Susana Suárez-Seoane

Responses of birds of different biogeographic origins and habitat requirements to agricultural land abandonment in northern Spain

Abstract Agricultural land-use changes in Europe have taken two opposing directions: towards agricultural intensification or land abandonment. While in the Mediterranean region land abandonment is a main cause of avian diversity decline, in northern Europe species diversity often increases with successional age. We examined the hypothesis that the biogeographic origin of the avifauna determines whether abandonment brings conservation benefits or detriment by studying the bird community of agricultural land in northern Spain, at the boundary of the Mediterranean and Eurosiberian regions. Using a successional gradient, we examined landscape-scale effects of agricultural abandonment on birds during the breeding and non-breeding seasons. The trend in avian diversity with successional stage differed little between Mediterranean and Eurosiberian species in winter. In the spring, however, there was an increase in diversity with stage in abandonment for Eurosiberian birds but not for Mediterranean species. Analysis of individual species showed a preference among Eurosiberian birds for more wooded habitats whereas Mediterranean birds preferred open areas and shrubland. The introduction of agricultural policies to geo-political units that do not coincide with eco-regions cannot be assumed to bring uniform conservation benefits. In the Mediterranean region, agricultural mosaics of low intensity cultivation maintain the highest diversity of priority bird species. Agricultural land abandonment should not be assumed to benefit conservation.

Should data be partitioned spatially before building large-scale distribution models?

There is growing interest in building predictive models of species distributions over large geographic areas. As larger areas are modelled, however, it is highly likely that heterogeneity in the predictors variable increases and that areas are included where animals respond to habitats in different ways, for example, due to social status. These effects (spatial non-stationary) may weaken model performance. This paper explores whether data partitioning prior to analysis can improve the tit of models and provide ecological insight into distribution patterns. Data on three bird species were modelled for the whole of Spain at 1 km(2) resolution using logistic regression analysis. Data were partitioned into geographic quarters, concentric rings around the centroid of the distribution, and into random samples for comparison. In all cases, data partitioning produced better models as assessed by Receiver Operating Characteristic curve (AUC) statistics than analysis of the global data set. Inclusion of latitude and longitude improved the global models only when added as smoothed splines but produced different probabilities to the partitioned data. Geographic partitioning is a very crude local modelling approach and we suggest that some form of geographically-weighted regression could offer the best solution to large-scale modelling but is computationally intensive on Geographical Information Systems (GIs) data. It is concluded that simple partitioning by geographic quarters may detect spatial non-stationary and alert the modeller to possible problems; that partitioning into more novel arrangements may be used to test ecological hypotheses; and that data should not be partitioned spatially to build and test models if non-stationary is suspected.

Uncertainty analysis as a tool for refining land dynamics modelling on changing landscapes: a case study in a Spanish Natural Park

In this study we developed a methodology aimed at improving the assessment of inter-annual land cover dynamics from hard classified remotely sensed data in heterogeneous and resilient landscapes. The methodology is implemented for the Spanish Natural Park of Sierra de Ancares, where human interference during the last century has resulted in the destruction and fragmentation of the original land cover. We ran supervised classifications, with a maximum likelihood algorithm (Maxlike), on a temporal series of Landsat images (1991–2005), followed by an uncertainty assessment using fuzzy classifications and confusion indices (CIs). This allowed us to show how much (and where) of the resulting maps contained a substantial amount of error, distinguishing data that might be useful to measure land change from data that are not particularly useful when applying a post-classification comparison methodology. In this way, we can detect true changes not skewed by the effects of uncertainty. Even if patterns of change were always coherent amongst years, they were more realistic after reducing uncertainty, in spite of a substantial decrease in the number of available pixels (i.e. unmasked by the method). We then computed land cover dynamics by means of a model specifically designed to determine the frequency of disturbances (mainly fire events) and the vegetation recovery time during the study period. Model outputs showed correlated landscape patterns at a broad scale and provided useful results to explore land cover change from pattern to process.

Temporal Changes in Socio-Ecological Systems and Their Impact on Ecosystem Services at Different Governance Scales: A Case Study of Heathlands

Heathlands are considered biodiversity hotspots of high conservation interest. However, they are at risk of degradation and disappearance in most parts of Europe mainly due to land abandonment, degradation, and conversion to other land uses. Heathlands are semi-natural systems: their maintenance and survival depends on specific practices such as extensive grazing or burning. Traditionally they provide a wide range of goods and services to societies. In this study we used the ecosystem services (ES) framework to analyze the changes in the demand for and delivery of ES for the heathland landscapes of the Cantabrian Mountains (NW Spain), since the 1950s. Particularly, we analyzed how the social changes since the 1950s have determined changes in stakeholders’ demand for provisioning, cultural and regulating services and how these changes have influenced the vegetation dynamics and conservation status of these systems. We identified a general shift from the provisioning of grazing facilities and local products for the local-regional market to the provisioning of conservation services to satisfy national–international demand. For the present situation we found a clear mismatch between the conservation demand, management practices, and land-use forms. This mismatch threatens to lead to further landscape changes and loss of biodiversity. The results of our multi-scale and -services study can help to increase awareness of the value of currently obtainable benefits from heathlands among stakeholders and managers. The ES approach can improve understanding of the functioning of the socio-ecological heathland system, and inform the development of new management strategies for heathland protection.

