Urban green land plant dynamic screening method based on multi-dimensional function balance

Abstract

The invention belongs to the technical field of urban ecological planning, and relates to a dynamic screening method for urban green land plants based on multi-dimensional function trade.According to the dynamic screening method, by quantifying ecological functions, social demands and stress resistance, combining an AHP-entropy weight method, dynamically adjusting the weight according to the field type and combining a nitrogen-fixing microbial inoculum and a microelement fertilizer, the phyllospheric nitrogen fixation rate is increased; compared with a traditional method, the method has the advantages that PM2.5 in the green land is remarkably reduced, the landscape satisfaction degree in winter is improved, the problem of'flying snow in spring 'is radically solved through application of varieties such as the flying-wadding-free salix matsudana and the like, and a universal solution is provided for the high-heterogeneous urban environment.

Description

Technical Field

[0001] The present invention belongs to the technical field of urban ecological planning and relates to a dynamic screening method for urban green space plants based on multi-dimensional functional trade-offs. Background Art

[0002] As the core carrier of the urban ecosystem, urban green space plants play multiple irreplaceable roles. Green space plants significantly alleviate the urban heat island effect through transpiration and canopy shading, while also fixing carbon and releasing oxygen. Root systems can filter rainwater, reduce surface runoff, and saline-alkali-tolerant plants (such as Tamarix) collaborate with symbiotic microorganisms to repair contaminated soil. In addition, green space plants effectively support social service functions. Diversified seasonal landscapes (such as forsythia spring flowers and ginkgo autumn leaves) improve residents' mental health and provide habitats for urban organisms. Optimizing vegetation configuration can reduce maintenance costs and enhance urban climate resilience. Green space plant screening technology is directly related to the ecological benefits, social service functions and sustainability of green spaces. Plant screening must adhere to the three basic principles of ecological adaptability, functional orientation and landscape aesthetics to cope with the complex environmental challenges brought about by the urbanization process. In modern cities, plant growth faces multiple stress environments, including soil pollution, urban heat island effect, traffic noise, human interference, etc. The traditional ornamental-oriented screening model can no longer meet the needs of contemporary cities. Current plant screening research is multidisciplinary, integrating knowledge from diverse fields such as ecology, landscape design, environmental psychology, and plant physiology. Through scientific screening, it aims to enhance the comprehensive service functions of green spaces, including improving air quality, regulating microclimate, promoting resident mental health, and protecting biodiversity. Traditional screening relies on a single environmental adaptability indicator (such as salt tolerance), neglecting the synergy between ecological functions (cooling, nitrogen fixation) and social needs (landscape aesthetics). Therefore, it is imperative to construct a three-tiered screening technology system: "functional quantification - dynamic weighting - modular configuration." Summary of the Invention

[0003] In order to solve the above problems, the present invention provides a method for dynamic screening of urban green space plants based on multi-dimensional functional trade-offs, which specifically includes the following steps: Step 1: Quantification of ecological functions: Measure the net photosynthetic rate per unit leaf area, and calculate the cooling index according to the formula: cooling index = 0.38 × photosynthetic rate + 4.2; Collect plant leaves, measure the ANF rate of diazotrophic bacteria in the leaf space and the Fe / Mo content in the leaves, and calculate the synergistic coefficient according to the formula: ANF × (0.8 × [Fe] + 0.1 × [Mo]); Measure the PM per unit leaf area. 2.5 The adsorption capacity is the dust retention capacity; Ecological index = (cooling index / 15) + (ANF efficiency coefficient / 2) + (dust retention capacity / 10).

[0004] Preferably, the net photosynthetic rate per unit leaf area is measured by a photosynthetic meter.

[0005] Preferably, the ANF rate of phyllospheric nitrogen-fixing bacteria is determined by the acetylene reduction method.

[0006] Preferably, the Fe / Mo content in the leaves is detected by ICP-MS.

[0007] Preferably, PM per unit leaf area is measured by elution weighing method. 2.5 Adsorption amount.

