Showing papers in "Ecography in 2013"

Collinearity: a review of methods to deal with it and a simulation study evaluating their performance

Abstract: Collinearity refers to the non independence of predictor variables, usually in a regression-type analysis. It is a common feature of any descriptive ecological data set and can be a problem for parameter estimation because it inflates the variance of regression parameters and hence potentially leads to the wrong identification of relevant predictors in a statistical model. Collinearity is a severe problem when a model is trained on data from one region or time, and predicted to another with a different or unknown structure of collinearity. To demonstrate the reach of the problem of collinearity in ecology, we show how relationships among predictors differ between biomes, change over spatial scales and through time. Across disciplines, different approaches to addressing collinearity problems have been developed, ranging from clustering of predictors, threshold-based pre-selection, through latent variable methods, to shrinkage and regularisation. Using simulated data with five predictor-response relationships of increasing complexity and eight levels of collinearity we compared ways to address collinearity with standard multiple regression and machine-learning approaches. We assessed the performance of each approach by testing its impact on prediction to new data. In the extreme, we tested whether the methods were able to identify the true underlying relationship in a training dataset with strong collinearity by evaluating its performance on a test dataset without any collinearity. We found that methods specifically designed for collinearity, such as latent variable methods and tree based models, did not outperform the traditional GLM and threshold-based pre-selection. Our results highlight the value of GLM in combination with penalised methods (particularly ridge) and threshold-based pre-selection when omitted variables are considered in the final interpretation. However, all approaches tested yielded degraded predictions under change in collinearity structure and the ‘folk lore’-thresholds of correlation coefficients between predictor variables of |r| >0.7 was an appropriate indicator for when collinearity begins to severely distort model estimation and subsequent prediction. The use of ecological understanding of the system in pre-analysis variable selection and the choice of the least sensitive statistical approaches reduce the problems of collinearity, but cannot ultimately solve them.

A practical guide to MaxEnt for modeling species' distributions: what it does, and why inputs and settings matter

Abstract: The MaxEnt software package is one of the most popular tools for species distribution and environmental niche modeling, with over 1000 published applications since 2006. Its popularity is likely for two reasons: 1) MaxEnt typically outperforms other methods based on predictive accuracy and 2) the software is particularly easy to use. MaxEnt users must make a number of decisions about how they should select their input data and choose from a wide variety of settings in the software package to build models from these data. The underlying basis for making these decisions is unclear in many studies, and default settings are apparently chosen, even though alternative settings are often more appropriate. In this paper, we provide a detailed explanation of how MaxEnt works and a prospectus on modeling options to enable users to make informed decisions when preparing data, choosing settings and interpreting output. We explain how the choice of background samples reflects prior assumptions, how nonlinear functions of environmental variables (features) are created and selected, how to account for environmentally biased sampling, the interpretation of the various types of model output and the challenges for model evaluation. We demonstrate MaxEnt’s calculations using both simplified simulated data and occurrence data from South Africa on species of the flowering plant family Proteaceae. Throughout, we show how MaxEnt’s outputs vary in response to different settings to highlight the need for making biologically motivated modeling decisions.

Hierarchical effects of environmental filters on the functional structure of plant communities: a case study in the French Alps

Abstract: Understanding the inf l uence of the environment on the functional structure of ecological communities is essential to predict the response of biodiversity to global change drivers. Ecological theory suggests that multiple environmental factors shape local species assemblages by progressively fi ltering species from the regional species pool to local communities. ! ese successive fi lters should infl uence the various components of community functional structure in di" erent ways. In this paper, we tested the relative infl uence of multiple environmental fi lters on various metrics of plant functional trait structure (i.e. ‘ community weighted mean trait ’ and components of functional trait diversity, i.e. functional richness, evenness and divergence) in 82 vegetation plots in the Guisane Valley, French Alps. For the 211 sampled species we measured traits known to capture key aspects of ecological strategies amongst vascular plant species, i.e. leaf traits, plant height and seed mass (LHS). A comprehensive information theory framework, together with null model based resampling techniques, was used to test the various environmental e" ects. Particular community components of functional structure responded di" erently to various environmental gradients, especially concerning the spatial scale at which the environmental factors seem to operate. Environmental factors acting at a large spatial scale (e.g. temperature) were found to predominantly shape community weighted mean trait values, while fi ne-scale factors (topography and soil characteristics) mostly infl uenced functional diversity and the distribution of trait values among the dominant species. Our results emphasize the hierarchical nature of ecological forces shaping local species assemblage: large-scale environmental fi lters having a primary e" ect, i.e. selecting the pool of species adapted to a site, and then fi lters at fi scales determining species abundances and local species coexistence. ! is suggests that di" erent components of functional community structure will respond di" erently to environmental change, so that predicting plant community responses will require a hierarchical multi-facet approach.

