Widely distributed species, such as the perennial plant Arabidopsis lyrata, face a range of environmental conditions across space, creating selective pressures for local evolutionary adaptation. The species' fragmented distribution may reduce gene flow, which could either reduce or increase adaptive potential. The substantial variation in phenotypic traits observed across this species' northwestern European range may reflect a combination of plastic responses to environmental conditions, evolutionary adaptation and nonadaptive genetic differentiation. We conducted multi-site common garden experiments to study differences in plant performance in core and marginal areas. Plants from eight source populations representing the species' full geographic and altitudinal range in northwestern Europe were planted out in Iceland, Sweden, Scotland and Wales. We found evidence of both strong plastic responses and apparently adaptive differentiation in performance. Most evidence for local adaptation was found at range margins, with the strongest effects on reproductive output. Both biotic and abiotic factors affected performance, especially at range margins. Performance of most plants was best in the Scottish and Swedish common garden sites, in the core of the species' distribution. Despite adaptations at range margins, the performance of the species declines at distributional limits, with extreme southern populations looking particularly vulnerable.© 2012 The Authors. New Phytologist © 2012 New Phytologist Trust.
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The measurement and prediction of species' populations at different spatial scales is crucial to spatial ecology as well as conservation biology. An efficient yet challenging goal to achieve such population estimates consists of recording empirical species' presence and absence at a specific regional scale and then trying to predict occupancies at finer scales. So far the majority of the methods have been based on particular species' distributional features deemed to be crucial for downscaling occupancy. However, only a minority of them have dealt explicitly with specific spatial features. Here we employ a wide class of spatial point processes, the shot noise Cox processes (SNCP), to model species occupancies at different spatial scales and show that species' spatial aggregation is crucial for predicting population estimates at fine scales starting from coarser ones. These models are formulated in continuous space and locate points regardless of the arbitrary resolution that one employs to study the spatial pattern. We compare the performances of nine models, calibrated at regional scales and demonstrate that a very simple class of SNCP, the Thomas process, is able to outperform other published models in predicting occupancies down to areas four orders of magnitude smaller than the ones employed for the parameterization. We conclude by explaining the ability of the approach to infer spatially explicit information from spatially implicit measures, the potential of the framework to combine niche and spatial models, and the possibility of reversing the method to allow upscaling.© 2012 by the Ecological Society of America.
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The species-area relationship (SAR) is considered to be one of a few generalities in ecology, yet a universal model of its shape and slope has remained elusive. Recently, Harte et al. argued that the slope of the SAR for a given area is driven by a single parameter, the ratio between total number of individuals and number of species (i.e., the mean population size across species at a given scale). We provide a geometric interpretation of this dependence. At the same time, however, we show that this dependence cannot be universal across taxa: if it holds for a taxon composed from two subsets of species and also for one of its subsets, it cannot simultaneously hold for the other subset. Using three data sets, we show that the slope of the SAR considerably varies around the prediction. We estimate the limits of this variation by using geometric considerations, providing a theory based on species spatial turnover at different scales. We argue that the SAR cannot be strictly universal, but its slope at each particular scale varies within the constraints given by species' spatial turnover at finer spatial scales, and this variation is biologically informative.
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Widely distributed species, such as the perennial plant Arabidopsis lyrata, face a range of environmental conditions across space, creating selective pressures for local evolutionary adaptation. The species' fragmented distribution may reduce gene flow, which could either reduce or increase adaptive potential. The substantial variation in phenotypic traits observed across this species' northwestern European range may reflect a combination of plastic responses to environmental conditions, evolutionary adaptation and nonadaptive genetic differentiation. We conducted multi-site common garden experiments to study differences in plant performance in core and marginal areas. Plants from eight source populations representing the species' full geographic and altitudinal range in northwestern Europe were planted out in Iceland, Sweden, Scotland and Wales. We found evidence of both strong plastic responses and apparently adaptive differentiation in performance. Most evidence for local adaptation was found at range margins, with the strongest effects on reproductive output. Both biotic and abiotic factors affected performance, especially at range margins. Performance of most plants was best in the Scottish and Swedish common garden sites, in the core of the species' distribution. Despite adaptations at range margins, the performance of the species declines at distributional limits, with extreme southern populations looking particularly vulnerable.
