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Knowledge on the relationships between species functional traits and environmental filters is key to understanding the mechanisms underlying the current patterns of biodiversity loss from a multi-taxa perspective. The aim of this study was to identify the main environmental factors driving the functional structure of a terrestrial vertebrate community (mammals, breeding birds, reptiles and amphibians) in a temperate mountain system (the Cantabrian Mountains; NW Spain). Based on the Spanish Inventory of Terrestrial Vertebrate Species, we selected three functional traits (feeding guild, habitat use type and daily activity) and defined, for each trait, a set of functional groups considering vertebrate species with common functional characteristics. The community functional structure was evaluated by means of two functional indexes indicative of functional redundancy (species richness within each functional group) and functional diversity. Ordinary least squares regression and conditional autoregressive models were applied to determine the response of community functional structure to environmental filters (climate, topography, land cover, physiological state of vegetation, landscape heterogeneity and human influence). The results revealed that both functional redundancy and diversity of terrestrial vertebrates were non-randomly distributed across space; rather, they were driven by environmental filters. Climate, topography and human influence were the best predictors of community functional structure. The influence of land cover, physiological state of vegetation and landscape heterogeneity varied among functional groups. The results of this study are useful to identify the general assembly rules of species functional traits and to illustrate the importance of environmental filters in determining functional structure of terrestrial vertebrate communities in mountain systems. [ABSTRACT FROM AUTHOR]

Land abandonment and the loss of traditional farming practices are thought to control land cover dynamics, and hence the ecosystem service supply in traditionally managed mountain landscapes. We evaluate the impact of land cover changes in Cantabrian Mountains (NW Spain), over 1990-2012, on the potential supply capacity of ecosystem services (regulating, provisioning, and cultural) at both regional and local scales. We also analyze trends in the use of ecosystem services at the local scale. Land cover changes were estimated from CORINE Land Cover database. Patterns of potential ecosystem service supply were assessed by applying an ecosystem service supply capacity matrix and trends in their actual use by using field data. Main trajectories of land cover change encompassed woody vegetation spread in semi-natural open systems and agricultural expansion in the most suitable areas. The capacity of landscape to provide ecosystem services improved during 1990-2012 at both scales. We detected trade-offs between the potential supply of ecosystem services associated to natural systems and those linked to traditional land uses, at both regional and local scales. Changes in the potential supply of ecosystem services matched trends in ecosystem service use. This study could help develop future scenarios to address upcoming challenges in ecosystem service supply. [ABSTRACT FROM AUTHOR]

The European Landscape Convention encourages the inventory and characterization of landscapes for environmental management and planning actions. Among the range of data sources available for landscape classification, remote sensing has substantial applicability, although difficulties might arise when available data are not at the spatial resolution of operational interest. We evaluated the applicability of two remote sensing products informing on land cover (the categorical CORINE map at 30 m resolution and the continuous NDVI spectral index at 1 km resolution) in landscape classification across a range of spatial resolutions (30 m, 90 m, 180 m, 1 km), using the Cantabrian Mountains (NW Spain) as study case. Separate landscape classifications (using topography, urban influence and land cover as inputs) were accomplished, one per each land cover dataset and spatial resolution. Classification accuracy was estimated through confusion matrixes and uncertainty in terms of both membership probability and confusion indices. Regarding landscape classifications based on CORINE, both typology and number of landscape classes varied across spatial resolutions. Classification accuracy increased from 30 m (the original resolution of CORINE) to 90m, decreasing towards coarser resolutions. Uncertainty followed the opposite pattern. In the case of landscape classifications based on NDVI, the identified landscape patterns were geographically structured and showed little sensitivity to changes across spatial resolutions. Only the change from 1 km (the original resolution of NDVI) to 180 m improved classification accuracy. The value of confusion indices increased with resolution. We highlight the need for greater effort in selecting data sources at the suitable spatial resolution, matching regional peculiarities and minimizing error and uncertainty. [ABSTRACT FROM AUTHOR]

Abstract: Knowledge of land cover dynamics and driving forces is a fundamental tool for landscape planning and management. Nevertheless, this understanding is often limited by the paucity of accurate land cover data. In this sense, remote-sensing offers the possibility of acquiring detailed land cover inventories by applying different methods of image classification. However, in heterogeneous and changing landscapes, these data may be insufficient to detect temporal changes (and their causes) because of the uncertainty associated with misclassification and the spatio-temporal variability of change patterns. In this work, we present a multi-temporal uncertainty-based method that incorporates regression models to establish the risk (probability) of land cover change (RLCC), as a function of a set of environmental and socioeconomic driving factors. After filtering out uncertainty for dependent variables (land cover changes), the accuracy of the models increased and regression yielded more parsimonious models that identified the relevant predictors more efficiently. Considering all land cover changes as a whole, drivers relating to the physical environment (i.e., soil properties, accessibility, altitude, slope, solar radiation and rainfall) were more frequently selected than those related to agriculture, society or economy, which may be due to the poor quality of the available socioeconomic data at the municipality level. When analysing changes separately, several differences appeared (e.g. woody vegetation cover was related with fire events and water availability or human management with forest expansion). Our methodological approach has demonstrated that uncertainty plays an important role in model characterisation and identification of potential drivers of change. [Copyright &y& Elsevier]

