Learning and linking for invasive species management
نویسندگان
چکیده
منابع مشابه
Species distribution modelling of invasive alien species; Pterois miles for current distribution and future suitable habitats
The present study aims to predict the potential geographic distribution and future expansion of invasive alien lionfish (Pterois miles) with ecological niche modelling along the Mediterranean Sea. The primary data consisted of occurrence points of P. miles in the Mediterranean and marine climatic data layers were collected from global databases. All the used models run 100% su...
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Geographical Information Systems (GIS) are powerful tools in the field of invasive species management. GIS can be used to create potential distribution maps for all manner of taxa, including plants, animals, and diseases. GIS also performs well in the early detection and rapid assessment of invasive species. Here, we used GIS applications to investigate species richness and invasion patterns in...
متن کاملPAC Optimal Planning for Invasive Species Management: Improved Exploration for Reinforcement Learning from Simulator-Defined MDPs
Often the most practical way to define a Markov Decision Process (MDP) is as a simulator that, given a state and an action, produces a resulting state and immediate reward sampled from the corresponding distributions. Simulators in natural resource management can be very expensive to execute, so that the time required to solve such MDPs is dominated by the number of calls to the simulator. This...
متن کاملHawkes Processes for Invasive Species Modeling and Management
The spread of invasive species to new areas threatens the stability of ecosystems and causes major economic losses in agriculture and forestry. We propose a novel approach to minimizing the spread of an invasive species given a limited intervention budget. We first model invasive species propagation using Hawkes processes, and then derive closed-form expressions for characterizing the effect of...
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ژورنال
عنوان ژورنال: Ecology and Society
سال: 2018
ISSN: 1708-3087
DOI: 10.5751/es-10327-230329