Landscape Structure Variables Research Articles

Do reptile responses to habitat structure and time since fire depend on landscape structure?

Land use changes, such as the development of agriculture and plantation forestry, and altered fire regimes, are major drivers of biodiversity loss worldwide, influencing the availability of suitable habitat for species. Reptiles are sensitive to both these processes as they are influenced by native vegetation extent and habitat structure. While much is known about the independent effects of fire and land use change on species distributions, few studies have investigated potential interactive effects; specifically, whether the influence of site-scale variables on reptiles depends on the properties of the surrounding landscape. We sampled reptiles at 107 sites in fire-prone heathy woodland, interspersed with plantation forestry and agriculture in south-west Victoria, Australia. We investigated the responses of seven reptile species to both site-scale variables (time since fire and several measures of habitat structure) and landscape-scale variables (extent of native vegetation and plantations and the presence of pasture within a 3.14 square km area) to 1) identify whether species’ responses to fire and habitat depended on landscape structure, and 2) examine the relative influence of time since fire, habitat structure and landscape structure on reptile abundance. We predicted that responses to site-scale variables would vary with a key landscape structure variable: the amount of native vegetation cover. Further, we predicted that site-scale variables would be stronger predictors of species abundance than landscape-scale variables. Generalised linear models, accounting for imperfect detection, were used to estimate species responses to site and landscape-scale predictors. For two species (Amphibolurus muricatus and Liopholis whitii) there was evidence that their responses to site-scale variables depended on landscape structure. However, contrary to our first prediction, native vegetation cover was not the only landscape structure variable that influenced species’ responses to site-scale variables. Three species (Acritoscincus duperreyi, A. muricatus, and Lerista bougainvillii) responded to both habitat structure and landscape structure variables, though the relative influence of the variables at the different scales was varied among the species. One species (Lampropholis guichenoti) responded to fire and habitat structure variables at the site-scale but did not respond to landscape structure. One species (Aprasia striolata) responded to landscape structure variables but not to site-scale variables. Our second prediction, that site-scale variables would be the strongest predictors of abundance, was true for two species, but overall, our results were varied, with species responding at both scales. Examining species' responses to drivers at multiple spatial scales is essential for conservation management, as even species with low dispersal capacity such as reptiles can respond to processes occurring at large spatial scales.

Assessing the “Scale of Effect”: The Impact of Multi-Scale Landscape Characteristics on Urban Bird Species Taxonomic and Functional Diversity

The influence of landscape structure on species communities is intimately connected to the spatial scales at which measurements are made. If we do not measure landscape structure at its most impactful scale, otherwise known as the “scale of effect”, we might fail to detect crucial community–landscape relationships. In our study, we focused on the “scale of effect” as it pertains to the relationship between urban bird diversity and landscape structure. We investigated eight types of landscape structure variables alongside elevation attributes across 16 spatial scales around 28 sampling sites in Kunming, Yunnan Province, China. Our objective was to identify the most influential scale at which the environmental variables under investigation affect the taxonomic and functional diversity of bird species. We utilized PLSR and VIP scores to overcome challenges posed by multicollinearity among predictors. We found that the influence of landscape characteristics on bird species richness and functional dispersion index (FDis) was scale-dependent. Notably, the influence of the area of open water on FDis is most pronounced at smaller scales, while at larger scales, open water dispersion becomes more essential. Additionally, in a highly fragmented urban matrix, the importance of forest connectivity may exceed that of patch size at medium scales. However, the significance of forest coverage increases with scale, which underscores the importance of preservation efforts at larger scales to prevent forest fragmentation. We also noted a considerable impact from landscape-level subdivision across almost all scales. These findings highlight the importance of shifting urban conservation planning towards a multi-scale approach, which would allow for the identification of priority intervention scales.