[0008] Step 2: Quantify social demand: Assess the ornamental value of the plant, combining the length of the flowering period and color saturation to obtain a visual index; and obtain participation by recording the frequency of public platform voting and the adoption rate of improvement suggestions; Social index = visual index × 0.6 + participation × 0.4;.

[0009] Preferably, evaluate the ornamental value: a panel of five landscape designers and five horticultural experts will independently rate the plants using a structured scoring table. The scoring table includes the following dimensions (each with a maximum score of 10).

[0010] Preferably, the length of the flowering period is: the number of days of the flowering period is divided by 365 (or 366) to obtain the proportion of the flowering period of the plant to the whole year.

[0011] Preferably, color saturation: The C*ab value range output by the colorimeter is usually large (e.g., 0-100+). To unify the dimensions, the measured CS value is divided by an empirical maximum value (e.g., 100) to make it range between 0-1.

[0012] Preferably, the visual index is obtained by weighted summing the above three standardized indices (ornamental value, standardized flowering period, and standardized color saturation) to obtain a final visual index.

[0013] Preferably, participation is calculated by recording the amount of participation that the plant (or green space project containing the plant) obtains on the designated city’s official park management platform or community APP: Votes (V): Number of public likes / votes (e.g. monthly / annual).

[0014] Suggestions_Adopted (SA): The number of times suggestions for improvements made by the public regarding the configuration, maintenance, etc. of this plant were adopted.

[0015] Suggestions_Total (ST): The total number of improvement suggestions made by the public regarding the configuration, maintenance, etc. of this plant.

[0016] Calculation formula: Engagement = (V / V Max Region )×0.6+(SA / ST)×0.4.

[0017] Where: V Max Region It is the highest number of votes obtained among all plants / projects in the region during the same period, and SA / ST is the rate of adoption of recommendations.

[0018] Step 3: Quantification of stress resistance: In the gradient salinity hydroponic experiment, the salt tolerance score was calculated with a relative biomass decline rate of ≤20% as the threshold; the electrolyte leakage rate was measured, and the freezing resistance score was assessed based on the leakage rate range; Stress resistance index = (salt tolerance score + frost resistance score) / 2.

[0019] Preferably, the gradient salinity hydroponic experiment is to select healthy and uniformly growing one-year-old seedlings, wash the roots and transplant them into a hydroponic device (volume 2L, shading treatment); Nutrient solution preparation: Hoagland's nutrient solution was used as the base, and NaCl was added to set the salt gradient: 0 (control), 50, 100, 150, and 200 mmol / L, for a total of 5 groups; Culture conditions: temperature 25±2℃, photoperiod 12h / 12h (light intensity 200 μmol·m -2 ·s -1 ), the nutrient solution was replaced every 48 h, and the treatment was continued for 14 days; Measurement indicators: At the end of the experiment, the aboveground dry weight of each group of plants was measured (dried at 80°C to constant weight); Relative biomass decline rate (%) = [(control dry weight - treatment dry weight) / control dry weight] × 100%.

[0020] Calculate the salt tolerance score: if the decrease rate is ≤10%, it is 1.0; if it is 10-20%, it is 0.8; if it is >20%, it is 0.

[0021] Preferably, according to the electrolyte leakage rate (%) after low temperature stress (-20℃ treatment for 6h), the freezing resistance scoring standard is 1.0 (strong freezing resistance) when the electrolyte leakage rate is ≤20%, FS=0.7 (medium) when it is 20%-40%, and FS=0.3 (weak) when it is >40%.

[0022] Step 4: Comprehensive score = 0.4 × ecological index + 0.3 × social index + 0.3 × stress resistance index. This comprehensive score is used to prioritize plant species and assign community roles: the highest-scoring species (top 20%) are selected as core species, the next highest-scoring species (with outstanding specific functions) are selected as functional species, and the remaining species are dynamically adjusted based on social needs. Specific weights are dynamically optimized using the AHP-entropy weight model in Step 5.

[0023] Step five: Use the AHP-entropy weight method dual-weight model to automatically adjust the indicator weights according to site attributes, with stress resistance weighting 20%-40%, ecological function weighting 30%-40%, and social demand weighting 20%-50%. In addition, input climate forecast data to dynamically increase the weights of drought / waterlogging resistance traits.

