Living on the edge - modelling habitat suitability for species at the edge of their fundamental niche

By Veronika Braunisch, K. Bollmann, R. F. Graf, A. Hirzel. 2008

111 citations recorded by the source corpus.

Predictive species distribution models have become increasingly common in conservation management. Among them, envelope-based approaches like the Ecological Niche Factor Analysis (ENFA) are particularly advantageous, as they require only presence data. Based on the assumption that the absolute frequency of species presence is a direct indicator of habitat suitability (HS), habitat suitability indices (HSI) are computed. However, this assumption may be misleading when the scarcity of optimal habitat forces most of the individuals to live in suboptimal conditions. This often happens when the environmental conditions in the study area represent only a marginal part of the species fundamental niche. In this study we propose three new HS algorithms for ENFA models, which address such ‘edge of niche’ situations. The first algorithm (area-adjusted median, Ma) takes the availability of environmental conditions in the study area into account, the second (median + extremum, Me) addresses situations where the species’ optimum is at or beyond the extremum of the investigated environmental gradient, and the third (area-adjusted median + extremum, Mae) combines both approaches. These algorithms were applied to two populations of capercaillie (Tetrao urogallus), situated in different positions relative to the environmental gradient represented in the respective study area, and compared with the classical median algorithm (M). We evaluated the models using cross-validation and a comparison with an expert model based on external data. In both study areas, the HS maps obtained with the three new algorithms differed visibly from those calculated with the median algorithm. Cross-validation and comparison with external data showed that the new algorithms always provided better models, with the extremum-based algorithms (Me and Mae) performing best. We conclude that the new algorithms can extend the applicability of ENFA-models to a broader range of conservationrelevant species by improving HS calculations for skewed species–habitat relationships in marginal habitats.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/1cb47f81324a0d083724467a43befd1e4773c55c

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In Ecological Modeling

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In Nature and Landscape Conservation

Citations in the corpus

Using presence‐only modelling to predict Asian elephant habitat use in a tropical forest landscape: implications for conservation (2010, background): “Hence, the canonical depiction of the species’ niche relative to its environment allows to evaluate which part of the available habitat is occupied and to assess to which extend the available habitat is utilized (Titeux et al., 2007; Braunisch et al., 2008).”
Using multi-scale modelling to predict habitat suitability for species of conservation concern: The grey long-eared bat as a case study (2011, unknown): “(2011), doi:10.1016/j.biocon.201 in sub-optimal conditions (Braunisch et al., 2008).”
Habitat suitability modelling and niche theory (2008, unknown): “2002; Braunisch et al .”
Differential impact of landscape transformation on pumas (Puma concolor) and jaguars (Panthera onca) in the Upper Paraná Atlantic Forest (2011, methodology): “The analysis was developed using biomapper 4.07.303 (Hirzel et al., 2008) that contains four algorithms for habitat-suitability calculation (Braunisch et al., 2008).”
Habitat suitability for marine fishes using presence-only modelling and multibeam sonar (2010, methodology): “This is in contrast to findings by Braunisch et al. (2008), who found that the more recent ENFA algorithms provided better models of habitat suitability for large forest grouse Tetrao urogallus than the original ENFA-M algorithm.”
Equilibrium or not? Modelling potential distribution of invasive species in different stages of invasion (2012, methodology): “, 2007) using the medianextremum algorithm that assumes the species optimum is indicated by either the median or extreme values of environmental conditions (Braunisch et al., 2008).”
Predicting species distribution at range margins: testing the effects of study area extent, resolution and threshold selection in the Sahara–Sahel transition zone (2014, background): “Our results support the view that at range margins of species distribution, where availability of optimal habitats is limited, species are forced to occupy suboptimal habitats different from global mean (Braunisch et al., 2008).”