Landscape structure influences grassland productivity through plant functional diversity

Agriculture intensification led to the gradual destruction of semi-natural habitats and landscape simplification in the North-Western Europe. All these profound changes affected plant assemblages, especially in semi-natural ecosystems such as grasslands. They could have negative effects on the plant diversity and the related ecosystem functions, such as primary productivity. At the landscape scale this biodiversity-productivity relationship still have to be tested in real-world systems. It could have important economic implications concerning fodder production. We used a large-scale sampling design (30 landscape windows – 1 ×1 km) to quantify landscape structure variables (semi-natural habitat amounts and landscape heterogeneity), grassland plant taxonomic diversity and functional diversity calculated from multidimensional functional spaces (functional richness, evenness, dispersion), and grassland productivity (mean, temporal stability, spatial variability) derived from satellite image time-series. Taxonomic dissimilarity, functional evenness and functional dispersion of grassland plant assemblages were related to semi-natural habitat amount. Functional evenness and dispersion decreased with grassland amount whereas taxonomic dissimilarity and functional evenness increased with hedgerow amount. Only taxonomic and functional richness depended on landscape heterogeneity, and with a positive relationship. Grassland plant assemblages with a higher functional evenness presented a higher and more stable mean productivity. In addition to the direct effect of landscape heterogeneity on plant productivity, we demonstrated plant trait-mediated effect of landscape structure on mean and temporal stability of grassland productivity at the landscape scale. Landscape management, especially through the conservation of hedgerows can help maintain high and resilient production of fodder in the future as a result of their positive effects on plant functional diversity.

Vegetation cover and configuration drive reptile species distributions in a fragmented landscape

Context Habitat loss and fragmentation are key drivers of biodiversity loss worldwide, yet the influence of landscape structure on species distributions is unknown. Globally, reptiles are thought to be especially sensitive to landscape modification due to their limited capacity for dispersal and reliance on native vegetation. New knowledge of how landscape structure influences species distributions is needed to inform conservation strategies. Aims Our principal aim was to examine the influence of landscape structure on the distributions of 40 terrestrial reptile species in Victoria, southeast Australia. Methods We obtained species occurrence records from the Victorian Biodiversity Atlas, and used MaxEnt to model the distributions of reptile species within Victoria using biophysical and landscape structure variables. A moving window analysis was applied to a land cover map to derive five landscape structure metrics; two metrics represented landscape cover and three represented landscape configuration. Key results Climate variables were generally found to be the strongest drivers of species distributions, although 80% of reptile species were also influenced by landscape structure (permutation importance ≥5%). Of the five landscape structure variables, extent of native vegetation had the greatest influence (30 of 40 species), followed by habitat shape. For Lerista bougainvillii and Tiliqua rugosa, native vegetation cover had a greater influence on their distributions than climate variables. Most species responded positively to native vegetation extent, whereas responses to other landscape structure variables were varied. Conclusions Although most studies of reptile distributions only use biophysical variables in modelling, our research shows that at the scale of our study area, reptile species distributions were also influenced by landscape structure; extent of native vegetation was an important predictor for most species. Integrating landscape structure in modelling has the potential to improve our ability to predict species distributions. Implications Because species distributions are likely to shift due to climate change, knowledge of the influence of landscape structure on distributions will help land managers to facilitate successful range expansions in fragmented landscapes. Our findings indicate that management focused on increasing the extent of native vegetation is likely to provide benefit to most reptile species.

Landscape structure and local variables affect plant community diversity and structure in a Brazilian agricultural landscape

AbstractThe biodiversity in agricultural landscapes depends on land‐use types, natural elements, and farming intensity. The Brazilian Cerrado is a biodiversity hotspot, however, the native vegetation loss rates have increased in the last years, leading several plant species to extinction risk. Here, we analyze the effects of local (soil fertility and litter amount) and landscape variables (patch shape, habitat amount, compositional heterogeneity, matrix dominance and connectivity) on alpha species richness and diversity, and basal area of different Cerrado vegetation types (savanna, forested savanna, and forest) using linear models and Akaike information criterion. We calculated landscape metrics at different spatial scales for 49 sampling sites in intensive farming landscapes. Woody plant diversity and richness were positively related to soil fertility and landscape compositional heterogeneity at 1500 m spatial scale. Plant richness was negatively related to the patch shape of remnants at 1000 m spatial scale. The effects of litter amount to explain the basal area varied between vegetation types. We found a positive effect in savanna and forested savanna and a negative effect in forest areas. Our findings suggest that the increase of monocultures lead to a decline on plant diversity in the studied landscapes. Also, local variables and the diversity of vegetation types need to be considered to design restoration actions in Cerrado. Sustainable intensification and biodiversity‐friendly production systems may be alternatives to increase compositional heterogeneity, thus favoring plant diversity in Cerrado farming landscapes.Abstract in Portuguese is available with online material.

