Integration of landscape metric surfaces derived from vector data improves species distribution models-Reference-Cited by-同舟云学术

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Integration of landscape metric surfaces derived from vector data improves species distribution models

Published:2020-09 Issue: Volume:431 Page:109160
ISSN:0304-3800
Container-title:Ecological Modelling
language:en
Short-container-title:Ecological Modelling

Author:

Ortner Olivia^ORCID,Wallentin Gudrun^ORCID

Publisher

Elsevier BV

Subject

Ecological Modeling

Reference53 articles.

1. ZonalMetrics - a Python toolbox for zonal landscape structure analysis;Adamczyk;Comput. Geosci.,2017

2. Habitat suitability and landscape structure: a maximum entropy approach in a mediterranean area;Amici;Landsc. Res.,2015

3. Species-specific tuning increases robustness to sampling bias in models of species distributions: an implementation with Maxent;Anderson;Ecol. Modell.,2011

4. Spatial filtering to reduce sampling bias can improve the performance of ecological niche models;Boria;Ecol. Modell.,2014

5. Using kernel density estimation to assess the spatial pattern of road density and its impact on landscape fragmentation;Cai;Int. J. Geograph. Inf. Sci.,2013

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3. Applying landscape metrics to species distribution model predictions to characterize internal range structure and associated changes;Global Change Biology;2022-11-17

4. Landscape-scale drivers of endangered Cape Sable Seaside Sparrow (Ammospiza maritima mirabilis) presence using an ensemble modeling approach;Ecological Modelling;2021-12

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