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 | Universal species–area and endemics–area relationships at continental scales
Despite the broad conceptual and applied relevance of how the number of species or endemics changes with area (the species–area and endemics–area relationships (SAR and EAR)), our understanding of universality and pervasiveness of these patterns across taxa and regions has remained limited. The SAR has traditionally been approximated by a power law1, but recent theories predict a triphasic SAR in logarithmic space, characterized by steeper increases in species richness at both small and large spatial scales2, 3, 4, 5, 6. Here we uncover such universally upward accelerating SARs for amphibians, birds and mammals across the world’s major landmasses. Although apparently taxon-specific and continent-specific, all curves collapse into one universal function after the area is rescaled by using the mean range sizes of taxa within continents. In addition, all EARs approximately follow a power law with a slope close to 1, indicating that for most spatial scales there is roughly proportional species extinction with area loss. These patterns can be predicted by a simulation model based on the random placement of contiguous ranges within a domain. The universality of SARs and EARs after rescaling implies that both total and endemic species richness within an area, and also their rate of change with area, can be estimated by using only the knowledge of mean geographic range size in the region and mean species richness at one spatial scale. | 660.78KB | 22.05.2013 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Universal species–area and endemics–area relationships at continental scales - supplementary information
Despite the broad conceptual and applied relevance of how the number of species or endemics changes with area (the species–area and endemics–area relationships (SAR and EAR)), our understanding of universality and pervasiveness of these patterns across taxa and regions has remained limited. The SAR has traditionally been approximated by a power law1, but recent theories predict a triphasic SAR in logarithmic space, characterized by steeper increases in species richness at both small and large spatial scales2, 3, 4, 5, 6. Here we uncover such universally upward accelerating SARs for amphibians, birds and mammals across the world’s major landmasses. Although apparently taxon-specific and continent-specific, all curves collapse into one universal function after the area is rescaled by using the mean range sizes of taxa within continents. In addition, all EARs approximately follow a power law with a slope close to 1, indicating that for most spatial scales there is roughly proportional species extinction with area loss. These patterns can be predicted by a simulation model based on the random placement of contiguous ranges within a domain. The universality of SARs and EARs after rescaling implies that both total and endemic species richness within an area, and also their rate of change with area, can be estimated by using only the knowledge of mean geographic range size in the region and mean species richness at one spatial scale. | 1.82MB | 22.05.2013 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Downscaling species occupancy from coarse spatial scales
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. | 392.85KB | 27.05.2013 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Species richness declines and biotic homogenisation have slowed down for NW-European pollinators and plants
Concern about biodiversity loss has led to increased public investment in conservation. Whereas there is a widespread perception that such initiatives have been unsuccessful, there are few quantitative tests of this perception. Here, we evaluate whether rates of biodiversity change have altered in recent decades in three European countries (Great Britain, Netherlands and Belgium) for plants and flower visiting insects. We compared four 20-year periods, comparing periods of rapid land-use intensification and natural habitat loss (1930–1990) with a period of increased conservation investment (post-1990). We found that extensive species richness loss and biotic homogenisation occurred before 1990, whereas these negative trends became substantially less accentuated during recent decades, being partially reversed for certain taxa (e.g. bees in Great Britain and Netherlands). These results highlight the potential to maintain or even restore current species assemblages (which despite past extinctions are still of great conservation value), at least in regions where large-scale land-use intensification and natural habitat loss has ceased. | 922.28KB | 27.05.2013 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Identifying appropriate spatial scales of predictors in species distribution models with the random forest algorithm
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 the appropriate 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 R2 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.
| 611.92KB | 27.05.2013 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Patterns of beta diversity in Europe: the role of climate, land cover and distance across scales
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 (βsim, βJaccard) 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 (at fine grains) indicate that any species distribution modelling should take both environment and dispersal limitation into account.
