Toward community predictions: Multi‐scale modelling of mountain breeding birds' habitat suitability, landscape preferences, and environmental drivers

Abstract

Across a large mountain area of the western Swiss Alps, we used occurrence data (presence‐only points) of bird species to find suitable modelling solutions and build reliable distribution maps to deal with biodiversity and conservation necessities of bird species at finer scales. We have performed a multi‐scale method of modelling, which uses distance, climatic, and focal variables at different scales (neighboring window sizes), to estimate the efficient scale of each environmental predictor and enhance our knowledge on how birds interact with their complex environment. To identify the best radius for each focal variable and the most efficient impact scale of each predictor, we have fitted univariate models per species. In the last step, the final set of variables were subsequently employed to build ensemble of small models (ESMs) at a fine spatial resolution of 100 m and generate species distribution maps as tools of conservation. We could build useful habitat suitability models for the three groups of species in the national red list. Our results indicate that, in general, the most important variables were in the group of bioclimatic variables including “Bio11” (Mean Temperature of Coldest Quarter), and “Bio 4” (Temperature Seasonality), then in the focal variables including “Forest”, “Orchard”, and “Agriculture area” as potential foraging, feeding and nesting sites. Our distribution maps are useful for identifying the most threatened species and their habitat and also for improving conservation effort to locate bird hotspots. It is a powerful strategy to improve the ecological understanding of the distribution of bird species in a dynamic heterogeneous environment.

No place to hide: Rare plant detection through remote sensing

“…Currently, there is still no consensus on which are the most suitable metrics to evaluate the predictive performance of SDMs, which has the use of multiple metrics as the best solution (Amini Tehrani et al., 2020; Breiner et al., 2015). However, since each accuracy metric provides a type of information, the choice should ideally be based on their intended use (Fielding & Bell, 1997) rather than on the arbitrary selection of different metrics.…”

Modeling current and future species distribution of breeding birds as regional essential biodiversity variables (SD EBVs): A bird perspective in Swiss Alps

“…This region is exposed to human activities which includes the urbanization and intensive land use. It has been negatively affected by the development of tourism, sporting activities, and agriculture in the subalpine regions which are marked by a mosaic of meadows and forest patches (see http://rechalp.unil.ch; Randin et al, 2009;Amini Tehrani et al, 2020).…”

The contribution of landscape features, climate and topography in shaping taxonomical and functional diversity of avian communities in a heterogeneous Alpine region

“…Both these opposing processes lead to landscape homogenisation (Brambilla 2019 ), resulting in severe losses of habitat diversity (Kujawa et al 2020 ), and lower the beta diversity of animal communities (Burgess and Maron 2016 ) . Habitat fragmentation negatively influences abundance, movements, and persistence of many bird species (Villard et al 1999 ) by disrupting connectivity between habitats (Amini Tehrani et al 2020 ) and reduces native biodiversity and ecological integrity (Noss and Cooperrider 1994 ). Moreover, habitat loss and fragmentation also affect functional diversity (Flynn et al 2009 ).…”

“…This combined approach is also key to effective conservation and management (Doley 2010 ), as is the evaluation of landscape composition or configuration effects over environmental gradients (Rüdisser et al 2012 ). This is particularly relevant in mountain landscapes, where elevation gradients shape complex environments (Liu et al 2018 ), even though this has rarely been explored (Amini Tehrani et al 2020 ). In the European Alps, a biodiversity hotspot hosting several endemic species (Jenkins et al 2013 ), LULC changes are occurring along broad elevation gradients, and across very different environments (Pecher et al 2013 ).…”