Framework for strategic wind farm site prioritisation based on modelled wolf reproduction habitat in Croatia

In order to meet carbon reduction targets, many nations are greatly expanding their wind power capacity. However, wind farm infrastructure potentially harms wildlife, and we must therefore find ways to balance clean energy demands with the need to protect wildlife. Wide-ranging carnivores live at low density and are particularly susceptible to disturbance from infrastructure development, so are a particular concern in this respect. We focused on Croatia, which holds an important population of wolves and is currently planning to construct many new wind farms. Specifically, we sought to identify an optimal subset of planned wind farms that would meet energy targets while minimising potential impact on wolves. A suitability model for wolf breeding habitat was carried out using Maxent, based on six environmental variables and 31 reproduction site locations collected between 1997 and 2015. Wind farms were prioritised using Marxan to find the optimal trade-off between energy capacity and overlap with critical wolf reproduction habitat. The habitat suitability model predictions were consistent with the current knowledge: probability of wolf breeding site presence increased with distance to settlements, distance to farmland and distance to roads and decreased with distance to forest. Spatial optimisation showed that it would be possible to meet current energy targets with only 31% of currently proposed wind farms, selected in a way that reduces the potential ecological cost (overall predicted wolf breeding site presence within wind farm sites) by 91%. This is a highly efficient outcome, demonstrating the value of this approach for prioritising infrastructure development based on its potential impact on wide-ranging wildlife species

A transitioning Arctic surface energy budget: the impacts of solar zenith angle, surface albedo and cloud radiative forcing

Snow surface and sea-ice energy budgets were measured near 87.5°N during the Arctic Summer Cloud Ocean Study (ASCOS), from August to early September 2008. Surface temperature indicated four distinct temperature regimes, characterized by varying cloud, thermodynamic and solar properties. An initial warm, melt-season regime was interrupted by a 3-day cold regime where temperatures dropped from near zero to -7°C. Subsequently mean energy budget residuals remained small and near zero for 1 week until once again temperatures dropped rapidly and the energy budget residuals became negative. Energy budget transitions were dominated by the net radiative fluxes, largely controlled by the cloudiness. Variable heat, moisture and cloud distributions were associated with changing air-masses. Surface cloud radiative forcing, the net radiative effect of clouds on the surface relative to clear skies, is estimated. Shortwave cloud forcing ranged between -50 W m-2 and zero and varied significantly with surface albedo, solar zenith angle and cloud liquid water. Longwave cloud forcing was larger and generally ranged between 65 and 85 W m-2, except when the cloud fraction was tenuous or contained little liquid water; thus the net effect of the clouds was to warm the surface. Both cold periods occurred under tenuous, or altogether absent, low-level clouds containing little liquid water, effectively reducing the cloud greenhouse effect. Freeze-up progression was enhanced by a combination of increasing solar zenith angles and surface albedo, while inhibited by a large, positive surface cloud forcing until a new air-mass with considerably less cloudiness advected over the experiment area. © 2010 Springer-Verlag