| 706.59KB | 27.05.2013 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Improving conservation planning for semi-natural grasslands: Integrating connectivity into agri-environment schemes
Agricultural intensification is a major driver of biodiversity decline throughout Europe. Agri-environment schemes governed by EU regulation are a significant tool in combating this decline but despite high spending, experiences of their effectiveness have been mixed. Their effectiveness might be improved by targeting them to locations with high biodiversity value, and particularly by spatial coordination to enhance habitat connectivity and the associated ecological processes, such as dispersal. We show, with an example of semi-natural grassland conservation in South-Western Finland, how spatial conservation planning tools, here the Zonation software, could help in assessing the habitat connectivity and allocating management actions. We assign highest priority to sites that have been classified as nationally important and that have been under management, and let connectivity influence the Zonation prioritizations. According to Zonation outputs, 25–30% of highest-ranking grasslands in our study area are without management contracts, indicating weak connectivity of managed sites, whereas Natura 2000 areas are spatially better located. A 50% expansion of the current network would be adequate to bring its value close to that of a network created from scratch, but as the contracts are temporary, reallocation of the contracts from the least valuable, funded sites to more valuable, unfunded ones would be even more effective. Current policy instruments supporting farmland biodiversity are strongly constrained by EU regulation, and appear to be too inflexible to take the spatial differences in conservation values into account. Better communication and incentives to encourage farmer participation to these voluntary programs are needed. | 1.04MB | 20.06.2013 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Modelling invasive alien species distributions from digital biodiversity atlases. Model upscaling as a means of reconciling data at different scales
Aim
There is a wealth of information on species occurrences in biodiversity data banks, albeit presence-only, biased and scarce at fine resolutions. Moreover, fine-resolution species maps are required in biodiversity conservation. New techniques for dealing with this kind of data have been reported to perform well. These fine-resolution maps would be more robust if they could explain data at coarser resolutions at which species distributions are well represented. We present a new methodology for testing this hypothesis and apply it to invasive alien species (IAS).
Location
Catalonia, Spain.
Methods
We used species presence records from the Biodiversity data bank of Catalonia to model the distribution of ten IAS which, according to some recent studies, achieve their maximum distribution in the study area. To overcome problems inherent with the data, we prepared different correction treatments: three for dealing with bias and five for autocorrelation. We used the MaxEnt algorithm to generate models at 1-km resolution for each species and treatment. Acceptable models were upscaled to 10 km and validated against independent 10 km occurrence data.
Results
Of a total of 150 models, 20 gave acceptable results at 1-km resolution and 12 passed the cross-scale validation test. No apparent pattern emerged, which could serve as a guide on modelling. Only four species gave models that also explained the distribution at the coarser scale.
Main conclusions
Although some techniques may apparently deliver good distribution maps for species with scarce and biased data, they need to be taken with caution. When good independent data at a coarser scale are available, cross-scale validation can help to produce more reliable and robust maps. When no independent data are available for validation, however, new data gathering field surveys may be the only option if reliable fine-scale resolution maps are needed. | 565.27KB | 29.05.2013 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Mapping from heterogeneous biodiversity monitoring data sources
Field monitoring can vary from simple volunteer opportunistic observations to professional standardised monitoring surveys, leading to a trade-off between data quality and data collection costs. Such variability in data quality may result in biased predictions obtained from species distribution models (SDMs). We aimed to identify the limitations of different monitoring data sources for developing species distribution maps and to evaluate their potential for spatial data integration in a conservation context. Using Maxent, SDMs were generated from three different bird data sources in Catalonia, which differ in the degree of standardisation and available sample size. In addition, an alternative approach for modelling species distributions was applied, which combined the three data sources at a large spatial scale, but then downscaling to the required resolution. Finally, SDM predictions were used to identify species richness and high quality areas (hotspots) from different treatments. Models were evaluated by using high quality Atlas information. We show that both sample size and survey methodology used to collect the data are important in delivering robust information on species distributions. Models based on standardized monitoring provided higher accuracy with a lower sample size, especially when modelling common species. Accuracy of models from opportunistic observations substantially increased when modelling uncommon species, giving similar accuracy to a more standardized survey. Although downscaling data through a SDM approach appears to be a useful tool in cases of data shortage or low data quality and heterogeneity, it will tend to overestimate species distributions. In order to identify distributions of species, data with different quality may be appropriate. However, to identify biodiversity hotspots high quality information is needed.