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Fundamental ecological research is both intrinsically interesting and provides the basic knowledge required to answer applied questions of importance to the management of the natural world. The 100th anniversary of the British Ecological Society in 2013 is an opportune moment to reflect on the current status of ecology as a science and look forward to high-light priorities for future work. To do this, we identified 100 important questions of fundamental importance in pure ecology. We elicited questions from ecologists working across a wide range of systems and disciplines. The 754 questions submitted (listed in the online appendix) from 388 participants were narrowed down to the final 100 through a process of discussion, rewording and repeated rounds of voting. This was done during a two-day workshop and thereafter. The questions reflect many of the important current conceptual and technical pre-occupations of ecology. For example, many questions concerned the dynamics of environmental change and complex ecosystem interactions, as well as the interaction between ecology and evolution. The questions reveal a dynamic science with novel subfields emerging. For example, a group of questions was dedicated to disease and micro-organisms and another on human impacts and global change reflecting the emergence of new subdisciplines that would not have been foreseen a few decades ago. The list also contained a number of questions that have perplexed ecologists for decades and are still seen as crucial to answer, such as the link between population dynamics and life-history evolution. Synthesis. These 100 questions identified reflect the state of ecology today. Using them as an agenda for further research would lead to a substantial enhancement in understanding of the discipline, with practical relevance for the conservation of biodiversity and ecosystem function.© 2013 The Authors. Journal of Ecology © 2013 British Ecological Society.
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A substantial proportion of the global land surface is used for agricultural production. Agricultural land serves multiple societal purposes; it provides food, fuel and fibre and also acts as habitat for organisms and supports the services they provide. Biodiversity conservation and food production need to be balanced: production needs to be sustainable, while conservation cannot be totally at the expense of crop yield. To identify the benefits (in terms of biodiversity conservation) and costs (in terms of reduction in yields) of agricultural management, we examined the relationship between crop yield and abundance and species density of important taxa in winter cereal fields on both organic and conventional farms in lowland England. Of eight species groups examined, five (farmland plants, bumblebees, butterflies, solitary bees and epigeal arthropods) were negatively associated with crop yield, but the shape of this relationship varied between taxa. It was linear for the abundance of bumblebees and species density of butterflies, concave up for the abundance of epigeal arthropods and butterflies and concave down for species density of plants and bumblebees. Grain production per unit area was 54% lower in organic compared with conventional fields. When controlling for yield, diversity of bumblebees, butterflies, hoverflies and epigeal arthropods did not differ between farming systems, indicating that observed differences in biodiversity between organic and conventional fields are explained by lower yields in organic fields and not by different management practices per se. Only percentage cover and species density of plants were increased by organic field management after controlling for yield. The abundance of solitary wild bees and hoverflies was increased in landscapes with high amount of organic land. Synthesis and applications. Our results indicate that considerable gains in biodiversity require roughly proportionate reductions in yield in highly productive agricultural systems. They suggest that conservation efforts may be more cost effective in low-productivity agricultural systems or on non-agricultural land. In less productive agricultural landscapes, biodiversity benefit can be gained by concentrating organic farms into hotspots without a commensurate reduction in yield.© 2013 British Ecological Society.
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Including predictors in species distribution models at inappropriate spatial scales can decrease the variance explained, add residual spatial autocorrelation (RSA) and lead to the wrong conclusions. Some studies have measured predictors within different buffer sizes (scales) around sample locations, regressed each predictor against the response at each scale and selected the scale with the best model fit as theappropriate scale for this predictor. However, a predictor can influence a species at several scales or show several scales with good model fit due to a bias caused by RSA. This makes the evaluation of all scales with good model fit necessary. With potentially several scales per predictor and multiple predictors to evaluate, the number of predictors can be large relative to the number of data points, potentially impeding variable selection with traditional statistical techniques, such as logistic regression. We trialled a variable selection process using the random forest algorithm, which allows the simultaneous evaluation of several scales of multiple predictors. Using simulated responses, we compared the performance of models resulting from this approach with models using the known predictors at arbitrary and at the known spatial scales. We also apply the proposed approach to a real data set of curlew (Numenius arquata). AIC, AUC and Naglekerke's pseudo R of the models resulting from the proposed variable selection were often very similar to the models with the known predictors at known spatial scales. Only two of nine models required the addition of spatial eigenvectors to account for RSA. Arbitrary scale models always required the addition of spatial eigenvectors. 75% (50-100%) of the known predictors were selected at scales similar to the known scale (within 3 km). In the curlew model, predictors at large, medium and small spatial scales were selected, suggesting that for appropriate landscape-scale models multiple scales need to be evaluated. The proposed approach selected several of the correct predictors at appropriate spatial scales out of 544 possible predictors. Thus, it facilitates the evaluation of multiple spatial scales of multiple predictors against each other in landscape-scale models.© 2012 The Authors. Methods in Ecology and Evolution © 2012 British Ecological Society.