[0024] Preferably, for industrial areas: the weight of stress resistance is 40%, the weight of ecological function is 40%, and the weight of social demand is 20%; for residential areas: the weight of social demand is 50%, the weight of ecological function is 30%, and the weight of stress resistance is 20%.

[0025] Preferably, the drought index (number of consecutive rainless days × average temperature) and flood index (number of heavy rain days × soil saturation rate) in the climate forecast data are extracted. Standardized calculations: Drought threat degree (DT) = (drought index - regional minimum) / (regional maximum - regional minimum) Flood threat (FT) = (flood index - regional minimum) / (regional maximum - regional minimum) Increase in drought resistance weight: ΔWd=0.3×ln(1+10×DT).

[0026] Among them, DT should be an indicator to measure the "degree of drought" (such as drought duration, soil moisture deficiency, etc.). The formula can be used to convert the degree of drought into the increase in weight.

[0027] Increase in waterlogging resistance weight: ΔWf=0.3×ln(1+10×FT).

[0028] Among them, FT should be an indicator to measure the "degree of waterlogging" (such as water depth, flooding time, etc.). Similarly, the degree of waterlogging can be converted into the increase in weight.

[0029] Adjusted stress resistance weight = basic weight × (1 + ΔWd + ΔWf).

[0030] Step 6: Select species with an ecological index ≥ 0.7 (out of 1.0) and a lifespan > 10 years as core species, which will undertake basic ecological stability functions and occupy 60% of the community area.

[0031] High-quantitative indicator species are configured according to the dominant ecological needs. Functional species are required to have specific functions (such as cooling / nitrogen fixation) that reach the top 30% of the index value to ensure the efficient realization of the dominant ecological functions. As functional species, they occupy 30% of the community area and are allowed to be replaced regularly.

[0032] Select fast-growing species with significant seasonal changes as dynamic species, dynamically adjust them according to social needs, and occupy ≤10% of the community area.

[0033] Core species are evenly distributed in a grid pattern, functional species are adjacent to pollution sources / heat island areas, and dynamic species are clustered and embedded in visual focus areas.

[0034] The present invention also provides bacterial fertilizer management after plant transplanting: Step 7: Dissolve the freeze-dried powder of salt-tolerant nitrogen-fixing bacteria in sterile water and add sodium molybdate-ferric citrate activation solution. The mass ratio of freeze-dried powder: sterile water: sodium molybdate-ferric citrate activation solution is 1:100:0.5 (i.e., 100 mL of sterile water and 0.5 g of activation solution per 1 g of powder). Incubate at 24-26°C, shaking at 150 rpm for 48 hours to obtain a bacterial solution.

[0035] Preferably, the sodium molybdate-ferric citrate activation solution is based on water and includes 0.05 mmol / L sodium molybdate and 0.1 mmol / L ferric citrate.

[0036] Step 8: Use a backpack electric sprayer (atomized particle size ≤ 100 μm) to carry out the operation in the early morning after the dew has dried or in the evening (temperature 18-25℃, humidity > 60%). The spraying amount is controlled according to the plant type. For core species, 300 mL / plant, focusing on spraying the middle and lower leaves; for functional species / dynamic species, 100 mL / m 2 , the whole plant is evenly covered.

[0037] Step 9: Within 2 hours after spraying the microbial agent, use the same equipment to spray sodium molybdate-ferric citrate activation solution, with the spraying amount being 1 / 2 of the microbial agent.

[0038] Preferably, the pH value of the activation solution is adjusted to 6.0-6.5 to avoid precipitation of iron ions.

[0039] The present invention has the following advantages: Multi-dimensional quantification and dynamic trade-offs: Comprehensively quantify ecological functions (cooling, nitrogen fixation, dust retention), social needs (visual, participation) and stress resistance (salt tolerance, frost resistance), and use the AHP-entropy weight method combined with site attributes to dynamically adjust weights to achieve scientific and accurate screening and overcome the one-sidedness of traditional methods.