| 1.09MB | 29.05.2013 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Modeling bird species distribution change in fire prone Mediterranean landscapes: incorporating species dispersal and landscape dynamics
Species distribution models (SDMs) have traditionally been founded on the assumption that species distributions are in equilibrium with environmental conditions and that these species–environment relationships can be used to estimate species responses to environmental changes. Insight into the validity of this assumption can be obtained from comparing the performance of correlative species distribution models with more complex hybrid approaches, i.e. correlative and process-based models that explicitly include ecological processes, thereby accounting for mismatches between habitat suitability and species occupancy patterns. Here we compared the ability of correlative SDMs and hybrid models, which can accommodate non-equilibrium situations arising from dispersal constraints, to reproduce the distribution dynamics of the ortolan bunting Emberiza hortulana in highly dynamic, early successional, fire driven Mediterranean landscapes. Whereas, habitat availability was derived from a correlative statistical SDM, occupancy was modeled using a hybrid approach combining a grid-based, spatially-explicit population model that explicitly included bird dispersal with the correlative model. We compared species occupancy patterns under the equilibrium assumption and different scenarios of species dispersal capabilities. To evaluate the predictive capability of the different models, we used independent species data collected in areas affected to different degree by fires. In accordance with the view that disturbance leads to a disparity between the suitable habitat and the occupancy patterns of the ortolan bunting, our results indicated that hybrid modeling approaches were superior to correlative models in predicting species spatial dynamics. Furthermore, hybrid models that incorporated short dispersal distances were more likely to reproduce the observed changes in ortolan bunting distribution patterns, suggesting that dispersal plays a key role in limiting the colonization of recently burnt areas. We conclude that SDMs used in a dynamic context can be significantly improved by using combined hybrid modeling approaches that explicitly account for interactions between key ecological constraints such as dispersal and habitat suitability that drive species response to environmental changes.
| 965.79KB | 29.05.2013 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Correlations in species richness between taxa depend on habitat, scale and landscape context
Biodiversity indicators are assumed to reflect changes in e.g. species richness of multiple taxa, but correlations in species richness between taxa have often been shown to be weak. However, only few studies are based on data allowing for rigorous tests whether strengths of correlations differ between habitat and landscape factors. We compared strengths of correlations between species richness of butterflies, plants and farmland birds between habitats (semi-natural grasslands, forest verges or field boundaries), spatial scales (0.8 ha, 25 ha and 50 ha) and landscapes differing in heterogeneity and regional land-use intensity. Between habitats, the correlation between butterflies and plants was strongest in semi-natural grasslands. Also concerning butterflies and plants, the correlation was weakest at the 0.8 ha scale, but no consistent scale-dependent patterns were found between plants and farmland birds. In a regional context, butterfly and plant species richness were consistently positively correlated, whereas when involving farmland birds we found correlations between taxa to be weaker and/or not significant in regions with high agricultural land-use intensity and in homogeneous landscapes. In general, species richness was consistently congruent only between butterflies and plants, whereas correlations involving farmland birds were mainly weak and showed contrasting patterns depending on regional context. Increasing landscape heterogeneity thus increased congruence amongst all studied taxa, but in different contexts and due to different underlying mechanisms. Although plants were involved in most of the significant correlations we cannot recommend a particular taxon as a general diversity indicator. | 263.31KB | 20.03.2015 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Effects of species turnover on reserve site selection in a fragmented landscape
Changes in species composition is an important process in many ecosystems but rarely considered in systematic reserve site selection. To test the influence of temporal variability in species composition on the establishment of a reserve network, we compared network configurations based on species data of small mammals and frogs sampled during two consecutive years in a fragmented Atlantic Forest landscape (SE Brazil). Site selection with simulated annealing was carried out with the datasets of each single year and after merging the datasets of both years. Site selection resulted in remarkably divergent network configurations. Differences are reflected in both the identity of the selected fragments and in the amount of flexibility and irreplaceability in network configuration. Networks selected when data for both years were merged did not include all sites that were irreplaceable in one of the 2 years. Results of species number estimation revealed that significant changes in the composition of the species community occurred. Hence, temporal variability of community composition should be routinely tested and considered in systematic reserve site selection in dynamic systems. | 870.37KB | 20.03.2015 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Influence of Admixture and Paleolithic Range Contractions on Current European Diversity Gradients
