical differences (size, power and water supply requirements, noise, etc.) mean that the two blower fans are advantageous, despite their lower airflow rates.

[0063] The area that moves at 50 km / h is 1 m² 2 The impact surface travels through 830m per minute 3 The air. Extrapolating this over an 8-hour / day operating period, this equates to approximately 400,000 m³. 3 The volume of air. This capacity is more than 250 times larger than that of the most powerful stationary sampling equipment. The impact surface is the size of an average city bus windshield, say 2.5m wide by 2m high or 5m... 2 With an average speed of 30 km / h, we see 2,500 m / s. 3 The effective air handling volume. Compared to porous filters, the potential for eDNA collection using this method is significantly greater, even with the assumed lower collection rate allowed by the impact surface. Even with a fairly small impact surface, such as 10 cm × 10 cm or smaller, useful results can be expected, for example, by having a consumer-grade drone (which can easily maintain speeds between 30 and 60 km / h for up to 30 minutes) fly along a transverse zone above a land area or region of interest. It should be understood that in all aspects of the invention, the initial phase of aerial nucleic acid capture can be performed using air vehicles such as drones or light aircraft, wherein the impact surface is disposed on or by the exterior of the air vehicle, and the exposed impact surface is non-adhesive; although these methods are not currently claimed, they remain within the scope of the invention.

[0064] The impact surface, or each impact surface, can be usefully positioned on the exposed front surface of the vehicle such that it is transverse to (e.g., orthogonal to) the vehicle's main direction of travel, increasing the likelihood that particles will impact the surface at or approximately the vehicle's speed due to inertia. In this position, the impact surface can be directly observed by a person positioned in front of the vehicle (at a distance and height from which the entire front surface of the vehicle can be seen, which of course may require the person to move themselves or at least their head). However, in some applications, the impact surface, or each impact surface, can be mounted on an outer surface of the vehicle that is obscured by another, further forward portion of the vehicle. For example, the impact surface can be positioned on the outer surface of a trailer or other towing load carrier attached to an HGV (Heavy Gear Vehicle) or other vehicle, obscured by the vehicle's cargo box from the perspective of someone standing in front of the vehicle. Clearly, it is desirable that the impact surface be exposed to air displaced by the vehicle's movement, and care must be taken to ensure this exposure occurs when the impact surface, or each impact surface, is carried by a trailer or other towing entity, despite the presence of the vehicle's cab in front of the impact surface and any streamlined or other airflow-affecting structures.

[0065] If the impact surface is mounted on a ground-based motor vehicle, this can be carried out, for example, on a track (e.g., a railway, subway, or tram track), a metallic road, or a non-metallic road or track, where an average speed of 50 km / h or 100 km / h can be maintained for one or several hours, again making it easy to sample large amounts of air even for vehicles with a relatively small frontal area (e.g., motor vehicles).

[0066] Buoyancy and inertia of airborne particles The size of the particles (or granules) that collect biological material such as eDNA on a large, exposed surface is largely determined by the particle (or granule) inertia. It is unclear how large eDNA particles are, but we assume that DNA is primarily located within cells, and this is why a suitable buffer (e.g., phosphate-buffered saline) is beneficial when harvesting eDNA, as it mitigates cell bursts.

[0067] Based on this assumption, we expect DNA or RNA to exist in different cell / particle sizes. Typical viral particle sizes range from 0.02 μm to 0.5 μm (but these particles can also be encapsulated in larger aerosols, typically less than 1 μm). Bacterial cells can range from 0.2 to 8 μm, and eukaryotic cells from 5 to 100 μm. Furthermore, this eDNA can exist within cell clusters, but the larger the particle size, the more likely it is to settle rapidly, as the density of typical cellular material can be approximately 1000 times higher than that of air. Assuming drag, buoyancy, and gravity act on the particles, and in the 1 μm to 100 μm range, without wind or other forces acting on the particles, we expect the settling velocity (the speed at which the particles can settle from the air) to be 0.2 cm to 15 m / min.

[0068] Heavier particles settle faster and are thus removed from the sampling medium (air). Based on this principle, it is therefore more likely that our method can sample smaller viral and bacterial cells. However, this principle is largely balanced by the fact that we need inertia to allow particles to impact the collection surface. The larger / heavier the particle, the more likely it is to escape from the redirected airflow and collide with the collection surface. This balance between particle settling and inertia is likely why our method is able to collect DNA from both smaller cells / particles (viruses and bacteria) and larger eukaryotic cells simultaneously. This is a unique feature compared to conventional filter-based sampling systems that focus on specific pore sizes and cell sizes, coupled with the fact that filters are prone to clogging due to larger particles.

[0069] Of course, forward-facing (e.g., external) impact surfaces on vehicles will sometimes be struck by flying insects and birds, and may also be struck by spider webs and “bugs” (e.g., ticks, spiders, and small insects) that have fallen or are hanging from roadside trees and street furniture. There may also be effects from bird-dropped prey or other food, and from fecal matter from birds (perched or on their wings) and possibly from small mammals inhabiting roadside trees or street furniture. An “external” impact surface is one directly exposed to the airflow generated by the movement of a traveling vehicle (relative to the vehicle), allowing optimal use of the inertia of biological particles present in the airflow. External impact surfaces may be slightly enclosed around their perimeter, provided that the airflow on the impact surface is not obstructed to the point of significant stalling.

[0070] Suitable examples of further processing the collected biological material to reveal information about the presence of organisms and, optionally, the populations in the surveyed or monitored area / space will be described later, but first we will give an overview of exemplary general methods that we have found effective for identifying the source of biological material harvested from the air.

[0071] Figure 1 This is a flowchart illustrating elements of a possible method for processing biological material collected from the air according to an aspect of the present invention, including various optional elements.

[0072] Phase 100 involves collecting biological material from the air (here, for brevity, broadly referred to as eDNA). At step 108, the actual collection is performed by moving a vehicle along a cross-section through the sample space to allow the eDNA to adhere to the impact surface carried by the vehicle. Typically, eDNA collection is preceded by a series of planning steps, where a survey protocol is designed, taking into account the extent and definition of the area or zone to be investigated, and also the details of what the survey is looking for (in a biological sense). For example, whether one or more identified species or taxa are being searched (to confirm their presence or absence), or whether a more general biodiversity survey is being conducted. Surveys targeting the identification of invasive alien species (IAS) can be targeted, but they have been found useful for non-targeted species detection, such as through eDNA metabolic encoding, as this provides the advantage of detecting novel IAS as well as broadly characterizing biodiversity.

[0073] At step 104, the accessibility of the area to be investigated is considered, particularly the extent to which transport routes (e.g., roads, tracks, paths, railways, tram lines, waterways, etc.) pass through the area, and the extent to which vehicles traverse such transport routes. If the area to be investigated is too sparsely covered by suitable transport routes, it may be necessary to consider using one or more aircraft, such as drones, micro-lights, or light aircraft, as collection tools. This is most likely to occur in more remote rural areas, but aircraft can be useful for ensuring adequate coverage of large survey areas, even if the area is close to urban areas. For use as a collection device, a suitable aircraft may be provided with an external impact surface, which may be a non-sticky surface (in this case, the collection surface is non-sticky) to which particles adhere during use. The external impact surface may be a surface specifically added to the vehicle, such as glass or a sheet of plastic, or it may be an existing vehicle surface, such as a windshield or body panel, or some combination of components of the vehicle surface.

[0074] At step 106, consider time-related factors—potentially related to the nature of the target biology (e.g., whether the target biology is a nocturnal or diurnal species—this may be more relevant to insects (such as moths) than to large mammal species (such as badgers), and seasonal behaviors (such as hibernation and reproduction)) and relevant transport times (if potential primary vehicles or vehicle categories are to be utilized (e.g., public transport, delivery, or transport vehicles)). The time of year (summer or winter), public holidays, days of the week, school term time, etc., may need to be considered, as each of these can affect tire usage (including the routes taken) and the frequency of public transport, and may also affect freight transport routes and frequencies. Scheduled vehicle parking times, such as cleaning, driver changes, and arrival / departure times at public transport hubs and destinations, may also need to be considered to ensure efficient and economical collection and harvesting of eDNA.

[0075] After the biological material has been collected on the collection surface (also known as the impact surface), the second stage 110 samples the biological material. Collection or harvesting 112 may be performed, for example, by wiping with a suitable collection fluid 114 (e.g., using rollers, wipers, sponges, or wiping materials, typically pretreated with a suitable collection fluid 114) or rinsing the collection surface with a suitable collection fluid 114 (e.g., if the collection surface is a component of a vehicle that has been traversed through the sample space), or by first removing the collection surface from the vehicle (e.g., if the collection surface is a dedicated surface that has been added to the vehicle, such as a dedicated surface carried by the vehicle but easily removed from the vehicle), and then processing, for example, possibly washing the collection surface with a suitable collection fluid 114 after dividing the collection surface into multiple pieces. The harvested biological material may then need to be preserved (possibly still attached to the collection surface removed from the vehicle or to rollers, wipers, sponges, wiping materials, or filters) to maintain the integrity of the biological material (e.g., DNA, RNA, or protein), for example by placing the material in a temperature-controlled environment (e.g., in a refrigerated environment) and / or by adding a preservation buffer that allows the sample to be stored and transported at ambient temperature without degradation.

[0076] Subsequently, and typically in a suitable laboratory with a controlled environment to minimize the risk of cross-contamination, molecular analysis 120 is performed on the samples. Initial processing 121 involves preparing the samples for purification of DNA, RNA, and / or proteins or other biological material. This typically involves washing away the sampling matrix (roller, wiper, filter, sponge) or washing the removed collection surface with a buffer such as phosphate buffer (or other suitable liquid) to collect the obtained biological and cellular material. The biological and cellular material can then be concentrated from the liquid (buffer) suspension by centrifugation. For example, RNA 123, DNA 124, or protein 125. The concentrated particles can then be purified 122 using commercially available reagents and methods, for example, as described further later.

[0077] The extracted DNA can be used for population genetic studies 126. The extracted DNA and / or RNA can be used for qPCR analysis 127, metabolic coding 128, and / or non-targeted sequencing 219. Generally, we are not interested in collecting or analyzing human DNA: the focus is on extracting non-human DNA / RNA / proteins from the collected biological material. In particular, we are generally not interested in processing to isolate individual human markers. However, there may be situations where collecting human DNA for analysis is useful, and sometimes it can even be selectively used to isolate individual human characteristic markers.

[0078] It should also be understood that we may be interested not only in identifying animals, but also in identifying plants and / or fungi. For example, we may be interested in identifying the presence of invasive or problematic plant species, such as Japanese aster.

[0079] Bioinformatics processing 130 is then applied to the results obtained in the molecular analysis phase 120, optionally identifying aspects such as genetic variation, deriving all identified species, determining relative species abundance, or characterizing the genome and / or deriving the (potential) activity of the organism. Using RNA or DNA to identify functional or active genes (independent of the taxonomic identification of the organism) can tell us a variety of things about the environment. Particularly for bacteria, this can help us determine whether more genes have been detected to, for example, promote nitrogen cycling between regions. Quality filtering 132 is typically applied, followed by denoising and allocation of taxon readings.