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Savanna ecosystems are dominated by two distinct plant life forms, grasses and trees, but the interactions between them are poorly understood. Here, we quantified the effects of isolated savanna trees on grass biomass as a function of distance from the base of the tree and tree height, across a precipitation gradient in the Kruger National Park, South Africa. Our results suggest that mean annual precipitation (MAP) mediates the nature of tree-grass interactions in these ecosystems, with the impact of trees on grass biomass shifting qualitatively between 550 and 737 mm MAP. Tree effects on grass biomass were facilitative in drier sites (MAP≤550 mm), with higher grass biomass observed beneath tree canopies than outside. In contrast, at the wettest site (MAP = 737 mm), grass biomass did not differ significantly beneath and outside tree canopies. Within this overall precipitation-driven pattern, tree height had positive effect on sub-canopy grass biomass at some sites, but these effects were weak and not consistent across the rainfall gradient. For a more synthetic understanding of tree-grass interactions in savannas, future studies should focus on isolating the different mechanisms by which trees influence grass biomass, both positively and negatively, and elucidate how their relative strengths change over broad environmental gradients.
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In this paper we present a multi-disciplinary analysis of the potential impacts of undertaking similar environmental actions on multiple farms in a small geographic area, using organic farming as a proxy for a co-ordinated approach. Recent papers have called for more co-ordinated efforts between farmers in terms of their environmental actions, but there has been limited applied research demonstrating the environmental benefits or the economic and social implications to farmers of this approach. Comparative analysis of biodiversity, soil and water, and farm profitability were undertaken in England on 32 matched farms in areas of low and high organic farming concentration; qualitative interviews were also conducted with 48 farmers living in two of the eight areas. Findings demonstrate higher overall levels of biodiversity on organic farms (particularly in " hotspot" areas) but this was not universal across the species groups investigated. Higher water infiltration rates were found in organic grasslands, which could prove to be a useful measure to combat flooding. In terms of the technical efficiency of producing these environmental gains, conventional and organic farms in hotspot areas demonstrated equivalent efficiency from a financial perspective. Socio-cultural research identified the different amounts of trust farmers have intheir neighbours, based in part on their performance as 'good farmers'. We discuss the neighbourhood effect with a multi-disciplinary approach and conclude that encouraging local farmer co-ordination can have clear environmental benefits without high economic cost, but must be undertaken with caution - specifically regarding the trade-offs between benefits, local geophysical and social characteristics, and assumptions made about inter-farmer trust.© 2011 Elsevier Ltd.
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Aim We test the prediction that beta diversity (species turnover) and the decay of community similarity with distance depend on spatial resolution (grain). We also study whether patterns of beta diversity are related to variability in climate, land cover or geographic distance and how the independent effects of these variables depend on the spatial grain of the data. Location Europe, Great Britain, Finland and Catalonia. Methods We used data on European birds, plants, butterflies, amphibians and reptiles, and data on British plants, Catalonian birds and Finnish butterflies. We fitted two or three nested grids of varying resolutions to each of these datasets. For each grid we calculated differences in climate, differences in land-cover composition (CORINE) and beta diversity (β , β ) between all pairs of grid cells. In a separate analysis we looked specifically at pairs of adjacent grid cells (the first distance class). We then used variation partitioning to identify the magnitude of independent statistical associations(i.e. independent effects in the statistical sense) of climate, land cover and geographic distance with spatial patterns of beta diversity. Results Beta diversity between grid cells at any given distance decreased with increasing grain. Geographic distance was always the most important predictor ofbeta diversity for all pairwise comparisons at the extent of Europe. Climate and land cover had weaker but distinct and grain-dependent effects. Climate was more important at relatively coarse grains, whereas land-cover effects were stronger at finer grains. In the country-wide analyses, climate and land cover were more important than geographic distance. Climatic and land-cover models performed poorly and showed no systematic grain dependence for beta diversity between adjacent grid cells. Main conclusions We found that relationships between geographic distance and beta diversity, as well asthe environmental correlates of beta diversity, are systematically grain dependent. The strong independent effect of distance indicates that, contrary to the current belief, a substantial fraction of species are missing from areas with a suitable environment. Moreover, the effects of geographic distance (at continental extents) and land cover (at fine grains) indicate that any species distribution modelling should take both environment and dispersal limitation into account. © 2012 Blackwell Publishing Ltd.
