Avian SDMs: current state, challenges, and opportunities

Abstract

Quantifying species distributions using species distribution models (SDMs) has emerged as a central method in modern biogeography. These empirical models link species occurrence data with spatial environmental information. Since their emergence in the 1990s, thousands of scientific papers have used SDMs to study organisms across the entire tree of life, with birds commanding considerable attention. Here, we review the current state of avian SDMs and point to challenges and future opportunities for specific applications, ranging from conservation biology, invasive species and predicting seabird distributions, to more general topics such as modeling avian diversity, niche evolution and seasonal distributions at a biogeographic scale. While SDMs have been criticized for being phenomenological in nature, and for their inability to explicitly account for a variety of processes affecting populations, we conclude that they remain a powerful tool to learn about past, current, and future species distributions -at least when their limitations and assumptions are recognized and addressed. We close our review by providing an outlook on prospects and synergies with other disciplines in which avian SDMs can play an important role.

Biotic interactions in species distribution models enhance model performance and shed light on natural history of rare birds: a case study using the straight‐billed reedhaunter Limnoctites rectirostris

“…In this sense, SDMs have addressed a wide array of questions, such as quantifying environmental niches of species and predicting their geographic distributions, assessing the impact of global environmental change on species distributions, predicting suitable areas for rare or endangered species, and supporting appropriate conservation planning (Guisan and Thuiller 2005). In this field of ecology, birds have been the focus of many SDM studies because of the high availability of freely accessible avian occurrence data (Engler et al 2017).…”

“…Nevertheless, both theory and facts contest such statement because quantifying the fundamental niche does not explain the entire distribution for every species, and numerous studies have shown that the inclusion of biotic interactions improve predictions of species distributions at broad geographical scales (Araújo and Luoto 2007, Heikkinen et al 2007, Bateman et al 2012, Hof et al 2012, Giannini et al 2013, Araújo and Rozenfeld 2014, Crystal-Ornelas et al 2017, Atauchi et al 2018. Besides, endotherm distributions may be less directly linked to bioclimatic variables than ectotherm distributions (Engler et al 2017). Therefore, a critical assessment about the importance of biotic interactions in SDMs, particularly in endotherms, is still needed.…”

“…Indeed, SDMs have shown high performance for identifying important environmental variables explaining the distributions of birds with these characteristics (Gibson et al 2007, Tinoco et al 2009, Marini et al 2010, Botero-Delgadillo et al 2012, Wu et al 2012, Girini et al 2017. In this context, and given that birds are one of the most well-known taxonomic groups, avian SDMs provide a suitable model into which include biotic interactions (Engler et al 2017).…”

The relative importance of biotic and abiotic determinants of temporal occupancy for avian species in North America

“…Birds are particularly suitable for modelling species ranges since they are well studied and there are ample data on their presence over time at large spatial extents (Bennett, Clarke, Thomson, & Mac Nally, 2015;Engler et al, 2017;Palacio & Girini, 2018). We used the North American Breeding Bird Survey (BBS) to characterize geographic variation in species presence and abundance.…”

Evaluating interspecific niche overlaps in environmental and geographic spaces to assess the value of umbrella species

“…Spatial modelling tools have been frequently used to address the issues related to multi-species conservation, for example to support the design of reserve networks or to delineate protected areas (Moilanen et al 2005, Ozaki et al 2006, Sutcliffe et al 2015. More recently, species distribution modelling (SDM) appeared as an approach to assess the distribution of species in a conservation context, for example to predict the expansion of a biological invader or estimate range shifts under climate change (Guisan et al 2013, Engler et al 2017). These statistical methods can also be used to map, quantify and compare the geographical ranges of various species of conservation interest, hence appearing as valuable tools to estimate the number and proportion of species which would benefit from conservation actions targeted on an umbrella species.…”