[0080] Step 5, 140, involves data delivery, the first step of which, 142, is to determine the temporal and spatial probabilities of the existence of taxa. After this, summary indices and visualizations can then be prepared at 144.

[0081] For meta-coding laboratory analyses, the bioinformatics process follows best practices outlined in the literature and provides a set of quality-controlled (QC) readouts—the output of the sequencing machine—including nucleotide strings and associated quality scores. These are not necessarily unique in the sample, but rather provide the basis for inferring unique DNA or RNA sequences present in the collected samples, amplified by the primer pairs used. The final output may be in the form of a table with taxon counts (the number of reads assigned to each taxon) and measures of signal intensity for each taxon in each sample. The specific methods used to achieve each of these incremental results are not necessarily interdependent and can be substituted later. Suitable methods will be discussed later.

[0082] If the laboratory procedure used is shotgun metagenomics (also known as whole-genome metagenomics), the bioinformatics analysis needs to be adapted accordingly based on best practices in the literature to include: Visualize and adjust readings based on their quality fraction; Assign reads to the genome; Identification / recognition of predicted gene sequences; and The predicted gene sequence is mapped / localized to the detected protein domain.

[0083] If the laboratory procedures used are population genetic analyses, the bioinformatics analyses need to be adapted according to best practices in the literature, including: Identify molecular markers from raw sequencing reads; and estimate the number of individuals from the genetic diversity observed in the molecular markers.

[0084] It should be understood that the described methods for collecting biological material from the environment are applicable not only to biodiversity assessments but also to survey procedures focused on individual species or target groups, whether the species or group is being monitored for conservation reasons or because it is considered at risk. In other words, the described techniques can be usefully applied to detect the presence of known rogue / unnatural species, known pests or animal / plant carriers, and at-risk, dangerous, or vulnerable species.

[0085] Having established the scenario, we will now consider aspects related to the initial collection of biological material by moving along the cross-sectional zone through the sample space via a collection surface. Later, we will discuss the definition and selection of the cross-sectional zone, as well as the timing and location of sample harvesting.

[0086] Figure 2A simplified view of the front of a pair of vehicles / transport vehicles (city / transport bus 200 and HGV truck 250) is shown, which are examples of larger vehicles that can be used to perform traverses to collect eDNA from an area to be investigated (smaller vehicles with smaller front areas, such as light transport vehicles and automobiles, can also be used in this new technology). These two vehicles are wheeled land vehicles; other examples include trains and trams, but other land vehicles (such as water vehicles (e.g., boats and other vessels)) and non-wheeled land vehicles (e.g., tracked vehicles, hovercraft) can also be used to collect airborne biological material, as can aircraft (such as light aircraft and drones, as discussed elsewhere).

[0087] Bus 200 will typically have a total height of about 3 meters (e.g., 2.99 meters) and a width of about 2.5 meters (typically 2.55 meters). The front surface of bus 200 is generally flat, but is usually arranged vertically or nearly vertically in use, with a glass windshield 202 that extends across the entire width of the front surface and typically has a vertical extent of at least 1.5 meters. Above the windshield 202 is a body panel 204, which is generally flat and typically houses the glass panel, behind which an array of indicators 206 can be mounted to indicate destination, route and / or route or bus number. Below the windshield 202 is another body panel 208, which is generally flat and may contain headlights 210.

[0088] Truck 250 will typically have a width of approximately 2.5 meters and a total height of approximately 4 meters (ranging from approximately 3.75 meters to approximately 4.2 meters). Like bus 200, the front of truck 250 can be generally flat, although truck cab designs tend to vary more significantly than city bus front-end designs. The windshield 252 of truck 250 again extends across almost the entire width of the front and typically has a vertical extension of at least 1.5 meters. Above the windshield 252 is the body panel 254, which can be generally flat and can be vertically mounted, or it can be tilted rearward to reduce wind resistance or simply for aesthetic reasons. Typically, the lower end of the front of truck 250 includes a collision-absorbing bumper unit 260, which, for pedestrian safety reasons, can have a generally flat front and typically has a vertical extension between 30 cm and 60 cm or greater. Between the lower edge of the bumper assembly 260 and the windshield 252 is another body panel 262, which may include a grille 263 having bars 264 separated by gaps 266 through which air can flow to one or more radiators (heat exchangers) mounted, for example, behind the grille 263. The bumper assembly may include a pair of headlights 270.

[0089] When any of these vehicles 250, 252 is driven through open spaces (such as urban or natural environments), eDNA (and other biomaterials) from the environment will be deposited on the vehicle, particularly the front. Our experiments have shown that this biomaterial tends to remain on the vehicle's surface under normal conditions, making it subsequently harvestable from the vehicle's surface. We have successfully harvested the biomaterial from the front of such vehicles using paint rollers (the type of synthetic material sponge, short-pile, or long-pile "hairy" fabric rollers used by trimmers to apply paint to the walls of buildings; these rollers are widely available in a wide range of sizes, allowing for selection of the appropriate roller size based on the size and shape of the vehicle parts being treated). Generally, we favor the use of "hairy" rollers (short-pile or long-pile) because it is easier to wash the biomaterial off from such rollers than from sponge rollers. Short-pile rollers are useful because their smaller diameter makes them more suitable for collecting biomaterial from discontinuous surfaces such as grilles, gaps around headlights, etc. Pre-soaking the paint rollers in a suitable buffer solution (e.g., phosphate buffer) before sample collection tends to increase the adhesion of biological material to the roller matrix. We also successfully harvested biological material using synthetic fabric wipers and acrylic sheets (including A4 overhead projector transparent material) adhered to bus windshields. After the collection phase, the acrylic sheets were removed from the carrier and taken to the laboratory for the harvest phase. Pre-soaking the fabric wipers in a suitable buffer solution (e.g., phosphate buffer) before sample collection tends to increase the adhesion of biological material to the matrix of the collection device.

[0090] Experiments conducted on municipal buses also demonstrated that eDNA (and other biological materials) adhered particularly well to glass surfaces in practice, such as the glass panels of the windshield 202 and the indicator array 206. Furthermore, our results indicate that valuable biological materials can be surprisingly collected from the windshield 202 even after being swept away by the vehicle's windshield wipers (and washers).

[0091] It is possible that even after the vehicle has been cleaned, a significant amount of biomaterial may remain adhered to the windshield wipers (blades and / or frames), so it may be advisable to avoid taking samples from the windshield wipers unless the presence of material captured earlier in the journey is not a problem—for example, based on the route traveled and the objective behind the biomaterial harvest.

[0092] Similarly, using what might be called a vehicle's natural surface as an impact surface for collecting biological materials from the air, the large front area of ​​vehicles (such as buses, coaches, delivery vehicles, trucks, trains, etc.) means that a usefully large (e.g., 100cm) impact surface should be found. 2 1m2 The space for a removable collection surface (or larger). A removable, optionally self-adhesive plastic film (such as vinyl or other suitable material) can be applied as a wrapping to the main panel / body panel or a portion of the main panel / body panel, and then removed with the collected biological deposits intact. This method skips the surface cleaning (sterilization) step to remove previous DNA traces before collection and will ensure that biological information is indeed collected during that particular sampling trip. We have successfully used adhesive-backed plastic films that are already adhered to the outer surface of the vehicle's windshield, such as colored foils or films sold as vehicle sunscreens or exterior window tints.

[0093] As previously mentioned, if it is desirable to provide an impact surface with an adhesive side, a plastic film with adhesive on both sides can be used, such that one adhesive layer is used to adhere the film to a support surface of the vehicle or for it to be carried by the vehicle, and the other adhesive layer is used to provide the impact surface. We have successfully used this method to release captured biomaterial by washing the outer adhesive layer and its bioload from the film using a suitable detergent solution.

[0094] Alternatively, the plastic film roll can be used in conjunction with a mechanism that moves the film from a supply source to a winding device, stretching the film, for example, over a portion of the front of a vehicle, to provide a progressively renewed impact surface by winding the film from the supply source to the winding device. Preferably, the film is supported, for example, by a relevant part of the vehicle body, so that the film does not swing freely under the influence of airflow over the vehicle as it moves. As previously mentioned, such a film, if sufficiently transparent, can be used to cover all or part of the vehicle's windshield. To harvest the collected biomaterial, the film used is removed from the carrier for processing in a laboratory. This "active" impact surface may include a marking arrangement that timestamps and / or positions the film, making it possible to identify locations along the length of the film corresponding to known times and / or locations (vehicle navigation systems, such as satellite navigation systems, can record details of the vehicle's journey, making it possible to know where the vehicle went, when it was in any particular location, and how long it spent at any location). Optionally, it may also be beneficial to use a suitable airborne weather device (based on a suitable chip) or some external source to collect atmospheric data (such as temperature, humidity, etc.).

[0095] A mechanism can be provided to move a plastic film over an impact zone located between a film reservoir or storage container and a winding device, which is arranged to remove an exposed portion of the film from the impact zone after a certain period of time (or after traveling a certain distance), wherein a new length of film advances from the storage container to the appropriate position at the impact zone. Optionally, the winding device can be arranged to advance a sufficiently long length of film after each “exposure” such that the exposed film, while being wound in the winding device, cannot transfer its captured biological material to either side of the film at another “exposure” location. It should be understood that without this, there is a risk that biological material captured on the exposed side of the film may be transferred to the back side of another (adjacent) length of film, such that a single “frame” of the film may then contain biological material from two or more exposures, which diffuse across the front and back surfaces of the film. Preferably, a system for marking the film (before or after exposure) also exists, such that the film can be cut into individual exposures, which can then be processed individually to provide information about the biological material collected during the relevant exposure of the film. By synchronizing the exposure period with the location (a cross-section or part of a cross-section) based on data such as navigation system data, tracking device data, or waypoint data, a series of "bio-snapshots" that can be mapped to real-world locations can be obtained. This method is particularly useful for bio-mapping of vehicles that do not necessarily follow regular routes between location pairs (e.g., vehicles traveling from London to the British Midlands using M11, M1, A1, or M40 depending on traffic density and accident reports), especially vehicles traveling between locations that are very far apart, such as road transport vehicles, rather than typical public transport vehicles. This method would also potentially have significant benefits if aircraft were used to perform sample capture, as it would allow for extended capture periods by maintaining sample separation from different cross-sections by using a new "exposure" for each new cross-section, while maintaining the ability to analyze results from different cross-sections individually. The use of solar-powered drones with such multi-"exposure" capture mechanisms would be one way to reduce the cost of performing capture using aircraft (which is arguably the biggest drawback).