Abstract: Due to the high sensitivity of mountain landscapes to environmental changes, the study of land cover dynamics has become an essential tool for guiding management policies. Since the second half of the twentieth century, the Cantabrian Mountains (NW Spain) have been substantially altered by the loss of traditional management practices and, more recently, by the new environmental schemes developed by the Regional Government. This area is a biodiversity hotspot, representing the south-western-most distribution limit for a large number of species in Europe. Therefore, small changes in landscape patterns can result in biodiversity losses. In this study, we analyzed land cover changes in the Cantabrian Mountains from 1991 to 2004 by means of remote sensing techniques, identifying the main driving forces and classifying the territory according to its risk of land cover change. Forest expansion and loss of shrublands were the two major trajectories of change apparent during this period. When modeling the occurrence of these land cover changes, we found that performance of models was related to the nature of the change. The most accurate models were associated with processes of secondary succession, i.e. forest expansion (78.6%), while the least accurate models related to changes linked with management decisions, i.e. loss of shrubs (61.8%). The main drivers of change were variations in the number of goats (for the forest expansion model) and changes in the number of head of sheep and cattle (for the loss of shrubs model). Topographic conditions (altitude and slope) were relevant in both models. Our approach proposes an explicit decision support tool for landscape managers, allowing better identification of the areas where they should focus their attention. [Copyright &y& Elsevier]

Severe fires associated to climate change and land cover changes are becoming more frequent in Mediterranean Europe. The influence of environmental drivers on fire severity, especially under different environmental conditions is still not fully understood. In this study we aim to determine the main environmental variables that control fire severity in large fires (>500 ha) occurring in fire-prone ecosystems under two different environmental conditions following a transition (Mediterranean-Oceanic)-Mediterranean climatic gradient within the Iberian Peninsula, and to provide management recommendations to mitigate fire damage. We estimated fire severity as the differenced Normalized Burn Ratio, through images obtained from Landsat 8 OLI. We also examined the relative influence of pre-fire vegetation structure (vegetation composition and configuration), pre-fire weather conditions, fire history and topography on fire severity using Random Forest machine learning algorithms. The results indicated that the severity of fires occurring along the transition (Mediterranean-Oceanic)-Mediterranean climatic gradient was primarily controlled by pre-fire vegetation composition. Nevertheless, the effect of vegetation composition was strongly dependent on interactions with fire recurrence and pre-fire vegetation structural configuration. The relationship between fire severity, weather and topographic predictors was not consistent among fires occurring in the Mediterranean-Oceanic transition and Mediterranean sites. In the Mediterranean-Oceanic transition site, fire severity was determined by weather conditions (i.e., summer cumulative rainfall), rather than being associated to topography, suggesting that the control exerted by topography may be overwhelmed by weather controls. Conversely, results showed that topography only had a major effect on fire severity in the Mediterranean site. The results of this study highlight the need to prioritise fuel treatments aiming at breaking fuel continuity and reducing fuel loads as an effective management strategy to mitigate fire damage in areas of high fire recurrence. • Pre-fire vegetation composition controlled severity across the climatic gradient. • Fire recurrence and pre-fire vegetation configuration also affected fire severity. • The effect of weather on fire severity was dependent on the study site. • Topography affected fire severity only in the Mediterranean site. [ABSTRACT FROM AUTHOR]

Fire-induced changes in vegetation composition due to fire-regime intensification are leading to alterations in ecosystem services that might threaten their future sustainability. Fire recurrence, in particular, could be a key driver shaping ecosystem service resilience in fire-prone ecosystems. This study evaluates the impact of fire recurrence, over twenty-four years, on the potential supply capacity of ten regulating, provisioning, and cultural services selected as critical services by stakeholders and experts. We assessed fire effects in four fire-prone landscapes dominated by species with different functional-traits response to fire (i.e., obligate seeder vs resprouter species). Trends in the potential supply capacity linked to fire recurrence were estimated by applying a supervised classification of Land Use and Land Cover (LULC) classes performed using Landsat imagery, associated to an ecosystem service capacity matrix adapted to the local socio-ecological context. In landscapes dominated by seeders, fire recurrence broke off the potential supply capacity of services traditionally associated to mature forest cover (i.e., the predicted probability of a decrease in the potential supply capacity of climate regulation, timber, wood fuel, mushroom production, tourism, landscape aesthetic, and cultural heritage occurred with high fire recurrence). In landscapes dominated by resprouter species, the effect of fire recurrence was partially buffered in the short-term after fire and no substantial differences in trends of change were found (i.e., equal predicted probability in the potential supply capacity of ecosystem services regardless of fire recurrence). We detected two new opportunities for ecosystems service supply associated to fire recurrence: livestock and honey production, especially in sites dominated by seeders. These findings provide valuable information aiming at recovering post-fire ecosystem service potential supply to partially counterbalance the loss in the socio-ecological system. When the main post-fire restoration goal is preserving ecosystem service resilience in fire-prone ecosystems, establishing management strategies focused on promoting resprouter species could aid mitigating the fire-driven loss of their supply capacity. • Fire recurrence reduced seeder-dominated landscapes' capacity to provide services. • Loss of service supply capacity was buffered in resprouter-dominated landscapes. • Fire recurrence created new services, livestock or honey, in seeder-dominated sites. [ABSTRACT FROM AUTHOR]