Local genetic structure on breeding grounds of a long-distance migrant passerine: the bluethroat (Luscinia svecica) in Spain

Breeding site fidelity can be determined by environmental features, which depending on their heterogeneous distribution may shape the genetic landscape of a population. We used 10 microsatellite loci to study the genetic variation of 83 bluethroats (Luscinia svecica azuricollis) across 14 localities within the Spanish breeding population and assess the relative influence of different habitat characteristics (physiography and vegetation) on genetic differentiation. Based on the genetic variation of this population, we identified 3 geographically consistent genetic clusters that on average showed a higher genetic differentiation than among other north European populations, even those belonging to different subspecies. The inferred genetic clusters occurred in geographic areas that significantly differed in elevation. The highest genetic differentiation was observed between sites at different mountain ranges, as well as between the highest altitude sites in the northeastern locale, whereas vegetation type did not explain a significant percentage of genetic variation. The lack of correlation between geographic and genetic distances suggests that this pattern of genetic structure cannot be explained as a consequence of isolation by distance. Finally, we discuss the importance of preserving areas encompassing high environmental and genetic variation as a means of preserving evolutionary processes and adaptive potential.University of León (2009/00131/00); CSIC/MICINN Proyecto Intramural Especial-PIE (201030I019).Peer Reviewe

Evolutionary divergences in Luscinia svecica subspecies complex – new evidence supporting the uniqueness of the Iberian bluethroat breeding populations

P. 141-149The assessment of evolutionary divergences within subspecies complexes provide an effective short-cut for estimating intraspecific genetic diversity, which is relevant for conservation actions.We explore new evidence supplementing the existing knowledge about the singularity of Iberian bluethroats within the Luscinia svecica subspecies mosaic.We compared biometric traits of Iberian males (L. s. azuricollis) to the closest subspecies (L. s. cyanecula, L. s. namnetum and L. s. magna) using general linear models and analysed the correlations between biometric and genetic differentiation (based on nuclear microsatellites) among the target subspecieswith aMantel test. Biometric differenceswere calculated using 63 museum skins and 63 live specimens. Genetic distances were estimated in a sample of 136 individuals. An additional characterisation of the plumage of Iberian males was shaped from 22 live specimens. We highlight the distinctiveness of Iberian birds within the subspecies mosaic since L. s. azuricollis had longer wings than L. s. cyanecula and L. s. namnetum, but shorterwings than L. s. magna. Indeed, L. s. azuricollis had longer tarsus and bill than L. s. namnetum, but shorter bill than L. s. magna. Biometric divergence was not significantly associated with genetic distance. Iberian males showed an all-blue plastron in 77% of specimens, a mostly non-marked black band and no white band, which distinguished them from males of L. s. cyanecula and L. s. namnetum. We conclude the importance of considering phenotypic and genotypic differences at subspecies level, which is essential for designing realistic conservation strategies addressed to preserve species genetic diversity patterns. 1. Introduction The presence of endangered species is currently one of the main principles for establishing priorities of conservationS

Modeling Pinus pinaster forest structure after a large wildfire using remote sensing data at high spatial resolution

P. 257-271In the Mediterranean Basin, wildland fires are major drivers of forest ecosystem dynamics. In the current context of global change, these fires are becoming more severe and recurrent because of climatic conditions, land use changes and invasive species. In areas affected by mega-fires (burned area > 10,000 ha), the patterns of regeneration may be heterogeneous due to local variations in fire regime, community composition and environmental features. The goal of this study was to analyze the post-fire structure of both Pinus pinaster Aiton. seedlings population and understory community in a Mediterranean fire-prone ecosystem at short-term by means of high spatial resolution satellite imagery within the perimeter of a full stand replacing mega-fire that burned around 12,000 ha of a Pinus pinaster forest in NW Spain. We established 234 field plots of 2 × 2 meters to cover four recurrence-severity scenarios. In each plot, we sampled 15 vegetation structural variables at both pine seedlings population and understory community levels. From the WorldView-2 satellite imagery, we obtained three sets of spectral variables (reflectance, spectral indices and image textures) that were used as predictors of vegetation recovery in generalized linear models. At population level, the number and cover of pine seedlings were successfully modeled with spectral indices and textural information (normalized root mean square error of 16% and 17%, respectively). At understory community level, woody species cover was correlated with first order textures (normalized root mean square error of 9%). Other understory structure variables (height and richness of woody species, percentage of bare soil, necromass and leaves) were predicted with an error lower than 20%. The predictive capacity of the models was similar for all recurrence-severity scenarios. Our results highlight the usefulness of spectral indices and textural data at high spatial resolution in the analysis of post-fire recovery in large and heterogeneous burnt areas. Given the accuracy and predictive capacity of the models obtained in this study, high spatial resolution satellite imagery together with field data provide useful information in post-fire decision making in fire prone ecosystems.S