Spatio-temporal changes in habitat quality and linkage with landscape characteristics in the Beressa watershed, Blue Nile basin of Ethiopian highlands

An increase in human population generally exerts pressure on natural habitats and leads to a decline in biodiversity resources. As a proxy for biodiversity study, an evaluation of habitat quality (HQ) change caused by land use/land cover (LULC) and associated landscape structural changes may provide a scientific basis for ecological protection and landscape management. This study analyzed spatio-temporal changes in HQ over the last four decades and predicted the trends over the next three decades. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model was employed to evaluate the state of HQ. Criteria of habitat naturalness, habitat complexity and a soil degradation index were used to classify habitat types. Results showed that, between 1972 and 2017, areas with high HQ indicators declined by about 20% while areas with poor HQ increased by 11%. An unprecedented expansion of anthropogenic LULC changes related to the growth of human settlements and artificial plantations and a decline in natural and semi-natural habitats resulted in the total loss of HQ by about 35%. The mean value of HQ decreased from 0.60 to 0.45 during the study period. The distribution of moderate levels of HQ, primarily in farmlands, remained essentially unchanged. Predicted HQ values are expected to follow a similar trend to past decades with 41.5% of the areas continuing to decline, although with a slight HQ improvement in some areas. The spatial distribution of HQ is negatively correlated with habitat degradation (R2 = 0.95 at p < 0.01) and slope (R2 = 0.84 at p < 0.05). HQ change also appears more strongly influenced by landscape composition than by configuration in the watershed. The most important landscape structure variables accounted for HQ change were LPI, PLAND and MPS of anthropogenic habitats, suggesting reducing habitat modifications and restoring degraded natural habitats is crucial to maintain biodiversity in the study area.

The influence of landscape composition and configuration on crop yield resilience

Abstract Sustainable agriculture aims to produce sufficient food while minimizing environmental damage. To achieve this, we need to understand the role of agricultural landscapes in providing diverse ecosystem services and how these affect crop production and resilience, that is, maintaining yields despite environmental perturbation. We used 10 years of English wheat yield data to derive three metrics of resilience (relative yield across the time series, yield stability around a moving average and resistance to an extreme weather event) at 10 km × 10 km resolution. We used remotely sensed maps to calculate measures of landscape structure, including composition (proportions of different land cover types) and configuration (metrics of connectivity and proximity), known to affect ecosystem service delivery (e.g. control of pests by beneficial invertebrates). We then used an information‐theoretic approach to identify the best‐fitting combination of landscape structure predictors for each resilience metric, using a potential yield model to account for the effects of climate and soils. Relative yield showed a strongly positive relationship with the area of arable land. For yield stability, this relationship was evident but alongside other landscape structure variables in the best‐fitting model. No relationship with arable land was evident for resistance. Yield stability showed a strongly positive effect of proximity to semi‐natural habitats. For resistance, the best‐fitting model included positive relationships with the cover of semi‐natural habitats and proximity to semi‐natural grasslands. Synthesis and applications. Landscapes with the highest relative wheat yields did not show the highest yield stability or resistance to extreme events. As resilience metrics were derived from shorter portions of the time series, the importance of semi‐natural habitats compared to arable land increased. This is probably driven by the complex interplay between landscape structure, agricultural management and ecosystem services. These results demonstrate that measuring relative yield over time may be insufficient to capture the full effect that non‐arable components of the landscape, and the ecosystem services they deliver, have on other aspects of resilience, and that there are clear trade‐offs in managing agricultural landscapes to maximize different aspects of crop yield resilience.

