5 results about "Species selection" patented technology

The application provides a reservoir drawdown zone suitable habitat construction and precise vegetation restoration method, which comprises the following steps: S1, reservoir drawdown zone habitat suitability analysis; S2, reservoir drawdown zone vertical function partition; S3, microtopography regulation; S4, vegetation restoration species selection and partition function configuration. The application fully considers the reservoir periodic flooding rhythm and site environment difference, combines the partition prominent problems, screens the tree-shrub-grass vegetation, and optimizes the partition configuration, so that the functions and benefits such as soil fixation, bank protection, sand interception, pollution interception, water quality protection and biodiversity maintenance are maximized.

The invention relates to the technical field of ecological system restoration, in particular to an alpine region soil fertility activation technology. According to the specific technical scheme, the method comprises the following steps that firstly, detailed ecological environment investigation is conducted on the major engineering damaged area in the alpine region, and main species for vegetation restoration configuration are determined; 2, a detachable breeding base is constructed, species breeding testing and species configuration testing are conducted, and reconstructed soil is constructed with deep soil, surface soil and waste residues; and 3, selecting a breeding mode according to the configured main species. The method solves the common problem of surface soil nutrient depletion in ecological restoration engineering of the alpine region.

The invention relates to the technical field of ecological restoration and environmental engineering, and solves the technical problems that in existing engineering, species screening lacks a quantitative basis for substrate adaptation, an ecological window is not brought into an optimal decision, the function of an inhabiting device is single, and an evaluation result is difficult to translate into executable layout parameters. The method comprises the following steps: collecting substrate factor data of a target water body, unifying dimensions, comparing the data with a species response database, calculating a substrate matching score, and combining ecological windows such as water temperature, flow velocity, disturbance, transparency and the like to generate an optimal selection index; and outputting the target species, the suitable putting time period and the device layout parameters. According to the method, an integrated decision of seed selection, timing and layout is achieved, the colonization success rate and community stability are remarkably improved, the method is suitable for various water bodies such as lakes, rivers and wetlands, and the long-term restoration effect and operation and maintenance economical efficiency can be improved based on monitoring feedback iteration optimization parameters.

This invention belongs to the field of ecological restoration technology and relates to a method for screening species for the restoration of damaged ecosystems based on seed functional traits. It addresses the problems of lack of scientific basis for species selection, low establishment success rates, and potential biological invasion risks in existing restoration practices. Principal component analysis is used to extract key trait combinations, and hierarchical clustering analysis is performed based on principal component scores to classify functional groups with different restoration strategies. An adaptive evaluation mechanism is constructed to assess the relationship between multidimensional seed functional traits and field establishment, identifying and predicting the environmental adaptability and establishment capacity of candidate species. A screening system encompassing seed trait measurement, functional group identification, and field establishment rate prediction is established, transforming species selection from a traditional reliance on engineering experience or subjective judgment to a data-driven process, thereby improving the repeatability and reliability of the screening results.

This ecological monitoring system and method, based on the integration of community-specific species and multi-source intelligence, includes a species selection unit that optimizes representative species selection using artificial intelligence and ecological models; a monitoring unit that deploys a multi-scale monitoring network combining drones / unmanned vessels with in-situ sensors; a data acquisition and processing unit that integrates environmental DNA (eDNA) analysis, multi-source remote sensing, and real-time data acquisition using the Internet of Things (IoT), along with edge computing preprocessing; a data analysis and visualization unit that uses machine learning and digital twin technology for ecological health assessment, trend prediction, and visualization analysis; and an alarm unit based on artificial intelligence predictive models. This system enables precise, real-time, and intelligent monitoring and early warning of the dynamics of specific species communities, such as phytoplankton, as well as water health and ecosystem evolution trends, in the Yellow River estuary. This significantly improves monitoring efficiency, coverage, and prediction accuracy, providing strong technical support for estuarine ecological protection and management.