Are Landscape Configuration Metrics Worth Including When Predicting Specialist and Generalist Bird Species Density? A Case of the Generalised Additive Model Approach

Abstract

Due to the complexity of factors that influence species density on a large geographical scale, the effectiveness of the species distribution model (SDM) is still debatable. That is why the buffer zone (the area within 100 m from the outside edge of the patch), the core, i.e. (patches excluding the 100 m buffer zone from the patch's edge) and patch shape are explored in this study to see how they affect the density of habitat specialist and generalist bird species. Two sets of generalised additive models were generated separately for each of the four bird species: One set of models contained landscape configuration metrics as an additional predictor variable, and the other did not. The results showed that models including the core, the buffer zone and the shape of patches turned out to be definitely better than models without them. Specialist species, the Corn bunting and the Wood nuthatch, are more likely to occur in the core of the preferred patches, and they choose those of a simple shape; while generalist species, the Whinchat and the Tree pipit, are more probable to be present in the buffer zone of a more complicated shape. Thus, the results clearly show that specific landscape configuration models can improve the predictive power of SDMs and can be used as an effective tool for predicting species density and functional bird diversity (specialist and generalist). Furthermore, from the applied ecology perspective, detailed landscape configuration metrics can be considered as a surrogate of elusive habitat conditions.

Generalised Additive Models and Random Forest Approach as effective methods for predictive species density and functional species richness

“…So, both models can detect the influence of the same predictor, but with a varying power, which in turn may suggest that relationships between predictors and species distribution may partly reflect a spatial structure of predictors, especially climate and topography, rather than a real ecological process (Bahn and Mcgill 2007;Beale et al 2008;Chapman 2010). Furthermore, in the ecological modelling approach the problem with comparing models with one another increases along with spatial complexity (Hof et al 2012;Carrasco et al 2014;Seppelt and Voinov 2002;Kosicki 2018). When a lot of predictors affect species density and/or species richness in different ways (positive/negative and/or linear/non-linear), and models' output is transferred to new areas, more rigorous tests are indispensable.…”

Relevance of the Cell Neighborhood Size in Landscape Metrics Evaluation and Free or Open Source Software Implementations

“…The value of the cell neighborhood parameter was specified in eight different papers: seven chose a Moore definition [13][14][15][16][17][18][19][20] and one a von Neumann definition [21]. The 16 papers which exclusively employed LecoS [22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37] used an 8-cells neighborhood rule, as it is the only setting available in the add-on; a similar hypothesis is applicable to the four works which used r.li in GRASS [38][39][40][41], which uses a 4-cells neighborhood definition. The papers which did not specify the definition of the neighborhood in FRAGSTATS are assumed to have used a 8-cells definition, since this is the default setting [42], although it is not possible to prove this assumption.…”

Ecologia De Paisagens Aplicada Ao Ordenamento Territorial E Gestão Florestal: Procedimento Metodológicos

“…Além disso, as métricas de paisagem aplicam-se no manejo de fauna silvestre, como por exemplo em estudo de Kosicki (2018) que analisou, a partir da configuração da paisagem, a densidade de espécies de aves especialistas e generalistas. Neste mesmo sentido, Morelli et al (2018) avaliaram associações de métricas de paisagem com a diversidade de aves e métricas de comunidades, concluindo que a diversidade taxonômica relacionou-se à métrica da diversidade, explicada pelas métricas de paisagem.…”