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Inferring biotic interactions from the examination of patterns of species occurrences has been a central tenet in community ecology, and it has recently gained interest in the context of single-species distribution modelling. However, understanding of how spatial extent and grain size affect such inferences remains elusive. For example, would inferences of biotic interactions from broad-scale patterns of coexistence provide a surrogate for patterns at finer spatial scales? In this paper we examine how the spatial and environmental association between two closely related species of freshwater turtles in the Iberian Peninsula is affected by the geographical extent and resolution of the analysis. Species coexistence was compared across spatial scales using five datasets at varying spatial extents and resolutions. Both similarities in the two species' use of space and in their responses to environmental variables were explored by means of regression analyses. We show that a positive association between the two species measured at broader scales can switch to a negative association at finer scales. We demonstrate that without examination of the effects of spatial scale when investigating biotic interactions using co-occurrence patterns observed at coarse resolutions, conclusions can be deeply misleading.© 2012 Gesellschaft für Ökologie.
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Aim: To determine how changing the resolution of modelled climate surfaces can affect estimates of the amount of thermally suitable habitat available to species under different levels of warming. Location: Lake Vyrnwy RSPB Reserve, which covers around 9700 hectares of a topographically diverse landscape in Wales. Methods: A recently published microclimate model was used to predict maximum, minimum and mean temperatures at 5× 5 m resolution for the study site, under current and possible future conditions. These temperature surfaces were then averaged to produce coarser resolution surfaces, up to a maximum of 1 × 1 km resolution. Ground beetles were collected using pitfall traps between May and August 2008. Generalized linear models (GLMs) were fitted to the temperature surfaces to predict the amount of landscape suitable for a northerly-distributed ground beetle, Carabus glabratus, and the most southerly-distributed ground beetle found at the site, Poecilus versicolor, under current and possible future conditions. Results: A wider range of temperatures are expected within our site when temperature is modelled at finer resolutions. Fitting GLMs at different resolutions resulted in the inclusion of different temperature variables in the best models. Coarser resolution models tended to have higher predictionerror, and different resolution models predicted that different amounts of the landscape would remain or become suitable in future. There was less agreement between models for C. glabratus than for P. versicolor. Main conclusions: In our example system, different resolution analyses result in different predictions about the ability of populations to survive climatic warming. Higher resolution analyses are not only likely to provide more accurate estimates of expected patterns of change, but also to highlight potential microclimatic refugia for the conservation of species that otherwise mightappear to be threatened with regional or global extinction. © 2012 Blackwell Publishing Ltd.
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Experimental studies have shown that many species show preferences for different climatic conditions, or may die in unsuitable conditions. Climate envelope models have been used frequently in recent years to predict the presence and absence of species at large spatial scales. However, many authors have postulated that the distributions of species at smaller spatial scales are determined by factors such as habitat availability and biotic interactions. Climatic effects are often assumed by modellers to be unimportant at fine resolutions, but few studies have actually tested this. We sampled the distributions of 20 beetle species of the family Carabidae across three study sites by pitfall trapping, and at the national scale from monitoring data. Statistical models were constructed to determine which of two sets of environmental variables (temperature or broad habitat type) best accounted for the observed data at the three sites and at the national (Great Britain) scale. High-resolution temperature variables frequently produced better models (as determined by AIC) than habitat features when modelling the distributions of species at a local scale, within the three study sites. Conversely, habitat was always a better predictor than temperature when describing species' distributions at a coarse scale within Great Britain. Northerly species were most likely to occur in cool micro-sites within the study sites, whereas southerly species were most likely to occur in warm micro-sites. Effects of microclimate were not limited to species at the edges of their distribution, and fine-resolution temperature surfaces should therefore ideally be utilised when undertaking climate-envelope modelling.© 2012 The Authors. Ecography © 2012 Nordic Society Oikos.