[0040] Modular configuration improves comprehensive efficiency: Through the modular configuration strategy of core species-functional species-dynamic species (60%:30%:≤10%), taking into account ecological stability, dominant functional needs and social landscape dynamic response, the green space PM is significantly improved. 2.5 Cutback capacity, winter landscape satisfaction, and nitrogen fixation efficiency.

[0041] Microorganism-plant synergistic effect: Combining specific salt-tolerant nitrogen-fixing bacteria and molybdenum-iron micro-fertilizer activation liquid spraying technology, the leaf nitrogen fixation rate is significantly improved (Example 4 reaches 146%), the dependence on chemical fertilizers is reduced (Example 2 fertilization cost -35%, Example 4 soil improvement cost -62%), and the adaptability of plants to stress environments such as salinity is enhanced (Example 4 survival rate is increased to 92%).

[0042] Universality and high efficiency: We provide customized solutions for highly heterogeneous urban environments (such as cold industrial areas, dusty areas, waterfront areas, and coastal saline areas). After verification in four cities, we have achieved significant results in improving core functions (dust retention +37%, PM 10 -45%, cooling +3.1℃), while significantly reducing costs (irrigation -28%, soil improvement -40~62%) and improving plant survival rate (89~97%). By applying selected varieties (such as catkin-free Salix matsudana), urban environmental problems such as "spring snow" can be effectively eradicated. DETAILED DESCRIPTION

[0043] The following is a clear and complete description of the technical solutions in the embodiments of the invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present invention.

[0044] Example 1 Changchun Cold Industrial Zone (Antifreeze-Dust Retention Dominant) Environmental constraints: average annual temperature 4.6°C, permafrost depth 1.8m, PM 2.5 The annual average is 78 μg / m 3 .

[0045] Functional weights: 50% stress resistance (frost resistance + pollution resistance), 40% ecological function (dust retention), 10% social demand Module configuration:

[0046] Example 2: Beijing Dust Pollution Area (Dust Retention-Landscape Synergy) Environmental constraints: Spring PM 10 Peak value 800 μg / m 3 , the community demands to add more color and extend green.

[0047] Technical measures: Inoculate nitrogen-fixing bacteria on the leaves and spray 0.05mmol / L sodium molybdate.

[0048] Effect comparison:

[0049] Example 3: Hangzhou Waterfront (Cooling - Landscape-driven) Dynamic weight adjustment: In summer (June-September), the ecological function weight rises to 60% (focusing on cooling), and social demand 40%; In winter (December-February), the weight of social demand rises to 55% (focusing on flower viewing).

[0050] Configuration plan: Core species: Cinnamomum camphora (canopy shading rate 85%).

[0051] Functional species: Weeping willow (transpiration rate 8.2mmol / m² / s, temperature reduction 4.3℃).

[0052] Dynamic species: Summer: Lotus (visual index 0.93); Winter: Camellia sasanqua (blooms in winter, visual index 0.88).

[0053] Example 4: Haikou Coastal Saline Area (Salt Resistance-Ecological Restoration) Microbial enhancement: Inoculate salt-tolerant nitrogen-fixing bacteria and combine with 0.1mmol / L ferric citrate Quantitative results:

[0054] Comprehensive comparison of results (summary of four cities)