Cavalli-Sforza and Edwards (Analysis of human evolution. 1963. In: Geerts SJ, editor. Genetics today: Proceedings of the 11th International Congress of Genetics, The Hague, The Netherlands. New York: Pergamon. p. 923–993.) initiated the representation of genetic relationships among human populations with principal component (PC) analysis (PCA). Their study revealed the presence of a southeast–northwest (SE–NW) gradient of genetic variation in current European populations, which was interpreted as the result of the demic diffusion of early neolithic farmers during their expansion from the near east. However, this interpretation has been questioned, as PCA gradients can occur even when there is no expansion and because the first PC axis is often orthogonal to the expansion axis. Here, we revisit PCA patterns obtained under realistic scenarios of the settlement of Europe, focusing on the effects of various levels of admixture between paleolithic and neolithic populations, and of range contractions during the last glacial maximum (LGM). Using extensive simulations, we find that the first PC (PC1) gradients are orthogonal to the expansion axis, but only when the expansion is recent (neolithic). More ancient (paleolithic) expansions alter the orientation of the PC1 gradient due to a spatial homogenization of genetic diversity over time, and to the exact location of LGM refugia from which re-expansions proceeded. Overall we find that PC1 gradients consistently follow an SE–NW orientation if there is a large paleolithic contribution to the current European gene pool, and if the main refuge area during the last ice age was in the Iberian Peninsula. Our study suggests that an SE–NW PC1 gradient is compatible with little genetic impact of neolithic populations on the current European gene pool, and that range contractions have affected observed genetic patterns. | 6.47MB | 29.05.2013 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Spatial aggregation and the species–area relationship across scales
There has been a considerable effort to understand and quantify the spatial distribution of species across different ecosystems. Relative species abundance (RSA), beta diversity and species–area relationship (SAR) are among the most used macroecological measures to characterize plants communities in forests. In this paper we introduce a simple phenomenological model based on Poisson cluster processes which allows us to exactly link RSA and beta diversity to SAR. The framework is spatially explicit and accounts for the spatial aggregation of conspecific individuals. Under the simplifying assumption of neutral theory, we derive an analytical expression for the SAR which reproduces tri-phasic behavior as sample area increases from local to continental scales, explaining how the tri-phasic behavior can be understood in terms of simple geometric arguments. We also find an expression for the endemic area relationship (EAR) and for the scaling of the RSA.
| 569.46KB | 31.05.2013 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Increasing range mismatching of interacting species under global change is related to their ecological characteristics
Aim: We investigate the importance of interacting species for current and potential future species distributions, the influence of their ecological characteristics on projected range shifts when considering or ignoring interacting species, and the consistency of observed relationships across different global change scenarios.
Location: Europe.
Methods: We developed ecological niche models (generalized linear models) for 36 European butterfly species and their larval host plants based on climate and land-use data. We projected future distributional changes using three integrated global change scenarios for 2080. Observed and projected mismatches in potential butterfly niche space and the niche space of their hosts were first used to assess changing range limitations due to interacting species and then to investigate the importance of different ecological characteristics.
Results: Most butterfly species were primarily limited by climate. Species dwelling in warm areas of Europe and tolerant to large variations in moisture conditions were projected to suffer less from global change. However, a gradient from climate to host plant control was apparent, reflecting the range size of the hosts. Future projections indicated increased mismatching of already host-plant-limited butterflies and their hosts. Butterflies that utilize plants with restricted ranges were projected to suffer most from global change. The directions of these relationships were consistent across the scenarios but the level of spatial mismatching of butterflies and their host plants increased with the severity of the scenario.