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Aim We test the prediction that beta diversity (species turnover) and the decay of community similarity with distance depend on spatial resolution (grain). We also study whether patterns of beta diversity are related to variability in climate, land cover or geographic distance and how the independent effects of these variables depend on the spatial grain of the data. Location Europe, Great Britain, Finland and Catalonia. Methods We used data on European birds, plants, butterflies, amphibians and reptiles, and data on British plants, Catalonian birds and Finnish butterflies. We fitted two or three nested grids of varying resolutions to each of these datasets. For each grid we calculated differences in climate, differences in land-cover composition (CORINE) and beta diversity (β , β ) between all pairs of grid cells. In a separate analysis we looked specifically at pairs of adjacent grid cells (the first distance class). We then used variation partitioning to identify the magnitude of independent statistical associations (i.e. independent effects in the statistical sense) of climate, land cover and geographic distance with spatial patterns of beta diversity. Results Beta diversity between grid cells at any given distance decreased with increasing grain. Geographic distance was always the most important predictor of beta diversity for all pairwise comparisons at the extent of Europe. Climate and land cover had weaker but distinct and grain-dependent effects. Climate was more important at relatively coarse grains, whereas land-cover effects were stronger at finer grains. In the country-wide analyses, climate and land cover were more important than geographic distance. Climatic and land-cover models performed poorly and showed no systematic grain dependence for beta diversity between adjacent grid cells. Main conclusions We found that relationships between geographic distance and beta diversity, as well as the environmental correlates of beta diversity, are systematically grain dependent. The strong independent effect of distance indicates that, contrary to the current belief, a substantial fraction of species are missing from areas with a suitable environment. Moreover, the effects of geographic distance (at continental extents) and land cover (atfine grains) indicate that any species distribution modelling should take both environment and dispersal limitation into account. © 2012 Blackwell Publishing Ltd.
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Inferring biotic interactions from the examination of patterns of species occurrences has been a central tenet in community ecology, and it has recently gained interest in the context of single-species distribution modelling. However, understanding of how spatial extent and grain size affect such inferences remains elusive. For example, would inferences of biotic interactions from broad-scale patterns of coexistence provide a surrogate for patterns at finer spatial scales? In this paper we examine how the spatial and environmental association between two closely related species of freshwater turtles in the Iberian Peninsula is affected by the geographical extent and resolution of the analysis. Species coexistence was compared across spatial scales using five datasets at varying spatial extents and resolutions. Both similarities in the two species' use of space and in their responses to environmental variables were explored by means of regression analyses. We show that a positive association between the two species measured at broader scales can switch to a negative association at finer scales. We demonstrate that without examination of the effects of spatial scale when investigating biotic interactions using co-occurrence patterns observed at coarse resolutions, conclusions can be deeply misleading.© 2012 Gesellschaft für ökologie.
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Land-use changes can alter the spatial population structure of plant species, which may in turn affect the attractiveness of flower aggregations to different groups of pollinators at different spatial scales. To assess how pollinators respond to spatial heterogeneity of plant distributions and whether honeybees affect visitation by other pollinatorswe used an extensive data set comprising ten plant species and their flower visitors from five European countries. In particular we tested the hypothesis that the composition of the flower visitor community in terms of visitation frequencies by different pollinator groups were affected by the spatial plant population structure, viz. area and density measures, at a within-population ('patch') and among-population ('population') scale. We found that patch area and population density were the spatial variables that best explained the variation in visitation frequencies within the pollinator community. Honeybees had higher visitation frequencies in larger patches, while bumblebees and hoverflies had higher visitation frequencies in sparser populations. Solitary bees had higher visitation frequencies in sparser populations and smaller patches. We also tested the hypothesis that honeybees affect the composition of the pollinator community by altering the visitation frequencies of other groups of pollinators. There was a positive relationship between visitation frequencies of honeybees and bumblebees, while the relationship with hoverflies and solitary bees varied (positive, negative and no relationship) depending on the plant species under study. The overall conclusion is that the spatial structure of plant populations affects different groups of pollinators in contrasting ways at both the local ('patch') and the larger ('population') scales and, that honeybees affect the flower visitation by other pollinator groups in various ways, depending on the plant species under study. These contrasting responses emphasize the need to investigate the entire pollinator community when the effects of landscape change on plant-pollinator interactions are studied.© 2012 Gesellschaft für Ökologie.
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Aim: To determine how changing the resolution of modelled climate surfaces can affect estimates of the amount of thermally suitable habitat available to species under different levels of warming. Location: Lake Vyrnwy RSPB Reserve, which covers around 9700 hectares of a topographically diverse landscape in Wales. Methods: A recently published microclimate model was used to predict maximum, minimum and mean temperatures at 5× 5 m resolution for the study site, under current and possible future conditions. These temperature surfaces were then averaged to produce coarser resolution surfaces, up to a maximum of 1 × 1 km resolution. Ground beetles were collected using pitfall traps between May and August 2008. Generalized linear models (GLMs) were fitted to the temperature surfaces to predict the amount of landscape suitable for a northerly-distributed ground beetle, Carabus glabratus, and the most southerly-distributed ground beetle found at the site, Poecilus versicolor, under current and possible future conditions. Results: A wider range of temperatures are expected within our site when temperature is modelled at finer resolutions. Fitting GLMs at different resolutions resulted in the inclusion of different temperature variables in the best models. Coarser resolution models tended to have higher predictionerror, and different resolution models predicted that different amounts of the landscape would remain or become suitable in future. There was less agreement between models for C. glabratus than for P. versicolor. Main conclusions: In our example system, different resolution analyses result in different predictions about the ability of populations to survive climatic warming. Higher resolution analyses are not only likely to provide more accurate estimates of expected patterns of change, but also to highlight potential microclimatic refugia for the conservation of species that otherwise mightappear to be threatened with regional or global extinction. © 2012 Blackwell Publishing Ltd.