[0096] As an alternative to plastic films, other removable collection surfaces can be mounted on vehicles for collecting biological materials such as eDNA. For example, FTA (Flinders Technology Associates) cards can be mounted on vehicles (e.g., on the front panel or windshield) to capture airborne biological materials as air flows over / passes through the moving vehicle (these cards can be damaged by rain or prolonged exposure to sunlight, so this needs to be kept in mind when considering how and when they are used in this application). Similarly, panels or other forms of material can be mounted on vehicles to provide a removable impact surface, such as panels of metal, plastic, or even glass. In fact, the discovery that airborne biological materials adhere particularly well to glass substrates means that using removable glass panels as impact surfaces is attractive. Glass screen protectors (e.g., made from Gorilla Glass (RTM) and widely used in smartphones and tablets) are very tough, and the largest glass screen protectors (e.g., the 12.9-inch (32.77cm) glass screen protector used in Apple's iPad Pro (RTM)) have a travel of over 500cm. 2 The surface area. This glass panel can be securely held in a suitable retainer, for example, clamped in place in a frame that securely attaches to the vehicle's structure, fixing the periphery of the glass panel. A suitable retainer can be semi-permanently fixed to the vehicle's body panel, for example, using threaded fasteners screwed into tie nuts inserted into the vehicle's body, and using eccentric or other quick-release clamping arrangements to hold or clamp the impact surface in place within the retainer. Preferably, if the impact surface is provided by a glass sheet, the retainer is configured not only to support the periphery of the sheet but also to provide (preferably) an elastic backing arrangement, such as using plastic (e.g., neoprene) foam or sponge rubber, to reduce the risk of the sheet breaking due to impact with a projectile such as a stone. Such a backing arrangement may not be possible when mounting the sheet to cover the underlying display surface or other surfaces (such as lenses for lights or indicators) without significantly reducing the visibility of the underlying surfaces.

[0097] Pedestrian safety regulations preclude the installation of glass panels below approximately 2 meters above the ground; however, panels can be installed above the upper edge of windshields 202 and 252, for example, on panels 204 or 254. Given the high transparency of the glass panels, it is even feasible to install them in front of the glass panels used for indicator array 206 without significantly impairing the visibility of the indicator panels, and they could even be installed to cover at least a portion of the windshield. Clearly, such glass panels can be easily and conveniently installed on other vehicles, both large and small, and they do not require the application of adhesives or culture media to capture and retain airborne nucleic acids. Such panels would even be suitable for installation on lightweight aerial drones as a capture surface, provided the aerodynamic and flight behavior of the panels are properly considered. After the vehicle has performed one or more cross-stripping operations on the space to be investigated, the glass panels can be removed for laboratory harvesting of biological materials, or materials can be harvested while the panels remain in their proper position on the vehicle.

[0098] Vehicle grilles (such as 263) will typically provide suitable collection surfaces, such as grille bars 264, which are directly exposed to airflow as the vehicle moves. Biomaterials can be conveniently harvested from the grille using small paint rollers (e.g., those with lengths between approximately 2.5 cm and 15 cm).

[0099] Preferably, the collection surfaces (if they are not already cleaned) are cleaned before traversing the cross-section to obtain biological material. For example, a 10% bleach solution can be used for cleaning. Apply the bleach solution and allow it to act for 2–3 minutes. After bleaching, the surface should be thoroughly rinsed with distilled water and allowed to dry. A 70% ethyl alcohol solution can be applied to accelerate drying. Additionally or alternatively, because on-site cleaning is unlikely to be 100% successful in removing DNA from the surfaces or other parts of the collection device, it is also possible to collect the existing biological material (samples) before cleaning the device and then take these prior waypoints into account when interpreting data subsequently obtained from the cleaned device or surface.

[0100] All substrates used for collecting biological material should be cleaned and free of contaminating DNA. If necessary, cleaning can be performed using, for example, a 10% bleach solution followed by thorough rinsing with distilled water, or, if the substrate and housing materials permit, cleaning can be performed via a suitable autoclave cycle (under high temperature conditions). Prior to sample collection, it is preferable to pre-soak swabs, rollers, filters, and sponges in a suitable buffer solution (e.g., phosphate buffer) to increase the adhesion of the biological material to the substrate. Collection devices can be individually packaged in sealed containers to keep them uncontaminated (preferably, the collection devices are sterile and maintained in this state through suitable, ideal individual packaging).

[0101] After collection, the samples are then properly preserved to prevent degradation of the biological material and to maintain the integrity of any DNA / RNA proteins. For example, samples can be refrigerated and maintained at a temperature of approximately 4°C, including during transport. In certain cases (e.g., samples in conical tubes), preservation buffers can be added, allowing the samples to be stored and transported at ambient temperature. Removable impact / collection surfaces can be transported intact to the laboratory, where they undergo processing to harvest the collected biological material, such as by wiping, washing, etc., or these processes can be performed outside the laboratory before the resulting samples are sent to the laboratory.

[0102] The collected samples, appropriately labeled, are then processed. As a first step, the relevant biological material (DNA, RNA, protein) is extracted and isolated from the sampling device. In the laboratory, samples are processed and prepared for, for example, the purification of DNA or RNA. Different matrices undergo different processes / protocols / routines. Examples of suitable protocols / routines are illustrated here: 1. Wash away any rolls, sponges, filters, cones, and plastic / charged surfaces collected in the sampling bag with freshly prepared phosphate-buffered saline (PBS) (1 L prepared by adding 8 g sodium chloride; 0.2 g potassium chloride; 1.44 g disodium hydrogen phosphate and 0.245 g potassium dihydrogen phosphate. Adjust the solution to pH 7.4). After washing away the matrix, concentrate the biological and cellular material from the buffer suspension by centrifugation. The microspheres were then used with the commercially available Qiagen Blood & Tissue Kit (Qiagen) according to the manufacturer's instructions (Example reference: Clare EL et al., eDNAir: proof of concept for collecting animal DNA from air sampling. Peer J. 2021 Mar 31br 9: e 11030. doi: 10.7717 / peerj.11030. PMID: 33850648; PMCID: PMC8019316).

[0103] 2. Cut the air-dried FTA card into fragments and place them in a 2 mL microtube. The swab was also collected in the microtube. DNA was extracted from both the FTA card and the swab using the same commercial kit, the Qiagen Blood & Tissue Kit (Qiagen), following the manufacturer's instructions. (See references: Deiner K et al., The choice of capture and extraction methods affects the detection of freshwater biodiversity from environmental DNA. Biological Conservation. 2015; 183: 53-63.; Tsuji S et al., Detection of aquatic macroorganisms using environmental DNA analysis - A review of methods for collection, extraction and detection. Environmental DNA. 2019; 1: 99-108.) Relevant biological materials, such as DNA, RNA, and proteins, have been extracted and separated for analysis.

[0104] In the case of DNA and / or RNA, the purified genetic material is analyzed using specific techniques, depending on the question posed.

[0105] i) For targeted detection of specific species or taxa, we use PCR to analyze DNA: a. Real-time PCR (a technique in which the amplified DNA product (or amplicon) can be recorded in real time as the reaction progresses, and the product is quantified after each cycle based on fluorescence detection) b. Or digital PCR (a specialized method for the detection and quantification of nucleic acids by estimating the absolute number of molecules using statistical methods. In this method, the PCR reaction mixture is digitized into microreactions of 20-30 kN / L size. Because this digitization process distributes the PCR mixture across so many microreactions, each microreaction will effectively contain one, zero, or only a few target nucleic acid molecules. The isolated microreactions are then amplified, and data are collected from each microreaction at the end of the thermal cycling process. Microreactions that do not contain the target will not show post-amplification fluorescence, while microreactions that contain the target will show post-amplification fluorescence). This method requires us to use a pair of primers (DNA sequences of 18 to 24 bases in length) that must specifically target the DNA of the species or taxa of interest and clearly distinguish them from closely related taxa.

[0106] Depending on the target of interest, we can use primer sequences previously described in the literature or design our own primers, using reference sequences published in public databases (e.g., Genebank; EMBL; SILVA, etc.). Good results were obtained with primers targeting two different 16S targets and COIs. Generally, we have found that using more than one primer can be beneficial, as each primer can reveal the presence of species not revealed by other primers. Thus, for example, we discovered broader population information by using three named primers than by using any one or two primers.

[0107] PCR reagents are commercially available from leading companies in the molecular biology field, including Thermo Fisher, BioRad, and Roche. PCR can also be used to analyze RNA in specific environments. RNA analysis can be performed to identify and quantify the expression of specific genes that can indicate an organism's activity, resistance (e.g., pollutants, antibiotics, etc.). The first step in RNA analysis is to convert RNA into DNA using standard reagents, which are also commercially available from leading companies in the molecular biology field, including Thermo Fisher, BioRad, and Roche.

[0108] After converting RNA into DNA, the same procedure and reagents described above can be used.

[0109] ii) Metabolic coding analysis of DNA or RNA. Metabarcoding is the labeling (barcoding) of DNA / RNA in a way that allows for the simultaneous identification of multiple taxa and / or organisms within the same sample. This analysis is used, for example, to characterize insect diversity in a specific green area, or bacterial communities (microbiomes) in a soil sample, or to define the species of marine mammals and fish in a marine area.

[0110] Barcoding a specific sample is accomplished by combining a unique barcode sequence with a primer sequence specific to certain taxa / organisms of interest. Multiple unique codes are available, allowing the labeling of multiple samples and multiple taxa / organisms of interest. Barcoding is performed via PCR, and taxa / organism-specific primers for metabolic encoding are extensively described in the literature.

[0111] In the laboratory, the selected primers are validated for specificity and performance in PCR. PCR conditions vary depending on the primer sequences and can be modified according to the sample type. These optimizations are typically empirical. PCR reagents are commercially available from leading companies offering molecular biology products: Thermo Fisher, BioRad, Roche, etc.

[0112] The barcoded DNA products derived from the PCR (library) are then analyzed by next-generation sequencing (NGS) using one or more high-throughput sequencers. Suitable sequencers are available from Illumina, such as the MiSeq and NextSeq models (with varying analytical capabilities and outputs). Suitable techniques for an analytical pipeline that begins with a DNA sample and ends with NGS (amplicon sequencing) analysis of the DNA library are available from manufacturers of high-throughput sequencers (e.g., from Illumina).

[0113] Biological materials collected as described above (e.g., eDNA) can also be the subject of non-targeted DNA or RNA NGS analysis. Non-targeted NGS analysis does not use specific primers to amplify the sample during the library construction process. Therefore, DNA and / or RNA throughout the sample can be sequenced without prior knowledge or selection of the taxa / organisms to be analyzed. This analysis is performed when the derivation of organisms that may be present in a given sample is unknown beforehand. Suitable commercially available reagents and corresponding techniques for processing DNA samples and generating DNA libraries for NGS analysis are available from common suppliers (and described in the literature).

[0114] Following laboratory analysis, the generated data can be processed bioinformatically to determine genetic variability, derive all identified species, determine relative species abundance, or characterize the genome and / or derive the (potential) activity of organisms.