Main conclusions: Future changes in the co-occurrence of interacting species will depend on political and socio-economic development, suggesting that the composition of novel communities due to global change will depend on the way we create our future. A better knowledge of ecological species characteristics can be utilized to project the future fate and potential risk of extinction of interacting species leading to a better understanding of the consequences of changing biotic interactions. This will further enhance our abilities to assess and mitigate potential negative effects on ecosystem functions and services. | 451.22KB | 20.06.2013 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| The landscape matrix modifies the effect of habitat fragmentation in grassland butterflies
The landscape matrix is suggested to influence the effect of habitat fragmentation on species richness, but the generality of this prediction has not been tested. Here, we used data from 10 independent studies on butterfly species richness, where the matrix surrounding grassland patches was dominated by either forest or arable land to test if matrix land use influenced the response of species richness to patch area and connectivity. To account for the possibility that some of the observed species use the matrix as their main or complementary habitat, we analysed the effects on total species richness and on the richness of grassland specialist and non-specialist (generalists and specialists on other habitat types) butterflies separately. Specialists and non-specialists were defined separately for each dataset. Total species richness and the richness of grassland specialist butterflies were positively related to patch area and forest cover in the matrix, and negatively to patch isolation. The strength of the species-area relationship was modified by matrix land use and had a slope that decreased with increasing forest cover in the matrix. Potential mechanisms for the weaker effect of grassland fragmentation in forest-dominated landscapes are (1) that the forest matrix is more heterogeneous and contains more resources, (2) that small grassland patches in a matrix dominated by arable land suffer more from negative edge effects or (3) that the arable matrix constitutes a stronger barrier to dispersal between populations. Regardless of the mechanisms, our results show that there are general effects of matrix land use across landscapes and regions, and that landscape management that increases matrix quality can be a complement to habitat restoration and re-creation in fragmented landscapes. | 493.9KB | 20.06.2013 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Traits related to species persistence and dispersal explain changes in plant communities subjected to habitat loss
Aim: Habitat fragmentation is a major driver of biodiversity loss but it is insufficiently known how much its effects vary among species with different life-history traits; especially in plant communities, the understanding of the role of traits related to species persistence and dispersal in determining dynamics of species communities in fragmented landscapes is still limited. The primary aim of this study was to test how plant traits related to persistence and dispersal and their interactions modify plant species vulnerability to decreasing habitat area and increasing isolation.
Location: Five regions distributed over four countries in Central and Northern Europe.
Methods: Our dataset was composed of primary data from studies on the distribution of plant communities in 300 grassland fragments in five regions. The regional datasets were consolidated by standardizing nomenclature and species life-history traits and by recalculating standardized landscape measures from the original geographical data. We assessed the responses of plant species richness to habitat area, connectivity, plant life-history traits and their interactions using linear mixed models.
Results: We found that the negative effect of habitat loss on plant species richness was pervasive across different regions, whereas the effect of habitat isolation on species richness was not evident. This area effect was, however, not equal for all the species, and life-history traits related to both species persistence and dispersal modified plant sensitivity to habitat loss, indicating that both landscape and local processes determined large-scale dynamics of plant communities. High competitive ability for light, annual life cycle and animal dispersal emerged as traits enabling species to cope with habitat loss.
Main conclusions: In highly fragmented rural landscapes in NW Europe, mitigating the spatial isolation of remaining grasslands should be accompanied by restoration measures aimed at improving habitat quality for low competitors, abiotically dispersed and perennial, clonal species. | 426.21KB | 20.06.2013 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Effect of habitat area and isolation on plant trait distribution in European forests and grasslands
A number of studies show contrasting results in how plant species with specific life-history strategies respond to fragmentation, but a general analysis on whether traits affect plant species occurrences in relation to habitat area and isolation has not been performed. We used published data from forests and grasslands in north-central Europe to analyse if there are general patterns of sensitivity to isolation and dependency of area for species using three traits: life-span, clonality, and seed weight. We show that a larger share of all forest species was affected by habitat isolation and area as compared to grassland species. Persistence-related traits, life-span and clonality, were associated to habitat area and the dispersal and recruitment related trait, seed weight, to isolation in both forest and grassland patches. Occurrence of clonal plant species decreased with habitat area, opposite to non-clonal plant species, and long-lived plant species decreased with grassland area. The directions of these responses partly challenge some earlier views, suggesting that further decrease in habitat area will lead to a change in plant species community composition, towards relatively fewer clonal and long-lived plants with large seeds in small forest patches and fewer clonal plants with small seeds in small grassland patches. It is likely that this altered community has been reached in many fragmented European landscapes consisting of small and isolated natural and semi-natural patches, where many non-clonal and short-lived species have already disappeared. Our study based on a large-scale dataset reveals general and useful insights concerning area and isolation effects on plant species composition that can improve the outcome of conservation and restoration efforts of plant communities in rural landscapes. | 1.07MB | 20.06.2013 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Does the interpolation accuracy of species distribution models come at the expense of transferability?