Effects of wildfires on environmental variability: a comparative analysis using different spectral indices, patch metrics and thematic resolutions

P. 697-710Knowledge on environmental variability and how it is affected by disturbances is crucial for understanding patterns of biodiversity and determining adequate conservation strategies. The aim of this study is to assess environmental variability in patches undergoing post-fire vegetation recovery, identifying trends of change and their relevant drivers. We particularly evaluate: the value of three spectral indices derived from Landsat satellite data [Normalized Burn Ratio (NBR), Normalized Difference Vegetation Index (NDVI) and Wetness Component of the Tasseled Cap Transformation (TCW)] for describing secondary succession; the effectiveness of three metrics (diversity, evenness and richness) as indicators of patch variability; and how thematic resolution can affect the perception of environmental variability patterns. While the system was previously characterised as highly resilient from estimations of vegetation cover, here we noted that more time is required to fully recover pre-fire environmental variability. Using mean diversity as indicator of patch variability, we found similar patterns of temporal change for the three spectral indices (NBR, NDVI and TCW). Analogous conclusions could be drawn for richness and evenness. Patch variability, measured as diversity, showed consistent patterns across thematic resolutions, although values increased with the number of spectral classes. However, when the variance of diversity was plotted against thematic resolution, different scale dependencies were detected for those three spectral indices, yielding a dissimilar perception of patch variability. In general terms, NDVI was the best performing spectral index to assess patterns of vegetation recovery, while TCW was the worst. Finally, burned patches were classified into three classes with similar trends of change in environmental variability, which were strongly related to fire severity, elevation and vegetation type.S

Radar and multispectral remote sensing data accurately estimate vegetation vertical structure diversity as a fire resilience indicator

The structural complexity of plant communities contributes to maintaining the ecosystem functioning in fire-prone landscapes and plays a crucial role in driving ecological resilience to fire. The objective of this study was to evaluate the resilience to fire off several plant communities with reference to the temporal evolution of their vertical structural diversity (VSD) estimated from the data fusion of C-band synthetic aperture radar (SAR) backscatter (Sentinel-1) and multispectral remote sensing reflectance (Sentinel-2) in a burned landscape of the western Mediterranean Basin. We estimated VSD in the field 1 and 2 years after fire using Shannon’s index as a measure of vertical heterogeneity in vegetation structure from the vegetation cover in several strata, both in burned and unburned control plots. Random forest (RF) was used to model VSD in the control (analogous to prefire scenario) and burned plots (1 year after fire) using as predictors (i) Sentinel-1 VV and VH backscatter coefficients and (ii) surface reflectance of Sentinel-2 bands. The transferability of the RF model from 1 to 2 years after wildfire was also evaluated. We generated VSD prediction maps across the study site for the prefire scenario and 1 to 4 years postfire. RF models accurately explained VSD in unburned control plots (R2 = 87.68; RMSE = 0.16) and burned plots 1 year after fire (R2 = 80.48; RMSE = 0.13). RF model transferability only involved a reduction in the VSD predictive capacity from 0.13 to 0.20 in terms of RMSE. The VSD of each plant community 4 years after the fire disturbance was significantly lower than in the prefire scenario. Plant communities dominated by resprouter species featured significantly higher VSD recovery values than communities dominated by facultative or obligate seeders. Our results support the applicability of SAR and multispectral data fusion for monitoring VSD as a generalizable resilience indicator in fire-prone landscapes.SIEuropean Regional Development Fund (ERDF)Spanish Ministry of Economy and CompetitivenessRegional Government of Castilla and LeónBritish Ecological Societ

Local genetic structure on breeding grounds of a longdistance migrant passerine: the bluethroat (Luscinia svecica) in Spain

P. 36-46Breeding site fidelity can be determined by environmental features, which depending on their heterogeneous distribution may shape the genetic landscape of a population. We used 10 microsatellite loci to study the genetic variation of 83 bluethroats (Luscinia svecica azuricollis) across 14 localities within the Spanish breeding population and assess the relative influence of different habitat characteristics (physiography and vegetation) on genetic differentiation. Based on the genetic variation of this population, we identified 3 geographically consistent genetic clusters that on average showed a higher genetic differentiation than among other north European populations, even those belonging to different subspecies. The inferred genetic clusters occurred in geographic areas that significantly differed in elevation. The highest genetic differentiation was observed between sites at different mountain ranges, as well as between the highest altitude sites in the northeastern locale, whereas vegetation type did not explain a significant percentage of genetic variation. The lack of correlation between geographic and genetic distances suggests that this pattern of genetic structure cannot be explained as a consequence of isolation by distance. Finally, we discuss the importance of preserving areas encompassing high environmental and genetic variation as a means of preserving evolutionary processes and adaptive potentia