Plant functional connectivity of Nymphoides fallax in geographically isolated temporary wetlands in Mexican highlands

Plant functional connectivity integrates species-environment interactions, dispersal vectors, and landscape structure variables to understand species’ spatial responses to habitat fragmentation. Functional connectivity is still poorly understood for aquatic plants despite the promise it holds for informing wetland conservation across landscapes. Through a landscape genetics approach, we quantified plant functional connectivity among geographically isolated wetlands by genotyping seven nuclear microsatellite loci in 18 populations of Nymphoides fallax, a tetraploid aquatic plant endemic to Mexican and Guatemalan highland wetlands. We tested if wetland connectivity, quantified with three connectivity indices, translated to high genetic diversity within populations and if geographical distance per se explained gene flow among wetlands. We also tested if landscape features such as vegetation and surface water cover explained gene flow among N. fallax populations. Our results show that wetland connectivity is positively associated with genetic diversity over threshold distances up to 5 km. The Si Hanski connectivity index, with wetland area incorporated, was the best predictor explaining the effective number of alleles, allelic richness, and expected heterozygosity. Population-specific FST, as a proxy for gene flow, was better explained by a model including forest cover than by geographical distance or water cover. Our findings highlight the importance of forest conservation to maintain gene flow at the landscape scale for N. fallax and allows the detection of key populations to maintain genetic diversity and connectivity. Understanding wetland connectivity is critical to address wetland loss in human-impacted landscapes.

Changes in landscape composition influence the abundance of insects on maize: The role of fruit orchards and alfalfa crops

The traditional agricultural landscape of Ebro Basin (NE Spain), which is mainly composed of alfalfa and cereal crops, has undergone changes in recent years, mainly consisting of an increase in the area occupied by intensively managed irrigated orchards. Recently, it has been reported that the presence of a higher proportion of orchards in the landscape and their management negatively affect the abundance and diversity of natural enemies. Two hypotheses are tested in this study: (1) the increased orchard surface has led to a reduction in natural enemies in neighbouring maize crops, and (2) the higher alfalfa proportion of agricultural land enhances the predatory fauna on maize. Maize fields were selected across a landscape gradient created by orchards and field crops (alfalfa and maize) in a buffer of 500 m. The abundance of 17 insect taxa in each maize field was estimated by means of 3 yellow sticky traps per season over three years. The insect abundance was related to the landscape structure (proportions of landscape elements and landscape diversity) and local variables (maize phenology, perimeter/area, weed diversity of the maize edges and abundance of the potential predators or potential prey). Our results show that the proportion of orchards in the landscape had negative effects on the main predators, and alfalfa had positive effects on herbivores and their predators. Semi-natural habitats (non-crop habitats and forest) and landscape diversity had low effects on insect abundance. However, variables at the local level included more significant effects than landscape structure; maize growth stages and abundance of potential prey or predators on the crop were the most influential variables at a local level. Here we show the interplay between different land uses types and local management and their impact on natural enemies and herbivores in maize crops in the Mediterranean area.

Identification of fine scale and landscape scale drivers of urban aboveground carbon stocks using high-resolution modeling and mapping

Urban areas are sources of land use change and CO2 emissions that contribute to global climate change. Despite this, assessments of urban vegetation carbon stocks often fail to identify important landscape-scale drivers of variation in urban carbon, especially the potential effects of landscape structure variables at different spatial scales. We combined field measurements with Light Detection And Ranging (LiDAR) data to build high-resolution models of woody plant aboveground carbon across the urban portion of Brisbane, Australia, and then identified landscape scale drivers of these carbon stocks. First, we used LiDAR data to quantify the extent and vertical structure of vegetation across the city at high resolution (5×5m). Next, we paired this data with aboveground carbon measurements at 219 sites to create boosted regression tree models and map aboveground carbon across the city. We then used these maps to determine how spatial variation in land cover/land use and landscape structure affects these carbon stocks. Foliage densities above 5m height, tree canopy height, and the presence of ground openings had the strongest relationships with aboveground carbon. Using these fine-scale relationships, we estimate that 2.2±0.4 TgC are stored aboveground in the urban portion of Brisbane, with mean densities of 32.6±5.8MgCha−1 calculated across the entire urban land area, and 110.9±19.7MgCha−1 calculated within treed areas. Predicted carbon densities within treed areas showed strong positive relationships with the proportion of surrounding tree cover and how clumped that tree cover was at both 1km2 and 1ha resolutions. Our models predict that even dense urban areas with low tree cover can have high carbon densities at fine scales. We conclude that actions and policies aimed at increasing urban carbon should focus on those areas where urban tree cover is most fragmented.