Model transferability (extrapolative accuracy) is one important feature in species distribution models, required in several ecological and conservation biological applications. This study uses 10 modelling techniques and nationwide data on both (1) species distribution of birds, butterflies, and plants and (2) climate and land cover in Finland to investigate whether good interpolative prediction accuracy for models comes at the expense of transferability – i.e. markedly worse performance in new areas. Models’ interpolation and extrapolation performance was primarily assessed using AUC (the area under the curve of a receiver characteristic plot) and Kappa statistics, with supplementary comparisons examining model sensitivity and specificity values. Our AUC and Kappa results show that extrapolation to new areas is a greater challenge for all included modelling techniques than simple filling of gaps in a well-sampled area, but there are also differences among the techniques in the degree of transferability. Among the machine-learning modelling techniques, MAXENT, generalized boosting methods (GBM), and artificial neural networks (ANN) showed good transferability while the performance of GARP and random forest (RF) decreased notably in extrapolation. Among the regression-based methods, generalized additive models (GAM) and generalized linear models (GLM) showed good transferability. A desirable combination of good prediction accuracy and good transferability was evident for three modelling techniques: MAXENT, GBM, and GAM. However, examination of model sensitivity and specificity revealed that model types may differ in their tendencies to either increased over-prediction of presences or absences in extrapolation, and some of the methods show contrasting changes in sensitivity vs specificity (e.g. ANN and GARP). Among the three species groups, the best transferability was seen with birds, followed closely by butterflies, whereas reliable extrapolation for plant species distribution models appears to be a major challenge at least at this scale. Overall, detailed knowledge of the behaviour of different techniques in various study settings and with different species groups is of utmost importance in predictive modelling. | 2.14MB | 20.06.2013 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Landscape context affects the relationship between local and landscape species richness of butterflies in semi-natural habitats
Local species richness of butterflies can be expected to benefit from both local habitat properties as well as the availability of suitable habitats and source populations in the surrounding landscape. Whether local species richness is dependent on local or landscape factors can be assessed by examining the relationship between local and landscape species richness. Here we studied how local species richness is related to landscape-level species richness in landscapes differing in agricultural intensity. The relationship was linear for field boundaries in intensively cultivated landscapes and non-linear in less-intensively cultivated landscapes. In landscapes containing semi-natural grasslands (on average 4% of overall land-use), the relationship was non-linear for field boundaries, but linear when considering local species richness of the grasslands themselves. These results show that local factors are more important than landscape factors in determining local species richness in landscapes which contained semi-natural grasslands. Local species richness was limited by landscape factors in intensively cultivated landscapes. This interpretation was supported by the relationship between local species richness and landscape-scale average mobility and generalist percentage of butterfly assemblages. We conclude that the management of field boundary habitat quality for butterflies is expected to be most effective in landscapes with semi-natural grasslands, the species composition of which in turn is dependent on the regional occurrence of grasslands. Based on our results, managing non-crop habitats for the conservation of habitat specialists and species with poor mobility will be most efficient in regions where patches of semi-natural grasslands occur. | 410.44KB | 20.06.2013 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Differences in the climatic debts of birds and butterflies at a continental scale
Climate changes have profound effects on the distribution of numerous plant and animal species. However, whether and how different taxonomic groups are able to track climate changes at large spatial scales is still unclear. Here, we measure and compare the climatic debt accumulated by bird and butterfly communities at a European scale over two decades (1990–2008). We quantified the yearly change in community composition in response to climate change for 9,490 bird and 2,130 butterfly communities distributed across Europe4. We show that changes in community composition are rapid but different between birds and butterflies and equivalent to a 37 and 114 km northward shift in bird and butterfly communities, respectively. We further found that, during the same period, the northward shift in temperature in Europe was even faster, so that the climatic debts of birds and butterflies correspond to a 212 and 135 km lag behind climate. Our results indicate both that birds and butterflies do not keep up with temperature increase and the accumulation of different climatic debts for these groups at national and continental scales. | 1016.45KB | 20.06.2013 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Adaptability of prey handling effort in relation to prey size in predatory wasps (Hymenoptera: Eumeninae)