[0115] For the meta-barcode laboratory analysis mentioned in the preceding section, the bioinformatics process provides a set of quality-controlled readings (sequencer output, consisting of nucleotide strings and associated quality fractions; these are not necessarily unique in the sample), inferences of unique DNA or RNA sequences amplified by the used primer pairs present in the collected samples, and a table as the final output containing taxonomic counts (the number of readings assigned to each taxonomic group), a measure of the signal intensity for each taxonomic group in each sample. The specific methods for achieving each of these incremental results are not necessarily interdependent and can be substituted later. Exemplary suitable methods include the following: Sequencing quality filtering: Due to the nature of PCR amplification used in meta-barcode analysis, the correct output readings from the sequencer will include the sequences of the primers used for amplification. To exclude other readings, read filtering software such as Cutadapt is used to detect primer sequences in the readings of each sequencing library. Readings that do not contain sequences belonging to the primer pairs used for amplification (or, when using paired-end sequencing), are removed from the remainder of the analysis (allowing for some sequencing errors). Readings below a certain quality threshold (Phred score, a confidence metric reported by the sequencing device that can be converted into a probability of error) or readings with an expected number of errors above another threshold are then filtered out. These thresholds can be manually defined or estimated from the data using appropriate software.

[0116] Inferring the unique sequence in the sample: The general process in this step is called "denoising." It involves evaluating the sequence in each read and its associated quality score, followed by grouping those reads that, given the estimated error probability (from the Phred score mentioned above), might represent the same original sequence. Several denoising packages are available, such as DADA2. When using paired-end reads, packages like DADA2 also perform the necessary trimming and fusion of read pairs. The required parameters (the position of the truncation of the read, the resulting length of the fused read) can be manually defined or estimated based on the data. A reasonable approach is to first try automatic estimation, and if the results are unsatisfactory, to manually set the parameters based on previous experience with primer pairs used to amplify the sample.

[0117] Assigning readings to taxa: This step can be done in various ways. For example, using a Naive Bayes classifier method as implemented in Qiime2. Naive Bayes classifiers are a family of probabilistic classifiers used for text classification in other applications. They are also used to assign classification information to eDNA sequences. Classifiers are created by training on a set of sequences with known classification annotations. Optionally, these classifiers can be trained on sequences expected to be amplified by each set of primers. In cases where the same sequence can match more than one species, the uniqueness and ambiguity of these expected sequences are checked first. During sample sequencing, the classifier created for each primer pair used in the library is applied to the inferred sequences of the samples identified in the previous step. The classifier outputs a classification assignment for each sequence above a selected confidence level (typically 95%). If the classifier cannot achieve species-level recognition above the confidence level, it attempts to report a genus-level classification above the confidence level, and so on, moving up the classification hierarchy.

[0118] The analysis can be re-performed from each step. For example, the identification of taxa associated with each sequence can be redone at a later stage to take advantage of a more complete database. This allows for continuous improvement of the data, even without new samples. The metabolic or ecological functions associated with each taxa can also be improved as new data (internal and external) are added at later stages. For example, a species detected at a previous time point may later be found to be a key pollinator.

[0119] Conversely, if the laboratory procedure used is shotgun metagenomics (also known as whole-genome metagenomics), then the bioinformatics analysis needs to be adjusted accordingly. This will require: Readings can be visualized and adjusted based on their quality scores using software such as FastQC and Trimmomatic. Readings are assigned to the genome using software such as mOTUs2; Predicting gene sequence identification; Predicted gene sequences are mapped to detected protein domains from databases such as Pfam, InterPro, or KEGG.

[0120] The metabolic potential of a sample can be better characterized based on the identified protein domains.

[0121] The third laboratory technique used to process samples is population genetic analysis. This technique identifies molecular markers of individuals, such as single nucleotide polymorphisms (SNPs), precise locations in the genome where specific nucleotides (or letters) of DNA may vary between individuals. This will require: Identify molecular markers from raw sequencing reads; Genetic diversity observed from molecular markers is used to estimate the number of individuals.

[0122] We will now consider the issue of determining the collection procedure, including the selection of cross-segments. Aerial DNA collection along cross-segments can be performed using various means of transport (or vehicles) via aerial DNA capture. In many cases, these vehicles are subject to operational constraints along the cross-segments they move along, such as public bus routes, rail networks, ferry and transport channels, transport vehicle networks, truck transport schedules, general road access, and, for example, aerial idleness for drones and other aircraft.

[0123] The design of the sampling cross-section is determined by the survey objectives and operational constraints. The following three survey objectives may be relevant to many different cross-section design considerations: i) Continuous *survey of aerial DNA in a region or country To investigate aerial DNA on a significant scale (>10,000 km²) within a region or country (e.g., to determine biodiversity, identify IAS, detect target taxa, or even identify populations), sufficient sampling is required to achieve the desired spatial and temporal resolution and significantly reduce survey costs. To achieve this, utilizing existing transport networks (i.e., public bus routes, rail networks, ferry and shipping lines, postal vehicle routes, delivery vehicle networks, etc.) is considered the most prudent approach. Therefore, a thorough understanding of these routes and their schedules is helpful in this context to allow for sample collection (harvesting) during long periods of inactivity or at (overnight) warehouses. In any case, cross-sections will preferably collectively cover (or at least span) the entire area to be investigated (or at least most of it, such that additional sampling trips sufficient to cover the remainder of the area do not need to be numerous or difficult to arrange), intersect each other, and provide numerous opportunities for repeated sampling (i.e., multiple cross-sections at the same or closely adjacent locations). In many cases, logistical / logistical constraints and road networks can hinder an ideal survey design. An ideal survey design would be a set of orthogonal vertical and linear cross-sections spaced apart in a manner that simulates the required spatial resolution. In this ideal case, each cross-section intersects another cross-section only once, and the distances between the lines are stable and easily resolved in further computational steps.

[0124] In the real world, two key aspects must be considered that lead to significant deviations from the ideal orthogonal & perpendicular set of intersecting cross-sections: i) road networks and public transport routes tend to be more densely spaced and converge in densely populated (urban) areas, and ii) lines are not straight and can therefore intersect each other in a variety of cases, or even extend parallel at significant distances. These two complexities can be partially solved computationally if sufficient cross-sections and sampling events are available. Furthermore, output maps can be computed in a way that depicts uncertainties in detection (e.g., a measure of the probability of detecting / presence of a taxonomy at mapped grid locations) and varying spatial resolution (the size of the mapped grid locations). To meet the survey objectives, it is therefore important to understand the computational possibilities in each survey design and combine them with logistical and operational possibilities. Additionally, it is important to collect the timestamp coordinates or routes traveled by these vehicles during the sampling period.

[0125] Geographical continuity may be the goal, but conducting surveys that are also quasi-continuous in a temporal sense may also be of interest (although the use of cross-sections conducted by public transport vehicles may inevitably introduce time gaps in survey data collection).

[0126] ii) Specific comparative studies of aerial DNA across space or time Limiting variations in eDNA collection methods is highly helpful when using this technology to compare two or more measurements of airborne DNA (i.e., taxa in a region (e.g., the same location, different times) or to compare taxa in two or more different regions. This means that the same or similar vehicles or collection devices / methods are preferably used to collect material samples from the air. This is also helpful if elements such as speed of movement, time of day, and weather conditions are the same or very similar.

[0127] In some cases, track or road layout or access restrictions will determine the likelihood of consistent sampling between stations or over time. In such cases, these variations should be closely captured by collecting maps, travel speeds and schedules, weather conditions, vehicle types, and collection methods / devices to enable the determination of optimal collection schedules and methods.

[0128] To effectively survey an area and generate accurate measurements of the presence of organisms via airborne DNA, multiple cross-banding operations or along various routes are typically required to obtain multiple samples. Environmental DNA possesses inherent randomness primarily related to the ecology and physiology of the source organisms, along with unknown retention rates of (airborne) DNA molecules to environmental factors (UV exposure, dryness, humidity, etc.) and their dispersibility from the source. Therefore, it is helpful to enhance the capture potential of true positives and limit the risk of false positives by using multiple eDNA collection events.

[0129] If done correctly (i.e., with very limited variation in collection devices / methods between measurements and a statistically robust sample size), the data delivered through this study can provide the relative abundance of airborne DNA and can potentially be used to infer (relative) species abundance, as well as the likelihood of its presence or absence.

[0130] iii) Detection of target taxonomic groups or clusters In cases where only specific airborne DNA sequences need to be detected, limiting measurements to the primary site may be sufficient. In such cases, working with positive and negative controls / controls in the laboratory is important because comparative sample data is limited. It is also recommended to obtain clear negative and positive field controls / controls within or around the lesion site using the same sampling methods, and to collect multiple biological replicas (i.e., environmental samples obtained under identical conditions or in parallel) to reduce the likelihood of false positives.

[0131] Seasonality and weather conditions can also affect species activity levels, DNA shedding rates, and dispersion. Therefore, collections conducted across multiple seasons, times of day, or weather conditions may help to establish a more complete picture of the biology of the surveyed area.

[0132] Data delivered through such research can provide evidence of the existence of aerial DNA, which can then be used to infer the existence of species.

[0133] In addition to the purposes mentioned above, the following processes related to eDNA ecology can be usefully considered for eDNA collection and sampling design.

[0134] a) eDNA origin Attempts are made to predict the origin of genetic material collected as eDNA, or to link its detection to species physiological functions (e.g., metabolism and body weight), specific ecological traits (e.g., reproductive time, behavior, locomotion, activity patterns and trophic levels (predators, pests)) or physical living environment.

[0135] b) eDNA Fate Linking biological and abiotic environmental conditions facilitates the detection of organisms via eDNA, taking into account their impact on the persistence, degradation rate, and detection capability of eDNA in certain taxa.

[0136] c) eDNA transport The detection of airborne eDNA involves biological agents capable of transporting genetic material through diffusion, mixing, sedimentation, and biological mechanisms, as well as anthropogenic interactions between natural species and humans. For example, the analysis could include probability maps that take into account prevailing wind directions, as wind is likely the most potent mechanism for DNA transport, dispersion, and dilution over long distances. Furthermore, when analyzing eDNA results, biological mechanisms and anthropogenic interactions can be considered (e.g., birds consuming worms release worm DNA into the air, or hedgehogs killed by collisions (roadkill) release large amounts of DNA into the air over extended periods).

[0137] Although not fully understood, humidity is believed to affect the atomization of DNA particles, viruses, and cells, and thus, dispersion. Furthermore, humidity is believed to influence the likelihood of airborne DNA adhering to surfaces for certain collection methods.

[0138] Weather conditions can also limit or enhance DNA transfer into the air. Weather can influence the behavior and interactions of certain species. Railways and wind can agitate soil and vegetation, releasing more DNA from particles and surfaces into the air. Furthermore, wet roads will result in more spray mobilizing more DNA from road surfaces. Meanwhile, rainwater may cause DNA to be removed from collecting surfaces through runoff or the use of windshield wipers.

[0139] Our experiments also demonstrate that DNA from marine organisms can be collected using this novel material collection method, even at a certain distance from the ocean, but not under all conditions or always at a similar distance. It can be hypothesized that wave action causes DNA from the ocean or water to be transferred into the air. Finally, it is thought that snow cover or ice may limit DNA transfer from soil, vegetation, or aquatic environments.

[0140] Depending on the research objective, various weather conditions can be utilized or avoided to enhance DNA recovery from specific species or taxa.