Influence of land use and climate on recent forest expansion: a case study in the Eurosiberian–Mediterranean limit of north-west Spain

1.In Mediterranean mountainous areas, forests have expanded in recent decades because traditional management practices have been abandoned or reduced. However, understanding the ecological mechanisms behind landscape change is a complex undertaking because the influence of land use may be reinforced or constrained by abiotic factors such as climate. In this work, we evaluated their combined effects on recent forest expansion across climatic, topographic and management gradients. 2.We used orthorectified aerial photographs from the second half of the twentieth century (1956, 1974, 1983, 1990 and 2004) to monitor changes in forest distribution in a set of 20 head-water basins in the Cantabrian Mountains of north-west Spain, at the Eurosiberian–Mediterranean limit. In particular, we evaluated the role of land-use history (comparing natural vs. anthropic basins) and microclimate (comparing shaded vs. sunny aspects) of forest gain/loss rates and spatial distribution shifts. Finally, we applied Species Distribution Modelling techniques (MaxEnt and BIOMOD) in the stated scenarios of land-use history and microclimate, to assess habitat suitability for forest expansion on the basis of topography, soil properties and mesoclimatic variables. 3.Forest cover increased from 10.72% in 1956 to 27.67% in 2004 in the area. The rate of expansion was significantly higher in natural basins and, particularly, on shaded slopes. In all cases, the mean elevation of new forest patches increased during the study period, which was particularly evident on natural sunny slopes. The performance of the models and the magnitude of the effects varied across land-use histories and microclimatic conditions. Soil properties and temperature and precipitation in late spring and early summer were the main drivers of forest expansion in modelling exercises, although expansion rates and upward altitudinal shifts were primarily controlled by land-use history and the biogeographic origin of the forests. 4.Synthesis. The combination of monitoring and modelling techniques used in this work contributed to the understanding of forest expansion in cultural systems, indicating that ecological succession is not a homogeneous process, but varies spatially due to human and abiotic constraints since historical times.

Linking habitat quality with genetic diversity: a lesson from great bustards in Spain

The effects of habitat loss and fragmentation on the genetic structure and variability of wild populations have received wide empirical support and theoretical formalization. By contrast, the effects of habitat quality seem largely underinvestigated, partly due to technical difficulties in properly assessing habitat quality. In this study, we combine geographic information system (GIS)-based habitat-quality modelling with a landscape genetics approach based on mitochondrial DNA markers to evaluate the possible influence of habitat quality on the levels and distribution of genetic diversity in a range of natural populations (n = 15) of Otis tarda throughout Spain. Ninety-three percent of the population represented by our countrywide sample lives in good-quality habitats, while 4.5% and 2.5% occur respectively in intermediate and poor habitats. Habitat quality was highly correlated with patch size, population size and population density, indicating the reliability and predictive power of the habitat suitability model. Genetic diversity was significantly correlated with habitat quality, size and density of the population, but not with patch size. Three of a total of 20 existing matrilineages from the species’ current genetic pool are restricted to poor-quality habitats. This study therefore highlights the importance of considering both population genetics and habitat quality in a species of high conservation priority.

Does fire regime affect both temporal patterns and drivers of vegetation recovery in a resilient Mediterranean landscape? A remote sensing approach at two observation levels

We investigate how fire regime may influence both temporal patterns and drivers of vegetation regeneration in a Natural Park (NW Spain) affected by a long history of fire events and human activities. To address this issue, we evaluate the suitability of five spectral indices derived from Landsat imagery (for the period 1992–2005) for estimating biophysical properties of vegetation and monitoring post-fire recovery. Complementarily, we assess the role of the observation level (pixel and patch) on the results, identifying which of them is more informative for land management. Tasselled Cap Wetness was the best-performing index and total cover was the vegetation property more closely related to spectral data. Most post-fire recovery occurred within the 2 years following the fire event. Fire recurrence did not influence patch extent or shape nor did it affect ecosystem resilience. However, patch extent and shape affected resilience. The relevance of the environmental drivers behind vegetation recovery was not related to fire recurrence and changed over time. Prior vegetation status and rainfall were the most important drivers, while topography and vegetation type had a more secondary role. Our results advocate the consideration of patches as the most appropriate organisational unit when monitoring vegetation recovery.

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

Knowledge 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.

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.

Can Iberian Water Rail Rallus aquaticus be sexed reliably using simple morphometrics

In this paper we classified the sex of 39 Iberian Water Rails Rallus aquaticus using external morphometric measurements and genetic analysis. Logistic regression and classification tree model techniques (CART) were used to test whether simple morphometric measurements alone could classify sex correctly. For most of these measurements the overlap between sexes was too great to be of value. Bill length was the most relevant variable according to all the statistical analyses for the population under study. The applied combination of statistical techniques on biometric and genetic data correctly classify 80% of individuals. However, in view of the apparent variability in morphometric characteristics between populations, morphometric techniques to sex individuals from other populations should be validated using other criteria.