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Species diversity typically increases from higher to lower latitudes, but the regional‐scale variation along this geographic gradient remains unclear. It has been suggested that species diversity throughout Amazonia generally increases westward toward the Andes, but this pattern and its environmental determinants require further investigation for most ...
Pilar L. Maia‐ Braga +14 more
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Ecological niche models of invasive seaweeds
Journal of Phycology, 2015Ecological niche models (ENMs) are commonly used to calculate habitat suitability from species’ occurrence and macroecological data. In invasive species biology, ENMs can be applied to anticipate whether invasive species are likely to establish in an area, to identify critical routes and arrival points, to build risk maps and to predict the extent of ...
Vanessa R, Marcelino, Heroen, Verbruggen
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Cognitive niches: An ecological model of strategy selection.
Psychological Review, 2011How do people select among different strategies to accomplish a given task? Across disciplines, the strategy selection problem represents a major challenge. We propose a quantitative model that predicts how selection emerges through the interplay among strategies, cognitive capacities, and the environment.
Marewski, J., Schooler, L.
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2019
Abstract Impact assessments increasingly rely on models to project the potential impacts of climate change on species distributions. Ecological niche models have become established as an efficient and widely used method for interpolating (and sometimes extrapolating) species’ distributions.
Damaris Zurell, Jan O. Engler
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Abstract Impact assessments increasingly rely on models to project the potential impacts of climate change on species distributions. Ecological niche models have become established as an efficient and widely used method for interpolating (and sometimes extrapolating) species’ distributions.
Damaris Zurell, Jan O. Engler
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2011
This chapter explains how environmental data can be used to create models that characterize species’ ecological niches in environmental space. It introduces a model, which is a function constructed by means of data analysis for the purpose of approximating the true relationship (that is, the niche) in the form of the function f linking the environment ...
A. Townsend Peterson +6 more
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This chapter explains how environmental data can be used to create models that characterize species’ ecological niches in environmental space. It introduces a model, which is a function constructed by means of data analysis for the purpose of approximating the true relationship (that is, the niche) in the form of the function f linking the environment ...
A. Townsend Peterson +6 more
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Programming Ecological Niche Modeling Workflows in the Cloud
2013 27th International Conference on Advanced Information Networking and Applications Workshops, 2013In the last decades biology scientists have relied on their own resources and tools to run the experiments and store the results of the analysis. However, the explosion of big data and the growing availability of computational methods find an obstacle in the lack of computational and storage resources.
Lezzi D. +5 more
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Ecological niche models improve home range estimations
Journal of Zoology, 2020AbstractHome ranges in animals can be estimated by different methods like minimum convex polygons, characteristic hulls or kernels while correlative ecological niche models (ENMs) are commonly employed for forecasting species' ranges. However, ENMs can also model the distribution of individuals if environmental very high spatial resolution data are ...
N. Sillero +3 more
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Modelling ecological niches with support vector machines
Journal of Applied Ecology, 2006SummaryThe ecological niche is a fundamental biological concept. Modelling species’ niches is central to numerous ecological applications, including predicting species invasions, identifying reservoirs for disease, nature reserve design and forecasting the effects of anthropogenic and natural climate change on species’ ranges.A computational analogue ...
Drake, J. M., Randin, C., Guisan, A.
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