[0055] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A dynamic screening method for urban green space plants based on multi-dimensional functional trade-offs, characterized in that: The following steps are involved: Step 1: Quantify ecological functions: Measure the net photosynthetic rate per unit leaf area and calculate the cooling index according to the formula: cooling index = 0.38 × photosynthetic rate + 4.2; collect plant leaves, measure the ANF rate of diazotrophic bacteria in the leaf sphere and the Fe / Mo content in the leaves, and calculate the synergistic coefficient; measure the PM2.5 adsorption per unit leaf area to obtain the dust retention capacity; Ecological index = (cooling index / 15) + (ANF efficiency coefficient / 2) + dust retention score; Step 2: Quantify social needs: Evaluate the ornamental value of plants, combining the length of flowering period and color saturation to obtain a visual index; Participation is determined by recording the frequency of voting on the public platform and the adoption rate of improvement suggestions; Step 3: Quantification of stress resistance: In the gradient salinity hydroponic experiment, the relative biomass decline rate ≤ 20% was used as the threshold to obtain salt tolerance; the electrolyte leakage rate was measured to obtain frost resistance; Step 4: Comprehensive score = 0.4 × ecological index + 0.3 × social index + 0.3 × resilience index; Step 5: Use the AHP-entropy weight method dual-weight model to automatically adjust the indicator weights according to site attributes, with stress resistance weighting 20%-40%, ecological function weighting 30%-40%, and social demand weighting 20%-50%; Step 6: Select species with strong stress resistance and a lifespan of more than 10 years as core species, accounting for 60% of the community area. Configure high-quantity indicator species based on dominant ecological needs as functional species, accounting for 30% of the community area. Select fast-growing species with significant seasonal changes as dynamic species, and dynamically adjust them according to social needs, accounting for ≤10% of the community area. The core weight model automatically adjusts the indicator weights according to site attributes: stress resistance weight 20%-40%, ecological function weight 30%-40%, and social demand weight 20%-50%; Step 6: Select species with strong stress resistance and a lifespan of more than 10 years as core species, accounting for 60% of the community area; configure species with high quantitative indicators according to the dominant ecological needs as functional species, accounting for 30% of the community area; select fast-growing species with significant seasonal changes as dynamic species, dynamically adjust according to social needs, and occupy ≤10% of the community area; core species are evenly distributed in a grid pattern, functional species are adjacent to pollution sources / heat island areas, and dynamic species are clustered and embedded in visual focus areas.

2. The method for dynamic screening of urban green space plants based on multi-dimensional functional trade-offs according to claim 1, characterized in that: It also includes the steps for managing microbial fertilizer after plant transplanting: Step 7: Mix the salt-tolerant nitrogen-fixing bacteria with sterile water, add sodium molybdate-ferric citrate activation solution, and culture at 24-26° C. and 150 rpm for 48 hours to obtain a bacterial solution; Step 8: Spray the bacterial solution, 300 mL / plant for core species, focusing on spraying the middle and lower leaves; 100 mL / m 2 , the whole plant is evenly covered; Step 9: Within 2 hours after spraying the microbial agent, use the same equipment to spray sodium molybdate-ferric citrate activation solution, with the spraying amount being 1 / 2 of the microbial agent.

3. The method for dynamic screening of urban green space plants based on multi-dimensional functional trade-offs according to claim 2 is characterized in that: The sodium molybdate-ferric citrate activation solution is based on water and includes 0.05 mmol / L sodium molybdate and 0.1 mmol / L ferric citrate.

4. The method for dynamic screening of urban green space plants based on multi-dimensional functional trade-offs according to claim 2, characterized in that: The pH value of the activation solution in step nine is adjusted to 6.0-6.

5.

5. The method for dynamic screening of urban green space plants based on multi-dimensional functional trade-offs according to claim 1 is characterized in that: In step 1, the net photosynthetic rate per unit leaf area was measured by a photosynthetic meter, the ANF rate of chlorophyll was measured by acetylene reduction method, the Fe / Mo content in the leaves was detected by ICP-MS, and the PM per unit leaf area was measured by elution weighing method. 2.5 Adsorption amount.

6. The method for dynamic screening of urban green space plants based on multi-dimensional functional trade-offs according to claim 1, characterized in that: Industrial areas: stress resistance weight 40%, ecological function weight 40%, social demand weight 20%; residential areas: social demand weight 50%, ecological function weight 30%, stress resistance weight 20%.

7. The method for dynamic screening of urban green space plants based on multi-dimensional functional trade-offs according to claim 1, characterized in that: The salt tolerance scoring standard in step 3 is 1.0 if the relative biomass decline rate is ≤10%, 0.8 if it is 10-20%, and 0 if it is >20%.

8. The method for dynamic screening of urban green space plants based on multi-dimensional functional trade-offs according to claim 1, characterized in that: The frost resistance scoring standard described in step 3 is 1.0 for an exudation rate ≤ 20%, 0.7 for 20-40%, and 0.3 for >40%.

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