Anuran responses to spatial patterns of agricultural landscapes in Argentina

Amphibians are declining worldwide and land use change to agriculture is recognized as a leading cause. Argentina is undergoing an agriculturalization process with rapid changes in landscape structure. We evaluated anuran response to landscape composition and configuration in two landscapes of east-central Argentina with different degrees of agriculturalization. We identified sensitive species and evaluated landscape influence on communities and individual species at two spatial scales. We compared anuran richness, frequency of occurrence, and activity between landscapes using call surveys data from 120 sampling points from 2007 to 2009. We evaluated anuran responses to landscape structure variables estimated within 250 and 500-m radius buffers using canonical correspondence analysis and multimodel inference from a set of candidate models. Anuran richness was lower in the landscape with greater level of agriculturalization with reduced amount of forest cover and stream length. This pattern was driven by the lower occurrence and calling activity of seven out of the sixteen recorded species. Four species responded positively to the amount of forest cover and stream habitat. Three species responded positively to forest cohesion and negatively to rural housing. Two responded negatively to crop area and diversity of cover classes. Anurans within agricultural landscapes of east-central Argentina are responding to landscape structure. Responses varied depending on species and study scale. Life-history traits contribute to responses differences. Our study offers a better understanding of landscape effects on anurans and can be used for land management in other areas experiencing a similar agriculturalization process.

Landscape structure influences urban vegetation vertical structure

Summary Vegetation vertical structure is important for biodiversity and ecosystem service provision. In cities, however, while variation in the spatial extent and distribution of vegetation has been widely investigated, vertical vegetation structure and its potential drivers have not. Understanding how vegetation vertical structure varies across cities and identifying the potential drivers of this variation will improve the management of urban vegetation for biodiversity and ecosystem services. We used light detection and ranging (LiDAR) data to quantify the vertical structure of vegetation across Brisbane, Australia, at 1‐km2 and 1‐ha spatial scales and investigated how this structure varied in response to biophysical, socioeconomic, urban form and landscape structure variables. Using model selection techniques, we found that landscape structure variables related to tree cover (tree cover extent and spatial configuration) best explained the vegetation vertical structure at both spatial scales. Biophysical and urban form variables were also important, but only in combination with landscape structure. Mean vegetation vertical complexity, foliage projective cover and canopy height at a site all decreased as the treed proportion of the surrounding urban landscape decreased. In general, these vertical structure variables also increased where patches of vegetation were clustered together spatially. Synthesis and applications. Using light detection and ranging (LiDAR) data and model selection techniques, we show that the extent and vertical structure of urban vegetation are not independent and that reduced extent and increased fragmentation of urban vegetation are associated with simplification of its vertical structure. If common, this relationship means that managing urban vegetation for biodiversity and ecosystem services should not focus solely on the amount of tree cover or green space present across cities, but also on identifying where interventions to improve vegetation vertical complexity are required. Our study provides important insights into where these locations may be in cities.

Do Landscape Structure and Socio-Economic Variables Explain the Solidago Invasion?

Biological invasions are considered a major threat to biodiversity on a global scale. In this study, we examined the effect of landscape structure and socio-economic variables on the invasion pattern of alien Solidago species. Field data were collected in a set of 309 sampling plots, regularly placed on the intersecting lines of a 10 × 10-km grid, in south-western Poland (Silesia, Central Europe). Landscape characteristics and average values of socio-economic variables, such as human population density and total income per capita, were calculated. To examine the effect of landscape structure across different spatial extents, the landscape characteristics were analysed for three different buffers (radius: 500 m, 2 km and 5 km). A model explaining the pattern of the invasion was developed using a univariate, binary classification (decision) tree. The results show that both landscape structure and density of human population explain the spatial pattern of the invasion by alien Solidago species. The pattern was mostly shaped by the presence of unsuitable (forests) and suitable (roadsides) habitats for Solidago. The influence of percentage forest cover and road length was the strongest at the small spatial extent (radius = 500 m). The sum of linear elements length, percentage of urban areas and human population density calculated at the large extent (radius = 5 km) significantly improved the model. However, the predictive ability of these variables was less accurate. The model can be used by local authorities and land managers for modelling/predicting the hazards of invasion and elaborating a landscape-level system of Solidago control.