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In response to evidence of insect pollinator declines, organisations in many sectors, including the food and farming industry, are investing in pollinator conservation. They are keen to ensure that their efforts use the best available science. We convened a group of 32 'conservation practitioners' with an active interest in pollinators and 16 insect pollinator scientists. The conservation practitioners include representatives from UK industry (including retail), environmental non-government organisations and nature conservation agencies. We collaboratively developed a long list of 246 knowledge needs relating to conservation of wild insect pollinators in the UK. We refined and selected the most important knowledge needs, through a three-stage process of voting and scoring, including discussions of each need at a workshop. We present the top 35 knowledge needs as scored by conservation practitioners or scientists. We find general agreement in priorities identified by these two groups. The priority knowledge needs will structure ongoing work to make science accessible to practitioners, and help to guide future science policy and funding. Understanding the economic benefits of crop pollination, basic pollinator ecology and impacts of pesticides on wild pollinators emerge strongly as priorities, as well as a need to monitor floral resources in the landscape.© 2012 The Royal Entomological Society.
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Land-use changes can alter the spatial population structure of plant species, which may in turn affect the attractiveness of flower aggregations to different groups of pollinators at different spatial scales. To assess how pollinators respond to spatial heterogeneity of plant distributions and whether honeybees affect visitation by other pollinators we used an extensive data set comprising ten plant species and their flower visitors from five European countries. In particular we tested the hypothesis that the composition of the flower visitor community in terms of visitation frequencies by different pollinator groups were affected by the spatial plant population structure, viz. area and density measures, at a within-population ('patch') and among-population ('population') scale. We found that patch area and population density were the spatial variables that best explained the variation in visitation frequencies within the pollinator community. Honeybees had higher visitation frequencies in larger patches, while bumblebees and hoverflies had higher visitation frequencies in sparser populations. Solitary bees had higher visitation frequencies in sparser populations and smaller patches. We also tested the hypothesis that honeybees affect the composition of the pollinator community by altering the visitation frequencies of other groups of pollinators. There was a positive relationship between visitation frequencies of honeybees and bumblebees, while the relationship with hoverflies and solitary bees varied (positive, negative and no relationship) depending on the plant species under study. The overall conclusion is that the spatial structure of plant populations affects different groups of pollinators in contrasting ways at both the local ('patch') and the larger ('population') scales and, that honeybees affect the flower visitation by other pollinator groups in various ways, depending on the plant species under study. These contrasting responses emphasize the need to investigate the entire pollinator community when the effects of landscape change on plant-pollinator interactions are studied.© 2012 Gesellschaft far kologie.
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Range margins are spatially complex, with environmental, genetic and phenotypic variations occurring across a range of spatial scales. We examine variation in temperature, genes and metabolomic profiles within and between populations of the subalpine perennial plant Arabidopsis lyrata ssp. petraea fromacross its northwest European range. Our surveys cover a gradient of fragmentation from largely continuous populations in Iceland, through more fragmented Scandinavian populations, to increasingly widely scattered populations at the range margin in Scotland, Wales and Ireland. Temperature regimes vary substantially within some populations, but within-population variation represents a larger fraction of genetic and especially metabolomic variances. Both physical distance and temperature differences between sites are found to be associated with genetic profiles, but not metabolomic profiles, and no relationship was found between genetic and metabolomic population structures in any region. Genetic similarity between plants within populations is the highest in the fragmented populations at the range margin, but differentiation across space is the highest there as well, suggesting that regional patterns of genetic diversity may be scale dependent.© 2009 The Royal Society.
