Coherent ecological networks (EN) composed of core areas linked by ecological corridors are being developed worldwide with the goal of promoting landscape connectivity and biodiversity conservation. However, empirical assessment of the performance of EN designs is critical to evaluate the utility of these networks to mitigate effects of habitat loss and fragmentation. Landscape genetics provides a particularly valuable framework to address the question of functional connectivity by providing a direct means to investigate the effects of landscape structure on gene flow. The goals of this study are (1) to evaluate the landscape features that drive gene flow of an EN target species (European pine marten), and (2) evaluate the optimality of a regional EN design in providing connectivity for this species within the Basque Country (North Spain). Using partial Mantel tests in a reciprocal causal modeling framework we competed 59 alternative models, including isolation by distance and the regional EN. Our analysis indicated that the regional EN was among the most supported resistance models for the pine marten, but was not the best supported model. Gene flow of pine marten in northern Spain is facilitated by natural vegetation, and is resisted by anthropogenic landcover types and roads. Our results suggest that the regional EN design being implemented in the Basque Country will effectively facilitate gene flow of forest dwelling species at regional scale.

SUMMARY: Transport infrastructures are a major driver of global landscape change. In many areas, highways were built before environmental impact assessments required the implementation of wildlife crossing structures. A fundamental task in the development of ecological networks is identifying areas where dispersal pathways of vulnerable populations may be blocked or affected by high volume roads. Financial considerations may limit investment, thus it is vital to establish the relative contribution of each road defragmentation location to upholding habitat connectivity and availability. In this paper, recent methodological developments in habitat network analysis, derived from the probability of connectivity index, were refined and used to evaluate the role of each highway defragmentation location in restoring landscape connectivity. The forest protected area network in the Basque country (northern Spain) was selected as an illustrative case study. The proposed approach was able to quantify and effectively account for a combination of factors determining the contribution of each highway defragmentation location to upholding connectivity, which are rarely jointly considered in analyses oriented to support restoration decisions in landscapes affected by the barrier effect of transport infrastructures. The contribution to connectivity of each defragmentation location depended on its topological position in the landscape, on the relative decrease in the effective distance among habitat areas that results from the permeability restoration at that location, on the distance from the defragmentation location to other alternative wildlife crossing structures already existing in the landscape, on the amount of habitat in the areas connected by the linkages that run through the defragmentation location and on the dispersal abilities of the focal species.

Since the first months of 2020, the Covid-19 pandemic has driven social distancing measures in many countries, which have made it potentially more attractive to reside in less populated areas. This paper visualizes whether the registered populations in municipalities with fewer than 2000 inhabitants in Spanish regions have changed during 2020 in a different way than previous years. The per cent variation of the rural population is measured, as well as the proportion of the rural population over the total population, in two periods: January 2000–January 2020 and during 2020. The results show an increase in the rural population in 13 of the 17 Spanish regions, and an increase in the proportion in 14 regions during 2020, in contrast to the declining trends prevailing in previous years.