Landscape ecology, urban morphology, and CBDs: An analysis of the Columbus, Ohio Metropolitan Area

Landscape structure variables, derived from landscape ecology theory, are widely used in ecological studies. Fifteen landscape indices, organized into four groups – size, complexity, diversity, neighborhood - are computed for each of the 1,763 Traffic Analysis Zones in the seven-county Columbus, Ohio Metropolitan Area (CMA), using Fragstats and GIS. Urban morphology study is first presented, and regression models are estimated for each landscape index as a function of distances to the major metropolitan area central business districts (CBDs). Multiple functional forms have been tested for the models. Overall, the results provide evidence of the importance of role of CBDs on the landscape structure. CBDs significantly impact landscape indices in most cases.

Response of an ecological indicator to landscape composition and structure: Implications for functional units of temperate rainforest ecosystems

We evaluated the northern flying squirrel (Glaucomys sabrinus griseifrons), a known associate of key habitat features and processes of old-growth forest, for its capacity as a broad-scale ecological indicator of temperate rainforest ecosystem condition in southeastern Alaska, USA. We utilized a spatially explicit, resource-selection function to evaluate its distribution relative to landscape composition and structure at local (within home-range) and broad (home-range selection) spatial scales, followed by a moving-window analysis to model patch occupancy across this landscape. We found strong support for the influence of type, size, and compositional elements: large, old-growth patches were selected at both spatial scales, and regenerating forest patches ≤40yrs old were selected against at the broader scale. More importantly, we found that occupancy was related to critical thresholds in composition: patches required ≥73% old-growth forest cover or a minimum total area of 73ha of old-growth forest to be occupied by flying squirrels. A non-uniform pattern of selection for patches with higher structural connectivity at the local scale, but not at the broader scale, was likely a result of the “empty forest” phenomenon, in which remnant patches were inaccessible in this fragmented landscape. These results are consistent with recent studies of this and related species and suggest that occurrence of northern flying squirrels in southeastern Alaska is influenced by a number of landscape structure and compositional variables that relate critically to late-seral forest conditions. These findings shed new light on the utility of this species as an ecological indicator and its functional relevance to the resilience of fragmented forest ecosystems.

谷津田沿いの斜面地における半自然草地の分布と景観構造および局所立地条件との対応

谷津田沿いの斜面地における半自然草地の分布と景観構造および局所立地条件との対応

Southern pine beetle regional outbreaks modeled on landscape, climate and infestation history

The southern pine beetle (Dendroctonus frontalis, SPB) is the major insect pest of pine species in the southeastern United States. It attains outbreak population levels sufficient to mass attack host pines across the landscape at scales ranging from a single forest stand to interstate epidemics. This county level analysis selected and examined the best climatic and landscape variables for predicting infestations at regional scales. The analysis showed that, for a given county, the most important factor in predicting outbreaks was that the county was classified as in outbreak status in the previous year. Other important factors included minimum winter temperature and the greatest difference between the average of daily minimums and a subsequent low temperature point, precipitation history either seasonally in the previous year or difference from average over the previous 2 years, the synchronizing effect of seasonal temperatures on beetle populations and the relative percentage of total forest area composed of host species. The statistical models showed that climatic variables are stronger indicators of outbreak likelihood than landscape structure and cover variables. Average climatic conditions were more likely to lead to outbreaks than extreme conditions, supporting the notion of coupling between a native insect and its native host. Still, some extreme events (i.e., periods of very low temperature or very high precipitation) did precede beetle infestation. This analysis suggested that there are predisposing and inciting factors at the large scale but the driving factors leading to individual infestations operate at smaller scales.