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There exists a transition zone between forest and the adjacent clearing wherein each is influenced by and influences the other. This paper presents an unbiased, bi-directional approach to describe the nature of this transition and determine the spatial extent of edge effects between habitats. Conceptual models are identified and existing statistical (regression-based) models are examined. Four different regression models are developed to describe each of the proposed models; a simple linear regression (SLR) and three piecewise linear regression models (PLR) with one, two and three changes in the response variable, representing different complexities of the community response. Use of these models is demonstrated using a case study of understorey vegetation community dynamics across the transition from clearcuts to the temperate rainforest of Southeast Alaska, USA. Results show that the overall variation in species composition is best described by the regression model with two points of change. Within the 95% confidence interval, edge effects extend to two meters into the clearcut and to two meters into the forest (total width of four meters), beyond which understorey composition in both the clearcut and the forest appears relatively stable and unaffected by the other environment. PLR models are an objective tool for determining edge responses in vegetation communities and may be further applied to ecological and environmental responses across spatial (or temporal) gradients.
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Fractals have found widespread application in a range of scientific fields, including ecology. This rapid growth has produced substantial new insights, but has also spawned confusion and a host of methodological problems. In this paper, we review the value of fractal methods, in particular for applications to spatial ecology, and outline potential pitfalls. Methods for measuring fractals in nature and generating fractal patterns for use in modelling are surveyed. We stress the limitations and the strengths of fractal models. Strictly speaking, no ecological pattern can be truly fractal, but fractal methods may nonetheless provide the most efficient tool available for describing and predicting ecological patterns at multiple scales.
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Artificial neural network (ANN) methods are used to predict forest characteristics. The data source is the Southeast Alaska (SEAK) Grid Inventory, a ground survey compiled by the USDA Forest Service at several thousand sites. The main objective of this article is to predict characteristics at unsurveyed locations between grid sites. A secondary objective is to evaluatethe relative performance of different ANNs. Data from the grid sites are used to train six ANNs: multilayer perceptron, fuzzy ARTMAP, probabilistic, generalized regression, radial basis function, and learning vector quantization. A classification and regression tree method is used for comparison. Topographic variables are used to construct models: latitude and longitude coordinates, elevation, slope, and aspect. The models classify three forest characteristics: crown closure, species land cover, and tree size/structure. Models are constructed using n-fold cross-validation. Predictive accuracy is calculated using a method that accounts for the influence of misclassification as well as measuring correct classifications. The probabilistic and generalized regression networks are found to be the most accurate. The predictions of the ANN models are compared with a classification of the Tongass national forest in southeast Alaska based on the interpretation of satellite imagery and are found to be of similar accuracy.
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The spatial distribution of a species can be characterized at many different spatial scales, from fine-scale measures of local population density to coarse-scale geographical-range structure. Previous studies have shown a degree of correlation in species' distribution patterns across narrow ranges of scales, making it possible to predict fine-scale properties from coarser-scale distributions. To test the limits of such extrapolation, we have compiled distributional information on 16 species of British plants, at scales ranging across six orders of magnitude in linear resolution (1 in to 100 km). As expected, the correlation between patterns at different spatial scales tends to degrade as the scales become more widely separated. There is, however, an abrupt breakdown in cross-scale correlations across intermediate (ca. 0.5 km) scales, suggesting that local and regional patterns are influenced by essentially non-overlapping sets of processes. The scaling discontinuity may also reflect characteristic scales of human land use in Britain, suggesting a novel method for analysing the 'footprint' of humanity on a landscape.
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Aim Species generally become rarer and more patchily distributed as the margins of their ranges are approached. We predicted that in such marginal sites, tree species would tend to occur where some key environmental factors are at particularly favourable levels, compensating in part for the low overall suitability of marginal sites. Location The article considers the spatial distributions of trees in Southeast Alaska (the Alaskan 'panhandle'). Methods We quantified range marginality using spatial distributions of eight tree species across more than one thousand surveyed sites in Southeast Alaska. For each species we derived a site core/margin index using a three-dimensional trend surface generated from logistic regression on site coordinates. For eachspecies, the relationships between the environmental factors slope, aspect and site marginality were then compared for occupied and unoccupied sets of sites. Results We found that site slope is important for more Alaskan tree species than aspect. Three out of eight had a significant core/margin by occupied/unoccupied interaction, tending to be present in significantly shallower-sloped (more favourable) sites in the marginal areas than the simple core/margin trend predicted. For site aspect, one species had a significant interaction, selecting potentially more favourable northerly aspects in marginal areas. A finer-scale analysis based on the same data came to the same overall conclusions. Conclusions There is evidence that several tree species in Alaska tend to occur in especially favourable sites in marginal areas. In these marginal areas, these species amplify habitat preferences shown in core areas.
