Evaluating the regional cumulative impact of wind farms on birds: how can spatially explicit dynamic modelling improve impact assessments and monitoring?

Abstract

Summary1. The Eurasian skylark Alauda arvensis is very susceptible to the negative effects of wind farms. In northern Portugal, this evidence is particularly severe due to the skylark's preference for mountain breeding habitats where most wind farms are located. Facing the frequent failure of environmental impact assessments (EIA) to evaluate the cumulative impacts of wind farms on wildlife, this study aimed to develop and test a methodology to quantify local and regional consequences on birds, using skylarks as a test species, taking into account future predictable environmental changes. 2. We propose a spatially explicit dynamic approach that combines the results from multiple modelling techniques under a common framework to assess the local and cumulative regional impacts of wind farms on skylark populations. This includes the following: (i) modelling the local impact of wind farms (in terms of collision mortality) on the skylark population dynamics by developing an index for quantitative assessments, (ii) determining the actual and future skylark breeding distribution across northern Portugal and (iii) integrating the above contributions in an emergent spatially explicit regional representation to capture the ecological cumulative consequences as a whole. 3. The simulations show an increasing average local impact for the skylark breeding populations directly affected by wind farms, expressed in mean number of collision fatalities per UTM study unit (1 km 2 ), representing 1Á3% of the local breeders in 2006 and 4% in 2026.4. The distribution area of skylark breeding populations was predicted to decrease around 4Á5% throughout a period of 15 years, as a result of the scenario of climate and land cover changes in the study area. When combined with a concomitant increase in skylark global mortality (c. 184%) induced by all wind farms in the study region, the above trend contributes to an intensification of the regional cumulative impact from 1Á2% to 3Á7% of the total estimated breeding individuals. 5. Synthesis and applications. The proposed modelling framework represents a step forward in evaluating the multi-scale cumulative consequences of wind farms on vulnerable birds, using skylarks as a test species. This could be used in the future to guide monitoring efforts and to improve the applicability of the data bases generated by long-term ecological research and monitoring studies.

Avian SDMs: current state, challenges, and opportunities

“…General application Examples Specific issues Examples Conservation Identification of priority areas for bird conservation Guisan et al 2013, Frick et al 2014 Seabirds and marine environments Lavers et al 2014 Identifying protected areas to meet specific targets Naoe et al 2015 Identifying no-go areas to reduce human-wildlife conflicts in wind power planning Reid et al 2015 Identifying specific habitats for certain species needs Brambilla and Saporetti 2014 Validating umbrella species to match conservation goals Fourcade et al 2017 Evaluating or forecasting the effect of environmental changes Green et al 2008 Future effectiveness of protected areas over different spatial scales Coetzee et al 2009, Hole et al 2009, Veloz et al 2013, Virkkala et al 2013, Brambilla et al 2015 Kissling 2013, Tracewski et al 2016 Including changes in demography Haché et al 2016 Including nest predation and food limitation Harris et al 2012 Including wind farm construction Bastos et al 2016 Invasive birds Predictions of invasion risk Muñoz and Real 2006, Nyári et al 2006, Real et al 2008, Strubbe and Matthysen 2009, Herrando et al 2010, Di Febbraro and Mori 2015, Fraser et al 2015 Range dynamics under climate change Huntley et al 2007, Reino et al 2009, Graham et al 2011 (Continued) …”

“…Further, SDMs have been used to quantify species' extinction risk by estimating changing habitat availability (Tracewski et al 2016) -partly by taking into account additional information on demography, nest predation, and food limitation (Harris et al 2012, Kissling 2013, Haché et al 2016. In conjunction with long-term ecological research and monitoring studies, such approaches hold strong potential to assess impacts of many aspects of anthropogenic environmental change or in the context of environmental planning (Bastos et al 2016). To this end, data from longterm monitoring projects have been shown to provide useful information for predicting trends in bird distributions using SDMs, representing an important supplement to atlas data .…”

Long-term sustainability of cork oak agro-forests in the Iberian Peninsula: A model-based approach aimed at supporting the best management options for the montado conservation

“…Therefore, this study represents an early step to support strategic options for impact mitigation and management by providing projections of long-term indicator trends under realistic social-ecological change scenarios (Bastos et al, 2015). Although the projections recreates realistically the known cork oak regeneration patters occurring in montado regions, some limitations arise when considering validation as a fundamental process to assess the relative accuracy of the model response facing independent real data (Rykiel, 1996).…”

“…Ecological modelling provides useful tools to study complex systems by predicting the outcome of alternative scenarios, and might help guiding the most correct management options from projected future outcomes (e.g. Bastos et al, 2012Bastos et al, , 2015Fernandes et al, 2013;Santos et al, 2013). Actually dynamic models can be used to support the mechanistic understanding of complex multifactorial ecological processes as they simultaneously integrate the structure and the composition of systems for a specific period (Jørgensen, 1994(Jørgensen, , 2001.…”

Identifying the Relevant Local Population for Environmental Impact Assessments of Mobile Marine Fauna

“…To adequately characterize the impact of a proposed development or activity on a particular species, it is necessary to identify the relevant local population which may be impacted (Brittingham et al, 2014;Bastos et al, 2016;Brown et al, 2016). In highly fragmented landscapes, the relevant local population may be straightforward to delineate because of the geographical separation between the area affected by the development and the nearest other sites where the species may be found.…”