[0141] Metadata collection To effectively process or interpret the data generated by this invention, various metadata are preferably collected along with the samples themselves. This allows for comparisons between different samples or provides quality control measures (i.e., proper application of preservation). Metadata may include cross-sectional coordinates, time and date, weather conditions, collection surface, and other relevant variables.

[0142] Most field cleanings are not entirely successful in removing DNA from the surfaces or other parts of the collection device. Therefore, it may be useful to collect data before the device is cleaned and to consider these relevant landmarks when interpreting data obtained from subsequent use of the cleaned device or surface.

[0143] Location coordinates can be collected using various commercially available data loggers or even GPS (or other satellite-based positioning) systems that transmit the location. Additionally, for some types of vehicles (e.g., trains, buses, delivery vehicles, etc.), location data can be captured and maintained remotely, allowing for tracking of the vehicle's location from a remote location, and the associated data (if accessible) can be used to correlate captured biological material with the vehicle's route and schedule.

[0144] Experimental results Trials were conducted in Portugal and the Netherlands using various road-based vehicles (such as public buses, delivery vehicles, and postal vehicles) to perform various proof-of-concept studies that clearly established the significant potential of the technology. These studies included a total of 86 airborne eDNA samples collected from a total of approximately 15,500 km of road-based routes throughout the year. More than 2,630 taxa were detected, including 336 vertebrate species and 1,543 arthropod species, many of which were related IAS or individual individuals. The technology according to aspects of the invention significantly increases the sampling efficiency in the air and its ability to detect IAS and rare / exotic species. The number of species detected using stationary samplers in all published studies is approximately 10-50 times lower than the number of species detected in pilots using mobile route-based sampling performed according to aspects of the invention (comparing the total reported taxa or arthropod and vertebrate species per sample). In some samples, approximately 500 taxa (eukaryotic) were identified per sample using only 3 primers.

[0145] The material collection techniques according to aspects of the invention are 10-50 times superior to current stationary air sampling techniques. Our study highlights that these techniques achieve very high levels of efficiency when analyzed using the exact same metabolic coding methods, identifying 25 to up to 495 taxa per sample, and substantially outperforming conventional stationary air sampling methods in terms of overall species detection. This advancement is even greater when compared to previously reported findings, demonstrating the non-parallel ability to detect novel low-abundance IAS species. Furthermore, the harvesting techniques allow for this wide-ranging detection across various road networks, urban and rural environments, and various vehicle speeds within a total sampling period of only about 60 working days, thus emphasizing the versatility and comprehensive environmental monitoring potential of the technology.

[0146] Species detection achieved in pilot studies, validated by public science, provides insights into the presence and potential proliferation of many previously unreported species. Various data validations comparing pilot study data with public science or other publicly available data confirm these findings and demonstrate that the technology can identify 25-30% of new species previously unreported in these areas. For example, multiple detections of IAS at different pathways / regions, such as Vespavelutina in Portugal and Procyon Lotor, Ondatra Zibethicus, or Myocast Coypus in the Netherlands, and accurate confirmation through events reported in public databases, demonstrate the effectiveness of the technology in mapping IAS distribution and potential hotspots. Furthermore, data from pilot studies also indicate that the overall frequency of bird species detection using methods according to aspects of the invention is highly correlated with known / expected species abundance. This suggests that, if deployed on a large scale, eDNA data obtained using methods according to aspects of the invention can potentially be used to infer relative species abundance across large areas. Such data could revolutionize ecological surveillance, contributing to effective IAS detection and management, and providing nuanced perspectives on biodiversity and species conservation.

[0147] Data from a pilot run in Portugal showed the detection of (extremely) rare and abundant bird species. Furthermore, there was a correlation between the number of detections and abundance. Approximately 70 species were detected in a pilot study in Portugal. These results represent an impressive 17% coverage of all known species, from just 40 samples collected over a limited batch over four weeks along a route covering only about 6% of a broad urban area.

[0148] Preliminary data also indicate that the methods according to aspects of the invention can provide spatial and temporal information for the detection of an average of 500 bacteria and 350 fungi per airborne eDNA sample, as well as plant distribution. Applying the techniques according to aspects of the invention to these taxa clearly has significant potential relevance to agriculture, horticulture, periwinkle, and public health.

[0149] Effective airborne eDNA sampling depends critically on the total volume of air being analyzed. Current airborne eDNA samplers include active samplers that draw in air and capture particles on filters or liquid media, and passive samplers that rely on the natural deposition of particles onto plates or cups. Each sampling system has its advantages and limitations; however, most studies to date have been limited in terms of the volume of air processed due to the physical constraints of using filters or eDNA preservation in passive sampling.

[0150] The methods according to various aspects of the invention utilize standard road vehicles to significantly increase the volume of air sampled for airborne eDNA analysis, thereby significantly improving the monitoring capabilities of IAS. The methods according to various aspects of the invention aim to capture large quantities of airborne eDNA from the vast amounts of air displaced by road-based mobile vehicles / transporters. Essentially, the airflow dynamics around mobile vehicles allow us to use them as mobile airborne eDNA sampling platforms, capable of handling air volumes several orders of magnitude higher than conventional stationary air sampling equipment. This approach not only increases the volume of air sampled but also offers the potential to cover a wider geographical and environmental range.

[0151] Key technological advantages of mobile airborne eDNA sampling: i) Enhanced air volume sampling: The sampling method using road vehicles according to aspects of the invention inherently handles significantly larger volumes of air. For example, 1m of air moving at 50km / h. 2 The area travels through 830m per minute 3 The air. Extrapolating this over an 8-hour / day operating period, this equates to approximately 400,000 m³. 3 The volume of air. This capacity is more than 250 times larger than that of the most powerful stationary sampling equipment.

[0152] ii) Utilizing reduced sampling effort, improved detection capabilities, and greater ecological insights: The sampling methods according to various aspects of the invention increase the possibility of detecting obscure / rare species whose eDNA is present in low concentrations, and sampling can be extended to cover large and diverse ecological landscapes. By combining this with the fact that it also captures a wider range of species, it potentially provides valuable insights into their distribution patterns, migration routes, and ecosystem interactions.

[0153] As mentioned above, while it is possible to actively scan IAS targets, we prefer non-targeted species detection, for example via eDNA metabarcoding, as this offers the advantages of detecting novel AIS as well as providing a broad characterization of biodiversity. To this end, we selected the optimal vehicles and appropriate routes for regional eDNA sampling. For some studies, for example, based on three key criteria, vehicle suitability, route characteristics, and accessibility, we determined that public buses and postal delivery vehicles are the best options for some large-scale monitoring programs. While buses repeatedly cover larger, stable regional routes, delivery vehicles navigate optimized local routes, and both vehicle types tend to return to a central depot or hub (e.g., train station, airport). These specific route aspects not only allow for easier sampling access but also increase the sampling density and resolution around transport hubs, which are key entry points for IAS, thus increasing the chances of success for these projects. Nevertheless, circumstances may require the use of dedicated vehicles to sample specific locations not covered by standard bus routes, trucks, or other delivery vehicles.

[0154] The results of these scans are used to generate species detection probability maps based on the obtained high-coverage eDNA data. Data obtained from a large number of recurring sampling events are converted into grid-based probability maps of a defined size (10x10km). This resolution is based on our current understanding of airborne eDNA transport. The detection probability (0 < p < 1) for each map grid cell is determined based on mathematical calculations comparing multiple routes and sample events. Over time, the maps are recalibrated by integrating data from new sampling events and reducing the influence of older data to generate smooth temporal trends and geographical patterns. By relying on multiple sampling events, these probability maps are more likely to include information from low-abundance species and can be refined using additional spatial data sources such as wind direction and habitat type to enhance accuracy and provide a more detailed understanding of eDNA dispersion patterns.

[0155] Figure 3 is a diagram schematically showing an idealized transport network for collecting biological samples. In this example, the transport network is a bus network. In the example shown, there are four public transport hubs 300, 301, 302, and 303. Here we assume that the hubs are equidistantly spaced and that each hub is connected to every other hub by direct transport routes. Ideally, buses would travel back and forth daily along the same cross-sectional band. Good coverage is achieved by sampling DNA from all routes going to each hub.

[0156] Furthermore, the area surrounding the central hub was sampled at least eight times, allowing for confirmation of the possible presence or inference of the absence of DNA around the hub, thus making it more likely that the DNA originated somewhere along a route farther from the hub. Biodiversity data collected from bus routes and hubs can also be cross-checked via GBIF data overlay, as it preserves information on species occurrence and geographic distribution. Further away from the hub, there are intersecting diagonal routes, providing another data point to confirm the presence or inference of the absence of DNA, making it more likely that the DNA originated from a point farther from that intersection. In this way, diagonal routes between hubs can be subdivided into areas where DNA attribution can be inferred, and horizontal and vertical routes can be subdivided into areas where DNA attribution can be inferred (see gray outline areas).

[0157] Additional cost optimization steps can be achieved by sampling longer routes only in a single hub (i.e., routes through 2 hubs, thick dashed lines). Using the same intersection principle as above, this allows horizontal and vertical routes to be subdivided into 4 zones, and diagonal routes into 6 zones.

[0158] Furthermore, more accurate results or reduced uncertainty can be achieved through multiple sampling (i.e., repeated sampling or sampling over multiple days, weeks, or months covering different seasonal species cycles). Note that DNA presence / absence cannot be resolved for areas outside the gray circles (depicting intersecting routes or hubs) and for areas along a single route, as absence can be sampled to confirm the presence or absence of DNA at intersecting routes. For these regional data, such as wind speed, known species presence and ecosystem maps can be used in conjunction with machine learning algorithms to add more granularity.

[0159] Public transport logistics constraints Based on our interactions with various bus companies, cleaning schedules clearly vary. Some buses and trains operating in Western European countries, as well as countries such as Japan and South Korea, are cleaned daily. This cleaning cannot be expected to remove all collected eDNA from the surface, but it will have a reducing effect on the amount of biological material remaining on the surface. Therefore, understanding and documenting cleaning schedules is helpful, but regular cleaning cannot be relied upon in the context of a clearly defined collection window (i.e., it cannot be assumed that any biological material collected from the surface has arrived within the interval since the last cleaning event).

[0160] Bus companies can also employ different bus route strategies. It has become apparent that some companies keep the same buses on the same cross-strip without transferring any buses to different cross-strips (a cross-strip can be equated with a route, but numbered bus routes can describe different cross-strips on different dates or at different times on different dates, and this must, of course, be taken into account). The same bus company or another bus company can operate the same bus on the same cross-strip for a long period (e.g., days or hours, traveling back and forth along the same cross-strip) – although the same cross-strips running in opposite directions can be given different route identifiers. Such a system is beneficial to our purposes because it provides flexibility regarding the timing of sample collection and potentially simplifies data processing – unlike situations where a given bus could take different possible routes (cross-strips) depending on bus demand and availability.