Relating landscape structure, environment and management to biodiversity indicators estimated from forest inventory data in Catalonia (NE Spain)

There is an increasing need to develop efficient methods for characterising and monitoring forest biodiversity. A landscape scale approach and assessment can provide complementary and valuable information in this respect, by considering patterns and processes that operate at broad scales and influence different aspects of forest biodiversity. Here we analysed the relationships between six forest biodiversity indicators (related to the tree and shrub layers and estimated from a large set of field plots in the Third Spanish National Forest Inventory) and landscape structure, environmental and management variables at a 10 x 10 km scale in the region of Catalonia (NE Spain) through the variation partitioning method. The tree layer indicators were those most predictable from the set of explanatory variables considered, and up to a 77.2 % of total variation was explained for tree species richness. Landscape variables were much more relevant to explain biodiversity patterns than environmental and spatial factors, and landscape composition outperformed the predictive capacity of configuration metrics. Management had a weak but positive effect on the tree layer indicators, while the amount of early successional forest was negatively associated to the tree layer indicators but positively to those of the shrub stratum. Our results highlight the need to (1) concentrate field sampling efforts in those indicators that are less predictable from the landscape scale, such as those related to rare species with a high conservation value, and to (2) incorporate landscape structure variables for forest biodiversity assessments in the Mediterranean, where a landscape management approach may be particularly suited to allow the adaptation of forest biodiversity to the ongoing landscape dynamics related to broad-scale processes such as rural land abandonment or climate change.

Linking density, productivity and trends of an endangered species: The Bonelli's eagle in Spain

Whether regional population density is a good indicator of environmental quality according to demographic variables such as breeding success or short-term population trends is controversial. In this paper we analyze the interrelationships among regional population density, breeding success and recent population trends of an endangered species, Bonelli's eagle in the Iberian Peninsula. We also analyze the different influence of geographical, climatic, landscape structure and human impact variables on regional variation in those demographic variables. Breeding success was higher and population decrease was lower in those areas where the population density of Bonelli's eagle was greater. Breeding success, density and recent population trends of Bonelli's eagle were tightly related, increasing from northern to southern Iberian Peninsula (with highest figures at intermediate latitudes), and as sun radiation increased, and altitude decreased. Breeding success and population density were significantly lower in the periphery of the distribution range than in core areas in the Iberian Peninsula. Population trends between 2000 and 2005 were also more negative (decreasing) in the periphery. Overall, these results suggest that population density in this endangered species of large home-range is a good indicator of environmental quality and reproductive output, and that peripheral populations occupy low-suitability areas with lower breeding success, where negative short-term population trends are more likely.

Effects of landscape structure on genetic diversity of Geum urbanum L. populations in agricultural landscapes

Plant species in fragmented populations are affected by landscape structure because persistence within and migration among inhabited patches may be influenced by the identity and configuration of surrounding habitat elements. This may also be true for species of the semi-natural vegetation in agricultural landscapes. To determine the effect of landscape elements we analyzed Wood Avens ( Geum urbanum L.) populations within three 4×4 km 2 agricultural landscapes in Germany, Switzerland and Estonia, which differ in levels of land use intensity and habitat fragmentation. Genetic variation was determined in 15 randomly selected populations in each landscape using 10 microsatellite loci. The landscape structure was assessed at two circles around each population, with radii defined by the range limits of spatial genetic autocorrelation. Multiple regression analysis was used to determine the influence of landscape structure variables for inter- and intrapopulation genetic diversity. Gene diversity was equally high in Germany ( H e=0.27) and Switzerland ( H e=0.26) but lower in Estonia ( H e=0.16). A high overall inbreeding coefficient ( F IS=0.89) was found, as expected for a selfing breeding system in G. urbanum. Genetic differentiation among populations was high (overall F ST=0.43, 0.48, and 0.45 in Estonia, Switzerland and Germany, respectively), and did not differ among the three landscapes. Only a moderate influence of individual land use types on genetic diversity within and among populations was found with some idiosyncratic relationships. Genetic variation within populations was correlated to the amount of hedgerows positively in Estonia but negatively in Switzerland. The study demonstrates that the distribution of individual land use types affects the genetic pattern of a common plant species. However, different variables were identified to influence the genetic structure in three different landscapes. This indicates a major influence of landscape-specific land use history and stochastic processes determining gene flow and plant population structure.