From general research questions to specific answers: Underspecificity as a source of uncertainty in biological conservation

P. 167-180Species distribution modelling may support ecologists in conservation decision-making. However, the applicability of management recommendations depends on the uncertainty associated to the modelling process. A key source of uncertainty is the underspecificity of the research question. Modelling specific questions is straightforward since they drive clearly the methodological choices about input data and model building. Nevertheless, when the research questions remain underspecific, modellers must choose among a wide spectrum of choices, with each decision sequence driving to a different outcome that explain partially the target question. We show how the underspecificity associated to a general research question about Great Bustard breeding success at geographic scale drives to multiple decision choices, leads to a variety of model outcomes and hampers the identification of specific conservation actions. We ran generalised linear models using multi-model inference on a set of databases built according to specific sequences of methodological choices. Then, we evaluated variations in model performance, complexity (parsimony) and nature of predictors, as well as averaged model predictions and spatial congruence among model outputs. Deviance and parsimony varied widely (11.46% to 83.33% and 7 to 18, respectively), as did model averaged mean predictions in occupied areas, contributing predictors and spatial congruence among outputs (rPearson = 0.44 ± 0.23 for models calibrated in occupied areas; 0.48 ± 0.06 for models calibrated in potential/accessible areas). We recommend to carefully fix research questions and associated methodological options through collaborative working frameworks to conceptualize modelling approaches and, thus, to mitigate problems arising from underspecificity and other forms of uncertainty in conservation applications.S

Linking species functional traits of terrestrial vertebrates and environmental filters: A case study in temperate mountain systems

P. 1-15Knowledge 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.S

Using Unmanned Aerial Vehicles in Postfire Vegetation Survey Campaigns through Large and Heterogeneous Areas: Opportunities and Challenges

17 p.This study evaluated the opportunities and challenges of using drones to obtain multispectral orthomosaics at ultra-high resolution that could be useful for monitoring large and heterogeneous burned areas. We conducted a survey using an octocopter equipped with a Parrot SEQUOIA multispectral camera in a 3000 ha framework located within the perimeter of a megafire in Spain. We assessed the quality of both the camera raw imagery and the multispectral orthomosaic obtained, as well as the required processing capability. Additionally, we compared the spatial information provided by the drone orthomosaic at ultra-high spatial resolution with another image provided by theWorldView-2 satellite at high spatial resolution. The drone raw imagery presented some anomalies, such as horizontal banding noise and non-homogeneous radiometry. Camera locations showed a lack of synchrony of the single frequency GPS receiver. The georeferencing process based on ground control points achieved an error lower than 30 cm in X-Y and lower than 55 cm in Z. The drone orthomosaic provided more information in terms of spatial variability in heterogeneous burned areas in comparison with theWorldView-2 satellite imagery. The drone orthomosaic could constitute a viable alternative for the evaluation of post-fire vegetation regeneration in large and heterogeneous burned areasS

Landscape heterogeneity as a surrogate of biodiversity in mountain systems: what is the most appropriate spatial analytical unit?

P. 285-294The estimated potential of landscape metrics as a surrogate for biodiversity is strongly dependent on the spatial analytical unit used for evaluation. We assessed the relationship between terrestrial vertebrate species richness (total and taxonomic) and structural landscape heterogeneity, testing the impact of using different spatial analytical units in three mountain systems in Spain. Landscape heterogeneity was quantified through an additive partitioning of the Shannon diversity index of landscape classes. Both landscape heterogeneity and species richness were calculated using two spatial analytical unit approaches: eco-geographic vs. arbitrary (i.e., watersheds vs. square windows of different sizes 20 × 20 km, 50 × 50 km, 100 × 100 km). We predicted species richness on the basis of landscape heterogeneity by fitting separate linear models for each spatial analytical unit approach. The main results obtained showed that landscape heterogeneity influenced terrestrial vertebrate species richness. However, the emerging relationships were dependent on the spatial analytical unit approach. The eco-geographic approach showed significant relationships between landscape heterogeneity and total and taxonomic species richness in almost all cases (except mammals). Considering the arbitrary approach, landscape heterogeneity appeared as a predictor of species richness only for mammals and breeding birds and at the coarsest spatial scales. Our results claim for further consideration of eco-geographical spatial analytical unit approaches in biodiversity studies and show that the methods of this study offer a valuable cost-effective framework for biodiversity management and spatial modeling, with potential to be adapted to national and global applications.S