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The analysis, measurement, and management of species abundance is central to ecology and conservation biology, but it has proved difficult to find a single index that adequately reflects the commonness or rarity of species across a range of spatial scales. Here, a scale-independent measure of species abundance is developed, using presence-absence maps at varying spatial resolutions. By extrapolating such "scale-area" curves, species abundance can be estimated accurately even at scales finer than those used to parameterize the model, a task that had previously been deemed impossible in principle.
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The coexistence of many plant species competing for a few resources is one of the central puzzles of community ecology. One explanation is that different species may be competitively superior in different microhabitats. Many species could then coexist within each piece of a mosaic landscape by what has been termed "mass effects," because subpopulations in areas with negative growth rates would be supplemented by propagules from areas with reproductive surpluses. If mass effects are important, plant species diversity should increase near habitat boundaries, especially where habitat differences are moderate. In the first experimental test of this prediction, plants were censused on 54 transects within the long-established Rothamsted Park Grass plots. Very few showed significant declines in species richness with distance from subplot boundaries. Nonetheless, the regression coefficients were negative much more often than expected by chance, suggesting that weak mass effects operated. The effect was strongest where neighboring subplots differed greatly, with no evidence of the predicted decline where differences were extreme. Detailed analyses of transects with apparent mass effects revealed few species that behaved as predicted. This study serves both to provide evidence of the existence of mass effects and to question their importance in the maintenance of local plant diversity in this system.
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1 The term 'density-dependence' is often applied rather loosely to a variety of aspects of local abundance. 'Density' is most commonly measured as the size of a local population and/or the (average) spacing between the individuals within it. These parameters are interrelated and correlated in most natural populations. Yet species interactions and population dynamics may be affected differently by these different aspects of abundance. 2 Field experiments were performed to tesi the effects of two components of local abundance on pollination in the self-incompatible annual plant, Brassica kaber. In one experiment, populations of uniform density but differing size were planted out, whilst in a second study both the density and size of populations were varied. 3 The number of individuals in a population had no effect on pollinator visitation or subsequent seed set in either experiment. 4 Population density, however, had strong effects on both visitation and reproductive success. 5 The position of a plant within a population had an impact on pollinator constancy in the second experiment, but had no effect on visitation rates or reproductive success.
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Most ecological generalizations stem from the study of common organisms, but most species are rare. There are a number of reasons to expect that rare and common species may differ consistently in their characteristics, with possible implications for conservation. Past analyses of this issue, however, have generally considered only a single measure of rarity and have not corrected analyses for the lack of independence in the traits of related species. We compared several reproductive characteristics of Mediterranean annual crucifers as a function of their global range regional abundance and local population density in Israel, making use of independent contrast methods to correct for the phylogenetic relationships of the species involved. We found plants growing at low local density to be disproportionately likely to be self-compatible. Petal length and floral depth (sepal length) were correlated with breeding system but showed significant interaction effects between breeding system and abundance. Floral longevity was inversely related to abundance and also showed significant interaction effects between breeding system and abundance. Overall, rare species tended to display more extreme values for floral traits than did common plants with the same breeding systems; they had unusually large and deep flowers ifself-incompatible and unusually small, shallow ones if self-compatible.
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Experimental studies have shown that many species show preferences for different climatic conditions, or may die in unsuitable conditions. Climate envelope models have been used frequently in recent years to predict the presence and absence of species at large spatial scales. However, many authors have postulated that the distributions of species at smaller spatial scales are determined by factors such as habitat availability and biotic interactions. Climatic effects are often assumed by modellers to be unimportant at fine resolutions, but few studies have actually tested this. We sampled the distributions of 20 beetle species of the family Carabidae across three study sites by pitfall trapping, and at the national scale from monitoring data. Statistical models were constructed to determine which of two sets of environmental variables (temperature or broad habitat type) best accounted for the observed data at the three sites and at the national (Great Britain) scale. High-resolution temperature variables frequently produced better models (as determined by AIC) than habitat features when modelling the distributions of species at a local scale, within the three study sites. Conversely, habitat was always a better predictor than temperature when describing species' distributions at a coarse scale within Great Britain. Northerly species were most likely to occur in cool micro-sites within the study sites, whereas southerly species were most likely to occur in warm micro-sites. Effects of microclimate were not limited to species at the edges of their distribution, and fine-resolution temperature surfaces should therefore ideally be utilised when undertaking climate-envelope modelling.© 2011 The Authors.
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