[0161] Other companies typically redirect buses to new routes based on daily schedules; routes are often changed once a bus arrives at a central hub (i.e., a central train station or other public transport hub). Bus schedules can be viewed a day or several days in advance, and collection (and / or cleaning) strategies can therefore be planned ahead of time. However, in many cases, bus availability-based rerouting occurs in real time at bus stops, junctions, or terminals (e.g., using an available bus to replace a faulty bus from another route), and therefore planning cleaning and collection in advance can be challenging (if not impossible). Typically, the routes individual buses have traveled can be known by accessing a centralized platform or via recorders on the buses. In these cases, a strategy could be to sample buses on selected routes arriving at the central hub while also recording previously traveled routes and using computational processing to account for the fact that biological material may also have been collected during those previous routes.

[0162] It should be understood that in this context, the use of a removable sampling surface (e.g., a glass or metal panel or sheet, or a plastic film or sheet, as described elsewhere) is particularly useful, as it can be installed onto the vehicle just before the journey begins and then removed from it after the journey is complete. This approach is also highly helpful when the vehicle used for material collection is not a public transport vehicle but rather a vehicle that may have less restricted routes, such as a road transport vehicle or delivery vehicle (whose route details can be obtained during or after the event using the vehicle's navigation system or onboard tracker).

[0163] Collection from public buses can generally be safely carried out around most public transport hubs or route terminals, as it typically only takes 2 or 3 minutes to wipe the front of the bus with paint rollers / coating rollers, and similar time should be achievable using structures and other collection devices with one or more removable collection surfaces (and therefore need to be replaced or simply removed at the end of the cross-strip journey or a series of journeys). Buses typically stop at these central hubs and terminals for at least 5 minutes, sometimes longer if the bus driver is changed. Sampling at these public transport hubs is ideal because it allows for daytime collection and greater flexibility in choosing routes and times for sampling. Alternatively, sampling can occur at night depots (where most buses are also cleaned), but here sampling time is limited to one time per day (upon arrival at the night depot, although sometimes buses may return to the night depot at least once during the day and before the end of the day), and there may be no reliable control over cross-strips operated by bus companies using mixed routing strategies. Using dedicated tracking devices to track the actual journeys of individual vehicles is helpful in this regard, especially when combined with vehicle identifiers such as device-readable codes (e.g., barcodes, QR codes, or RFID or NFC data tags) that are affixed to the vehicle in a location easily readable by someone collecting biometric data (e.g., using a smartphone or other handheld device). Of course, the vehicle registration number on the license plate can be used to identify the vehicle, but this may require photographs or some other documentation that may require more manual intervention.

[0164] When biological samples are collected (harvested from a medium), they are preferably identified individually by means of barcodes, for example, by placing (e.g., sealing) them into sterile containers that have been affixed with barcodes. The person performing the collection follows appropriate protocols to ensure that a given collected sample is associated with an identified vehicle, and thus with an identified cross-section or series of cross-sections (whose records will also include the date and time).

[0165] Experimental results A series of trials were conducted over several months using municipal buses in small European coastal towns. Four bus routes were selected, each with distinct characteristics. The first, A, was a purely urban route (approximately 10 km long) that was neither near the sea nor a park. The route was largely linear, with buses turning at each end for return trips. The second route, B, was also an urban route, essentially circular, running along the coast for several hundred meters and also adjacent to parkland at various points. The third and fourth routes were suburban routes. Route C was a linear route that began and ended within the urban area, but approximately half its length (approximately 10 km in total) traversed green spaces. The fourth route, D, was partially urban, but extended approximately two-thirds of its length (approximately 20 km in total) along the sea and extended a considerable distance into an adjacent park. All four bus routes offered daily service, and journeys were typically carried out by vehicles dedicated to the relevant route in each case. These four routes traversed areas with varying levels of natural beauty and habitat composition.

[0166] Biological samples were collected from buses along four routes, typically by wiping the buses with paint rollers soaked in phosphate buffer. Samples were collected on average every four days, with two samples taken from each bus each time, for a total of five harvest events. DNA was extracted and amplified using three primers, yielding a total of 120 DNA samples. The results were filtered to remove arthropod species. Below, we present a table summarizing the DNA samples analyzed for each primer and the number of non-arthropod species detected in each group.

[0167] Nine species overlapped between the two 16S primers, but not with the species identified using COI primers. DNA samples were sequenced using high-throughput sequencing, and the presence of known species was assessed using a computational pipeline by matching the sequencing data with genomics databases. A total of 255 species were observed in at least one biological sample across all DNA samples.

[0168] It is noteworthy that so many marine species were detected in these samples taken from the front of buses that were driven only near the ocean (within approximately 50 meters of bus route D). Interestingly, however, 19 out of 55 fish species (Arcticidae) were detected in samples from at least three of the four bus routes. One of the four identified cartilaginous fish species (wave ray) was classified as “dangerous,” while the others were classified as “near threat.” Furthermore, DNA from two “near threat” species of parrotfish was detected on one of the bus routes.

[0169] Using the same method, 120 DNA samples harvested from the front of the bus were used again with COI and two 16S primers to identify insect species.

[0170] DNA samples were sequenced using high-throughput sequencing, and the presence of known species was assessed using a computational pipeline by matching the sequencing data with genomics databases. A total of 657 species were observed in at least one biological sample across all DNA samples.

[0171] There was 105 overlaps between the two 16S primers, of which 30 were also detected using COI primers. Seven additional species were detected using both 16S gene targets for mammals and COI primers. Another 28 species were identified using both 16S gene targets for insects and COI primers. 277 species were identified using only the 16S gene target for insects, 228 species using only COI primers, and 12 other species using only the 16S gene target for mammals. Therefore, it is prudent to use multiple primers to increase the number of species identified. If monitoring plants rather than animals, then appropriate primers, such as ITS2, should certainly be used.

[0172] DNA extraction and amplification Total DNA was extracted from samples collected from the front of the bus according to an internally optimized procedure designed to maximize insect DNA recovery. DNA samples underwent quality control prior to PCR amplification and library preparation. All samples meeting established quality control thresholds were further processed.

[0173] Two molecular markers representing the insect population were analyzed for each sample. A single Illumina sequencing library was prepared for each DNA sample and marker using an internally optimized protocol.

[0174] Laboratory controls (negative, molecularly pure water) and positive, pure insect DNA) were added to the analysis and processed in parallel with the DNA samples. All laboratory controls produced the expected results. All sequencing libraries underwent multiple quality control steps at each stage of processing and were then sequenced.

[0175] DNA sequencing The library was sequenced on Illumina MiSeq in paired-end 300 mode, yielding 2 x 13,015,461 reads.

[0176] Sequencing performance was within platform specifications. Only high-quality sequencing reads were used for bioinformatics analysis.

[0177] Metacode Analysis Sequencing reads were analyzed using a custom metacode analysis pipeline based on the qiime2 platform. In short, quality control of the raw sequencing data was performed to verify sequencing accuracy. Reads without amplification primer sequences were discarded. The remaining reads were used to construct a representative set of sequences (ASVs) and filtered to discard amplicons of unexpected lengths, resulting in 6847, 3886, and 2791 sequences for insect 16S gene targets, mammalian COIs, and 16S gene targets, respectively. A set of classifiers was then trained to assign these sequences to taxa, resulting in a total of 2132 high-confidence taxa. Graph and additional analyses were performed using custom R and Python scripts.

[0178] Quality control All results are evaluated and categorized based on internally established quality control thresholds, and only calls to species with high confidence are reported.

[0179] The positive control was validated by identifying the insect species used in the analysis. No species were detected in the negative control sample.

[0180] database The following database was accessed during the analysis: MIDORI version GB245.

[0181] Spatial and temporal resolution Our method will enable the sampling of eDNA within long cross-sections and at different time points, and the conversion of this data into detected species. To further refine the spatial and temporal resolution of the detection, we use data analysis and combine different cross-sections. The following paragraphs describe one possible approach.

[0182] When collecting eDNA across transects and over a period of time, the location and timing of moving the collection surface can be used to map the potential regions from which the eDNA originated (potential occurrence maps) and associated probability scores. Other data, such as weather conditions, time of day, movement speed (and changes), collection surface type, and landscape features, will also be integrated to increase temporal and spatial resolution or reduce uncertainty in the occurrence data. Furthermore, data from other transects or collected during another time period can be used to refine the potential occurrence map by combining probabilities originating from each transect. Finally, data from other sources (manual surveys, event databases, etc.) can be integrated to further refine the potential occurrence map. Potential occurrence maps can be linked to specific time periods or points in time that allow for capturing temporal resolution. Inference of potential occurrence maps can include machine learning techniques or rule-based heuristics. The final result will be a geographic and temporal indexed dataset describing the detection probabilities of specific taxa.

[0183] Potential methods would involve machine learning classification algorithms such as neural networks or random forests. A model would be created for each species. The input to these models would be the metadata associated with the samples (location, time of day, landscape features, data from other databases associated with the same location, etc.), and the training target would be whether we detected the species of the model in our samples. After training, the output of the model would be the confidence in the probability that the species could be detected at that time and location. By using a properly trained classifier, we could extend this to allow us to predict species presence even without sampling, provided the metadata is present. For example, we could train classifiers that link the eDNA we have detected to various other (spatial, etc.) data (i.e., forest cover, temperature, presence of other species), and in this way allow us to predict the likelihood of detecting eDNA in unsampled areas where such other data is present.

[0184] Another method could be based on collecting the known routes of vehicles. The unit detection of species across the transect would be divided into a uniform probability distribution along the length of the transect. Finally, information from several transects would be combined by adding the probabilities of presence on intersecting routes. This method could be done for all samples, or by subsetting on variables such as date, time, or meteorological conditions.

[0185] Figure 4 Possible methods of generating and using probability maps are shown. To generate a probability map that reflects the probability of eDNA collection sites within the transect survey area, the survey area is divided into grid cells of a defined size (based on the required resolution, the overall size of the survey area, and the transect density within the area). For example, if we consider the whole of the Netherlands, we could achieve a resolution of 10 km × 10 km using approximately 360 bus routes strategically selected across the country; if we also add some other collection types (such as vans), a resolution of 5 km × 5 km could be achieved. For urban areas with a reasonable bus route density (or a reasonable density of some other public transport routes), we could realistically expect to achieve a resolution as low as 2 km by 2 km or even 1 km by 1 km. The collection probability (0 < p < 1) is determined for each grid cell based on mathematical calculations and comparison of various routes and sample events.

[0186] Figure 4The diagram shows a survey area or region comprising three vehicle routes (A1, A2 & A3) (here the area is shown as a rectangle of 6 units by 12 units), which could be, for example, public transport routes (e.g., bus routes). For the purposes of discussion, we assume that each of these routes is sampled weekly, with sampling events for all three routes occurring on the same day, although these conditions / restrictions are clearly not necessary. For example, routes could be sampled daily or every few days, and different routes could be sampled at different frequencies and at different times.

[0187] Routes A1 and A3 overlap from cell (4,1) to cell (7,1); route A1 intersects with route A2 in cell (7,2); and route A2 overlaps with route A3 from cell (4,2) to cell (4,4).