The stinging pattern of a predatory wasp is a behavioural trait, affecting the possible evolutionary changes of its niche, e.g. widening or shifting the prey spectrum. We tested the hypothesis that the ability of a predator to adjust its handling effort to the size of prey is a species-specific trait, the parameters of which depend on the size and size range of the exploited prey. We found that wasps better adjust their stinging effort to prey size if they hunt relatively larger or relatively more variable prey. This adaptability differs amongst neighbouring phylogenetic lineages. We presume that evolution of prey-handling behaviour may result in two types of tactics: the first, an application of precise techniques for optimal prey immobilization, little dependent on prey size and typical of specialists. The second tactic typical of generalists is a less precise handling, causing more general damage to the prey with an intensity dependent on its size. | 341.4KB | 12.08.2014 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Sexual size dimorphism in the ontogeny of the solitary predatory wasp Symmorphus allobrogus (Hymenoptera: Vespidae)
Sex-specific patterns of individual growth, resulting in sexual size dimorphism (SSD), are a little studied aspect of the ontogeny related to the evolutionary history and affected by the ecology of a species. We used empirical data on the development of the predatory wasp Symmorphus allobrogus (Hymenoptera, Vespidae) to test the hypotheses that sexual differences of growth resulting in the female-biased SSD embrace the difference in (1) the egg size and the starting size of larva, (2) the larval development duration, and (3) the larval growth rate. We found that eggs developing into males and females have significant differences in size. There was no significant difference between the sexes in the duration of larval development. The relative growth rate and the food assimilation efficiency of female larvae were significantly higher than compared to those of male larvae. Thus, the SSD of S. allobrogus is mediated mainly by sexual differences in egg size and larval growth rate. | 549KB | 12.08.2014 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Species identification and genetic differentiation of European cavity-nesting wasps (Hymenoptera: Vespidae, Pompilidae, Crabronidae) inferred from DNA barcoding data
Solitary trap-nesting wasps are prospective bioindicators of anthropogenic pressures on natural ecosystems and one of the surrogate taxa for biodiversity assessments. The implementation of these studies is taxonomy-based and relies on accurate identification of species. The identification of larval stages of cavity-nesting Hymenoptera, collected using trap-nests, is complicated or impossible before the post-hibernation hatching of adults. DNA barcoding may allow the identification of the trap-nesting Hymenoptera species immediately after collection of the trap-nests, using larvae or dead specimens as sources of DNA. Using the standard barcoding sequence, we identified 33 wasp species from the families Vespidae, Pompilidae and Crabronidae, inhabiting trap-nests in Europe. Within-species and between-species genetic distances were estimated to evaluate the differences of intraspecific and interspecific genetic diversity. Genetic distances between related species indicated an obvious “barcoding gap”. Neighbour-joining analysis revealed that groups corresponding to taxa of genus level are cohesive as well. COI barcode approach was confirmed as a valuable tool for taxonomy-based biodiversity studies of the trap-nesting Hymenoptera.
Read More: http://informahealthcare.com/doi/abs/10.3109/19401736.2014.905827 | 279.82KB | 12.08.2014 | Margarita Grudova | Scales Relevant Scientific Papers | |
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| Assessing bee species richness in two Mediterranean communities: importance of habitat type and sampling techniques
The decline of bees has raised concerns regarding their conservation and the maintenance of ecosystem services they provide to bee-pollinated wild flowers and crops. Although the Mediterranean region is a hotspot for bee species richness, their status remains poorly studied. There is an urgent need for cost-effective, reliable, and unbiased sampling methods that give good bee species richness estimates. This study aims: (a) to assess bee species richness in two common Mediterranean habitat types: semi-natural scrub (phrygana) and managed olive groves; (b) to compare species richness in those systems to that of other biogeographic regions, and (c) to assess whether six different sampling methods (pan traps, variable and standardized transect walks, observation plots and trap nests), previously tested in other European biogeographic regions, are suitable in Mediterranean communities. Eight study sites, four per habitat type, were selected on the island of Lesvos, Greece. The species richness observed was high compared to other habitat types worldwide for which comparable data exist. Pan traps collected the highest proportion of the total bee species richness across all methods at the scale of a study site. Variable and standardized transect walks detected the highest total richness over all eight study sites. Trap nests and observation plots detected only a limited fraction of the bee species richness. To assess the total bee species richness in bee diversity hotspots, such as the studied habitats, we suggest a combination of transect walks conducted by trained bee collectors and pan trap sampling. | 421.9KB | 18.08.2014 | Margarita Grudova | Scales Relevant Scientific Papers | |
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