[0188] On route A1, species S1 is identified at T0 (first sampling event). This means that a crossband defined by the route eDNA of species S1 has been collected somewhere (assuming the sampling surface is completely clean at the start of the sampling period). The crossband for route A1 traverses a certain number of grid cells (g A1 In this case, the probability is 17. Without knowing more, we must assume that the probability of collecting along the cross-sections of the route is equal. Therefore, for each grid cell through which route A1 extends, the "probability of collection" p S1,A1 =1 / g A1 Therefore, this equals (1 / 17 = 0.059). The algorithm then continues merging the next route A2, whose crossband traverses 14 cells. Species S1 is also identified on this route, and therefore the probability for each grid cell is p. S1 , A2 = 1 / g A2 (1 / 14 = 0.071). No species S1 was detected on route A3, therefore for all grid cells through which the transverse zone of this route extends, p S1 , A3 = f. Here, f is a factor adjusted to reflect the probability of a false negative. In this example, we assume p S1 , A3 = 0.

[0189] In cells where the route did not pass through, a moving average (by the average route length) is applied using the probability of all routes sampled. This moving average is applied to each “probability of collection” grid linked to each route. It is based on other “probability of collection” grid cells that the route did pass through. The moving average algorithm can also be another exploratory algorithm, such as Kriging (Gaussian process regression) or multipoint statistics, and / or guided by secondary data (e.g., vegetation cover, land use maps, wind speed, other species occurrence databases). In our example, we use an average for all cells farther from the route than one grid cell, and for all cells within one grid cell distance, the “neighbor” average is the average of all such neighboring cells (cells near the route). To do this, we first calculate the base probability of cells far from (all) routes based on the average probability of routes in the (total) survey area. For this example, this would be p S1,A1 = (p S1,A1 + p S1 , A2 + p S1 , A3 ) / 3 = (0.059 + 0.071 + 0) / 3 = 0.043. For larger-scale areas where some routes are shorter than the total survey area, a moving average will be applied.

[0190] For each grid cell, species S1(p S1 The cumulative / modeling probability of the collected data is p. S1,A1 xp S1 , A2 xp S1 , A3 This means that in our example, the collection probability of species S1 not being detected on route A3, where other routes (A1 & A2) intersect with that route, is also set to 0. If two or more routes for a given substance are detected intersecting in a unit, the collection probability for that substance in that unit is increased (e.g., for species S1 in unit 7,2, where routes A1 and A2 intersect, as shown in the figure).

[0191] For example, grid cell (7,2) will have a probability of 0.059 × 0.071 × 0.043 = 0.00018. In grid cells (4,1); (5,1); (6,1) & (7,1), this would be 0.059 × 0.071 × 0 = 0 (again assuming no false negative probability; f = 0). In other non-intersecting grid cells along route A1, for route A2 with a probability of 0.043 × 0.071 × 0.043 = 0.00014, the probability is 0.059 × 0.043 × 0.043 = 0.00011. For all other cells (outside of the route), the probability is initially 0.043 × 0.043 × 0.043 = 0.00008. Next, for those grid cells that are close to the route but not part of it, we calculate the average probability of their surrounding 3×3 squares (in this case) to reflect the additional information we have about the surrounding area. We can then apply smoothing based on a larger scale (e.g., based on the use of 9x9 squares or larger). Figure 4 The gradation of the units in the data reflects these values.

[0192] Since the collected cumulative / modeled probability plots are not a true reflection of the probability associated with the presence of a species, their values ​​can be scaled or normalized. Furthermore, at subsequent sampling times (T1, T2, etc.), the probabilities of grid cells can be recalculated and added to the previous probability plots. Data from many time steps can be used retrospectively with smaller weights to generate smooth time trends and plots. Alternatively, data from previous time steps can be used as guidance for moving averages or Kriging algorithms.

[0193] Example: Our test using buses in two Dutch provinces (A and B) illustrates an example of this concept. Here, we detected the common field mouse (Oriental field mouse) from all four sampled bus routes in province A. In province B, we detected it only from one of the three routes we sampled, and very consistently from that single route (five consecutive buses traveling the same route). No Oriental field mouse was detected on the other two routes. This corresponds well to known events (via citizen science reporting) at high resolution (5x5km grid cells), as Oriental field mice were reported in and around the city where we sampled buses in province A. In province B, more patterns were observed, and Oriental field mice were not reported in grid cells of the two cross-sectional areas where no common gaps were detected, nor near the central hubs we sampled. Instead, Oriental field mice were primarily reported at the ends of the specific routes where we found consistency.

[0194] Furthermore, the "bank vole" (Earth dam mole) was not found in the buses sampled in province A, but was detected in 4 out of 7 buses sampled in province B, which closely corresponds to the known occurrence of the bank vole, which has been almost never reported in province A.

[0195] In most urban areas, local public transport networks already provide a good foundation for sampling. We have sampled four bus routes in a municipality covering approximately 100 km², representing less than 10% of the total number of routes in the area. The full set covers a larger area and includes many intersecting routes as well as routes with overlapping sections having multiple common stops.

[0196] Data delivery and presentation For some end users, the delivery and presentation of this rich data may require specialized data platforms, websites, software, or dashboards (interactive graphical platforms for data exploration). In such software applications, species information derived from "bioinformatics processing" and / or "spatial and temporal resolution resolution" computational steps is integrated and presented as graphs, maps, measures, lists, and interactive menus. These data presentations may include summary measures and indexes focusing on ecological aspects of the client's interest, including but not limited to: • Life stage assessment – ​​for example, determining whether the detected species is in the larval or adult stage; • Functional / metabolic potential – By detecting bacterial taxa and / or their gene coding sequences, we will be able to determine what metabolic processes the bacterial communities present in our samples can perform; • Ecosystem services – Ecologists have allocated services to a wide range of species. These can range from biological (e.g., pollination) to environmental (soil degradation) to cultural (culturally important species, such as butterflies); • Functional network mapping – using existing databases such as GloBI (Global Biotic Interactions) to identify biological interactions (predator-prey, parasite, symbiosis) between species detected at the same location; • Pollination capacity – detected arthropod species by identifying plant species known to pollinate plant species known to be present in a particular location; • Soil health – identified by examining the bacterial and fungal species detected that are known in the literature to represent healthy and unhealthy agricultural soils; • Monitoring of threatened and invasive species – by identifying those species among those detected that are present in databases of threatened and invasive species, such as those of the IUCN; • General biodiversity and population trends.

[0197] Adding another layer of outsourced information (i.e., remote sensing, satellite data, artificial intelligence, and ecological modeling) to DNA-based observations will allow for the detection of ecological changes in multiple systems and the creation of predictive models.

[0198] Figure 5 This is a flowchart illustrating a method 500 according to one aspect of the present invention. As a first step 502, a geographical survey area is identified. For example, this may be the result of a request from a client (individual, enterprise, local, regional or national government organization, international organization, semi-official agency, etc.), or it may be the result of an expectation to determine certain aspects of the biological or ecological presence within the survey area.

[0199] In this example of the method, it is decided to utilize existing public transport routes as a means of collecting material samples. Therefore, at step 504, one or more existing public transport routes are identified (e.g., selected) for initial sample acquisition. At step 506, cross-sectional surveys of the survey area are conducted using the selected public transport routes, or each selected public transport route (which may be, for example, only a single type of transport (e.g., bus, tram, or train), or a mixture of different transport types, such as bus and tram, or bus and train, or bus, tram, and train). As previously stated, collection can be carried out over a day or several hours within a 24-hour period, or over several days, or even longer. For each route, a single vehicle or multiple vehicles may be used, depending on the terrain and logistics.

[0200] After a predetermined collection period (which may vary for some or more routes, or may be standardized for different routes), the collected biological material from each route is harvested in step 508.

[0201] After harvesting, molecular analysis is performed in step 510 as described above.

[0202] The process can continue based on the identification / selection of other existing public transport routes. Alternatively, other public transport routes can be selected based on the results of molecular analysis (e.g., based on other public transport routes that intersect with the initially selected route). It should be understood that... Figure 5 The method shown can also be well utilized with road transport vehicles, or some combination of public transport vehicles and road transport vehicles, operating on known (or captureable) road transport routes through the survey area. Similarly, privately chartered vehicles (such as school buses and / or tour buses) and / or public transport vehicles can be used, and references to public transport vehicles should be considered to include such vehicles unless the context explicitly requires otherwise. In some cases, it may be desirable to use only public transport vehicles and not private vehicles.

[0203] Figure 6 It shows what is usually corresponding to Figure 5Method 500, or Method 600, includes initial survey area identification 602, identification of existing public transport routes 604, collection of biological material at 606, collection at 608, and molecular analysis at step 610. However, in this case, the results of the molecular analysis at step 610 are used as the basis for selecting 612 one or more additional public transport routes intersecting with previously used routes within the survey area. The collection, harvesting, and analysis steps 606-610 are then repeated. Further iterations of step 612 may exist to obtain a more complete picture of biological presence within the survey area, and optionally extend beyond the initial survey area. At step 616, a probability map of the identified species and / or taxa can then be generated, at least in part, based on the results of the molecular analysis performed at step 610.

[0204] 1.1 Example 1 - Ecological Measurement 1.1.1 For example - Biodiversity reporting requirements Commercial entities may be required to provide measures of biodiversity impacts relating to their assets. This relates to regulatory reporting requirements in various countries, including the EU. Such companies will be required to list biodiversity measures within and around the site, and more specifically, the presence of endangered species. The methods of biological collection and the provision of biodiversity measures described in this patent application can be applied by collecting biological material from vehicles / vehicles that cross the perimeter of the site but beyond it, as well as from vehicles / vehicles that cross the perimeter of the site itself. Depending on the size and geography of the site, this may require the use of drones or other aircraft. Public transport can be used to conduct at least some external (beyond the perimeter of the site) cross-stripping. In practice, eDNA results determined based on material collected during “routine” surveys using, for example, public transport vehicles can serve as the basis for off-site biodiversity measures. Commercial entities with large sites and / or those with a reasonable concern for local biodiversity may choose to work with local public transport services (and / or other operators of vehicles traversing the relevant area) to conduct routine and periodic (e.g., at least monthly) monitoring based on biological samples collected by vehicles. A data platform based on data collected using technology according to one aspect of the present invention can also provide this information via "data as a service".

[0205] A greater burden of commercial (corporate) responsibility for the impacts on biodiversity implies the need for readily available markets for reliable data on biodiversity, such as those obtained using methods according to one aspect of the invention. A reliable database of the “status” of biodiversity can be established through sufficiently frequent, geographically broad, and comprehensive reviews of biodiversity based on methods according to aspects of the invention—customized, if necessary, for locally endangered or rare species. Such a database can provide the basis for site-specific biodiversity reports that can be “topped up” through field surveys using vehicle-based bioharvesting techniques according to aspects of the invention.

[0206] Such databases may be particularly valuable in areas that include industrial plants and sites, and are of great interest to local or regional county / government authorities.

[0207] 1.1.2 Example - Environmental Impact Assessment Environmental assessments are essential for the construction of large-scale infrastructure projects. Economic consultants typically conduct desktop screenings before visiting the site. Desktop screenings can be based on a database established using biological samples collected according to a method based on one aspect of the invention, as just described.

[0208] 1.1.3 Example - Environmental Monitoring of Government Policies For regional policies, such as restrictions on pesticides, reduction of nitrogen loss from agricultural land, and limitations on the use or emission of toxic substances, it may be necessary to monitor ecological impacts to demonstrate positive effects on various stakeholders (e.g., in increasing biodiversity or protecting endangered species). Data platforms of the aforementioned types can also serve as a useful basis for comparative examination of such biodiversity and biodiversity trends.

[0209] 1.1.4 Example - Regional Biodiversity Trend Data Various countries are required to report national or regional biodiversity trends, either as part of international agreements or due to their own laws and obligations. The collection of trend data on a large number of species, sampled in a consistent manner, facilitated by this invention, can provide this information to governments, and potentially support NGOs and international organizations in their monitoring roles.

[0210] 1.1.5 For example, scientific research data Scientific ecological research typically relies on other reports or (public) data sources to i) design studies or surveys and ii) draw final conclusions. By making biodiversity data obtained using methods based on various aspects of this invention available to researchers, NGOs, scientific institutions, or other nonprofit organizations, they can gain a stronger understanding of ecological networks, derive empirical relationships, advance science, and better understand biodiversity change and impacts.

[0211] 1.2 Example 2 - Invasive, Alien, Harmful & Illegal Species 1.2.1 Example - Invasive Species Monitoring for Government Invasive species are a key threat to biodiversity, and therefore many governments have appropriate strategies to monitor, locate, control, or eradicate them. As new information becomes available and known invasive species continue to spread to new areas, the list of such species is constantly evolving. By using the vehicle-based harvesting techniques described in the context of this invention, it is possible to perform virtually routine, large-scale (geographically widespread and frequent) surveillance of such species, providing a basis for identifying trends and discovering new events at a relatively low cost. Furthermore, in the case of adding a new species to the list of invasive species, biological material previously harvested using methods according to aspects of the invention can be re-examined to check for the presence of the new species.

[0212] 1.2.2 Example - Crop Green Spot Trend Detection for Farmers Numerous known plant pests exist in and around farmland. Currently, these pests are typically eradicated through preventative pesticide use, which harms other species and may be unnecessary or applied at high doses due to a lack of detailed information about the threat. In various countries, pesticide use is being reduced through regulations because it is highly detrimental to biodiversity and human health. Utilizing spatial and temporal data on the presence of pests (primarily invertebrates, but sometimes vertebrates) and plagues (often microorganisms) provided by methods according to aspects of the invention, farmers can better develop pesticide strategies (i.e., integrated pest management; IPM) and tailor their use to allow for minimal damage while ensuring food safety.

[0213] 1.2.3 For example - government-mandated quarantine of species. In addition to common pests, there are various species listed as quarantine species. These species are not prevalent in a region, and if introduced, they can severely damage crops. For this reason, governments maintain a list of quarantine species to be inspected upon importation (phytosanitary control), or have regulations regarding the quarantine period for plant-based materials. Regardless of these inspections, quarantine species still enter new areas and are difficult to eradicate without inspection. Aspects of the present invention provide an effective and low-cost technique to support an early monitoring network that will allow for more rapid action, potentially reducing the risk of significant financial damage to the agricultural sector.

[0214] 1.2.4 Example - Monitoring of destructive insects or fungi by an insurance company In various countries, insects such as termites, caterpillars, and / or fungi (e.g., dry rot and mold) can cause serious damage to buildings or lead to health problems for residents. Here, management and eradication procedures are often in place, and areas with high risk are known. However, new areas may be affected as species spread through globalization and climate change. Here, structural damage can be severe due to a lack of eradication and management methods (i.e., certain timber preservation techniques, ventilation measures, or frequent inspections). For property owners or insurers seeking to manage the risks arising from such damage, aspects of this invention can be used to provide spatial and temporal data on these pests, allowing for rapid management and thus reducing damage and loss.

[0215] 1.2.5 Example - Detecting illegal pets or illegal spending by institutions In many countries, the trade, possession, or consumption of protected or endangered species is illegal. The collection techniques of the various aspects of the invention described in the context of eDNA can also be applied to the regulation of applicable laws. As mentioned in the context of experiments using biological material collected along four bus routes, the detection of DNA from two closely spaced threatened butterfly species demonstrates the applicability of the basic idea. By applying the methods according to various aspects of the invention to frequently conducted cross-sectional surveys, it should be possible to narrow down the investigation area to reveal the location of illegal activities.

[0216] 1.2.6 Example - Animal Disease (Vector, Virus, Bacterium, Fungus) Surveillance The spread of viral, bacterial, or fungal diseases has increased, partly due to intensive animal farming. In some cases, the spread is clearly airborne; in others, it occurs through direct contact or via vectors, primarily insects, but also other species. Methods according to various aspects of the invention can be used to support regional surveillance covering insects, bacteria, fungi, and viruses, enabling the identification of hotspots and spread patterns. This can help animal welfare and health authorities and farmers better manage this risk and control further spread.

[0217] 1.3 Example 3 - Health Monitoring 1.3.1 Example - Human Disease Vector Surveillance for Health Authorities The primary examples of human disease vectors are mosquitoes that transmit malaria and dengue fever. Tiger mosquitoes are of particular concern in northern countries because the vector appears to be spreading, partly due to climate change. In some countries, eradication and control measures are appropriate, but in practice these need to be focused, and current focus relies on public sightings or other local surveys, severely limiting detection opportunities. Methods according to aspects of the invention can provide improved alternatives to current sighting and survey techniques, thus offering greater containment and potential eradication opportunities. Applying methods according to aspects of the invention to regional monitoring of insects covering the area can identify hotspots and spread patterns of this human / animal disease vector, allowing for more focused investigation and eradication.

[0218] 1.3.2 Example - Viral Epidemiology by Health Authorities The recent COVID-19 pandemic has highlighted the importance of early detection of viral outbreaks. During COVID, many governments adopted wastewater monitoring systems before detecting numerous clinical cases. It is also potential to deploy broader regional surveillance methods by using the methods outlined in this patent to monitor the presence of airborne viruses. For some viruses, this method could even provide early measures of infection rates, prevalence, and / or infection risk with greater spatial coverage. Employing non-targeted detection and screening for viruses not yet present in the area could also provide a very early detection method, potentially allowing for mitigation of further spread. WHO, governments, and health authorities could significantly benefit from such data. A potential constraint here is the viability of viruses and viral particles in the air and once they adhere to an impact surface. Depending on the nature of the impact surface, UV light levels, and temperature, there may only be a relatively short window within which samples can be harvested and processed to reveal the presence of the virus. However, if these factors are taken into account and sampling and processing are performed rapidly, the techniques described in this patent application can be used to monitor the presence of the virus.

[0219] 1.3.3 Example - Pathogen outbreak for insurance companies It is known that certain diseases have a higher incidence in certain areas or regions of a city. In some cases, this is due to demographic causation, but it could also be due to other environmental factors or the presence of pathogens. One of the earliest examples is the analysis conducted by John Snow in 1854, which revealed a cholera outbreak linked to a specific water pump. More recently, Legionella has been linked to public fountains, but only after deducting all locations typically visited by sick people. With the methods outlined in this patent, health authorities can take more focused action to prevent new outbreaks or more easily understand and identify the source of clinical cases.

Claims

1. A method for generating information about the biology within a survey area, the method comprising: i) Harvesting biomaterial from an exposed impact surface that has been carried through the survey area by a land vehicle, the surface being exposed to air displaced by the movement of the vehicle through the survey area, the biomaterial being deposited from the displaced air; ii) Perform molecular analysis on the biomaterial to generate data about the source of the biomaterial, wherein the impact surface is substantially free of pores and other microstructures.

2. The method of claim 1, wherein the harvesting involves wiping the impact surface to transfer biological material from the impact surface to an article of articles used for wiping the impact surface, wherein optionally a paint roller is used for the wiping.

3. The method of claim 1, wherein the harvesting involves washing the impact surface to transfer biological material from the surface to a liquid used for washing the surface.

4. The method according to any one of the preceding claims, wherein the impact surface is provided by a body component of the vehicle, and optionally, the impact surface is selected from one or more of a glass surface, a plastic surface, a metal surface, and a painted surface.

5. The method according to any one of claims 1 to 3, wherein the impact surface is part of a collection element carried on the exterior of the vehicle.

6. The method of claim 5, wherein the collecting element is a flexible film or sheet, and optionally wherein the flexible film or sheet is adhered to the outer surface of the vehicle.

7. The method of claim 5, wherein the collecting element comprises a glass or metal panel.

8. The method according to any one of the preceding claims further includes collecting biological material on the exposed impact surface of a land vehicle moving across one or more first transverse zones of the survey area.

9. The method according to any one of the preceding claims further includes creating a database based on the results of the molecular analysis performed in step ii).

10. The method of claim 9, further comprising populating the database with biological presence data from multiple iterations of the method.

11. The method of claim 10, further comprising populating the database with biological presence data derived from iterations of methods performed for different geographic regions.

12. The method according to any one of claims 8 to 11, wherein, The geographic area is a building, commercial, or industrial site, and the method further includes collecting biological material on the exposed impact surface of a vehicle that moves over one or more geographic areas beyond the perimeter of the site, and performing the harvesting and molecular analysis steps on the biological material thus collected.

13. The method according to any one of claims 8 to 11, further comprising the step of: iii) Perform one or more additional captures of biological material on one or more second transverse bands passing through the survey area, each of the one or more second transverse bands intersecting one or more first transverse bands; iv) Harvesting the collected biomaterial from the impact surface; v) Perform molecular analysis on the harvested biological material to generate data about the source of the biological material; vi) Generate a probability map of the identified species and / or taxa based at least in part on the results of the molecular analyses performed in steps iv) and vi).

14. The method of claim 13, wherein at least one of the one or more second transverse bands is selected based at least in part on the results of the analysis performed in step iii).

15. The method according to any one of the preceding claims, further comprising monitoring the survey area for the presence of a marker of DNA, RNA, or protein based on the presence or function of an indicator of a biological target, the method comprising performing molecular analysis on the harvested biological material to generate data indicating the presence or absence or function of the biological target.

16. The method according to claim 15, characterized in that, The biological targets are rare, threatening, or dangerous species.

17. The method according to claim 15, characterized in that, The biological target is an invasive alien species, or a species targeted for control or eradication, and optionally, the biological target is termites, wood beetles, or fungi such as dry rot.

18. The method according to any one of the preceding claims, wherein the vehicle is a public transport vehicle or a delivery vehicle, the public transport vehicle being such as a bus, tram, or train, and the delivery vehicle being such as a motorhome, truck, or van.

19. The method according to any one of the preceding claims, wherein the method is performed using more than one type of vehicle, and optionally wherein the method is performed using both a ground collection vehicle and an air collection aircraft.

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