Selecting from correlated climate variables: a major source of uncertainty for predicting species distributions under climate change

Abstract: Correlative species distribution models are frequently used to predict species’ range shifts under climate change. However, climate variables often show high collinearity and most statistical approaches require the selection of one among strongly correlated variables. When causal relationships between species presence and climate parameters are unknown, variable selection is often arbitrary, or based on predictive performance under current conditions. While this should only marginally affect current range predictions, future distributions may vary considerably when climate parameters do not change in concert. We investigated this source of uncertainty using four highly correlated climate variables together with a constant set of landscape variables in order to predict current (2010) and future (2050) distributions of four mountain bird species in central Europe. Simulating different parameterization decisions, we generated a) four models including each of the climate variables singly, b) a model taking advantage of all variables simultaneously and c) an un-weighted average of the predictions of a). We compared model accuracy under current conditions, predicted distributions under four scenarios of climate change, and – for one species – evaluated back-projections using historical occurrence data. Although current and future variable-correlations remained constant, and the models’ accuracy under contemporary conditions did not differ, future range predictions varied considerably in all climate change scenarios. Averaged models and models containing all climate variables simultaneously produced intermediate predictions; the latter, however, performed best in back-projections. This pattern, consistent across different modelling methods, indicates a benefit from including multiple climate predictors in ambiguous situations. Variable selection proved to be an important source of uncertainty for future range predictions, difficult to control using contemporary information. Small, but diverging changes of climate variables, masked by constant overall correlation patterns, can cause substantial differences between future range predictions which need to be accounted for, particularly when outcomes are intended for conservation decisions.

Exploring the role of physiology and biotic interactions in determining elevational ranges of tropical animals

Abstract: Tropical mountains contain some of the world’s richest animal communities as a result of high turnover of species along elevational gradients. We describe an approach to study the roles of biotic and abiotic factors in establishing elevational ranges, and to improve our ability to predict the effects of climate change on these communities. As a framework we use Hutchinson’s concept of the fundamental niche (determined by the match between the physical environment and the organism’s physiological and biophysical characteristics) and realized niche (the subset of the fundamental niche determined by biotic interactions). Using tropical birds as an example, we propose a method for estimating fundamental niches and discuss five biotic interactions that we expect to influence distributions of tropical montane animals: predation, competition, parasites and pathogens, mutualisms, and habitat associations. The effects of biotic factors on elevational ranges have been studied to some extent, but there is little information on physiological responses of tropical montane animals. It will be necessary to understand all of these ecological constraints in concert to predict current and future elevational ranges and potential threats to montane species. Given the importance of tropical mountains as global biodiversity hotspots, we argue that this area of research requires urgent attention.

The assembly of tropical tree communities – the advances and shortcomings of phylogenetic and functional trait analyses

Abstract: Tropical tree communities present one of the most challenging systems for studying the processes underlying community assembly Most community assembly hypotheses consider the relative importance of the ecological similarity of co-occurring species Quantifying this similarity is a daunting and potentially impossible task in species-rich assemblages During the past decade tropical tree ecologists have increasingly utilized phylogenetic trees and functional traits to estimate the ecological similarity of species in order to test mechanistic community assembly hypotheses A large amount of work has resulted with many important advances having been made along the way That said, there are still many outstanding challenges facing those utilizing phylogenetic and functional trait approaches to study community assembly Here I review the conceptual background, major advances and major remaining challenges in phylogenetic- and trait-based approaches to community ecology with a specific focus on tropical trees I argue that both approaches tremendously improve our understanding of tropical tree community ecology, but neither approach has fully reached its potential thus far

Do stream fish track climate change? Assessing distribution shifts in recent decades

Abstract: Understanding the ability of species to shift their distribution ranges in response to climate change is crucial for conservation biologists and resources managers. Although freshwater ecosystems include some of the most imperilled fauna worldwide, such range shifts have been poorly documented in streams and rivers and have never been compared to the current velocity of climate change. Based on national monitoring data, we examined the distributional changes of 32 stream fish species in France and quantified potential time lags in species responses, providing a unique opportunity to analyze range shifts over recent decades of warming in freshwater environments. A multi-facetted approach, based on several range measures along spatial gradients, allowed us to quantify range shifts of numerous species across the whole hydrographic network between an initial period (1980–1992) and a contemporary one (2003–2009), and to contrast them to the rates of isotherm shift in elevation and stream distance. Our results highlight systematic species shifts towards higher elevation and upstream, with mean shifts in range centre of 13.7 m decade−1 and 0.6 km decade−1, respectively. Fish species displayed dispersal-driven expansions along the altitudinal gradient at their upper range limit (61.5 m decade−1), while substantial range contractions at the lower limit (6.3 km decade−1) were documented for most species along the upstream–downstream gradient. Despite being consistent with the geographic variation in climate change velocities, these patterns reveal that the majority of stream fish have not shifted at a pace sufficient to track changing climate, in particular at their range centre where range shifts lag far behind expectation. Our study provides evidence that stream fish are currently responding to recent climate warming at a greater rate than many terrestrial organisms, although not as much as needed to cope with future climate modifications.

Leaf nitrogen and phosphorus concentrations of woody plants differ in responses to climate, soil and plant growth form

Abstract: Leaf chemistry is important in predicting the functioning and dynamics of ecosystems As two key traits, leaf nitrogen (N) and phosphorus (P) concentrations set the limits for plant growth, and leaf N:P ratios indicate the shift between N- and P-limitation To understand the responses of leaf chemistry to their potential drivers, we measured leaf N and P concentrations of 386 woody species at 14 forest sites across eastern China, and explored the eff ects of climate, soil, and plant growth form on leaf N, P and N:P ratios In general, leaf N and P were both negatively related to mean annual temperature and precipitation, and positively related to soil N and P concentrations Leaf N:P ratios showed opposite trends General linear models showed that variation in leaf N was mainly determined by a shift in plant growth form (from evergreen broadleaved to deciduous broadleaved to conifer species) along the latitudinal gradient, while variations in leaf P and N:P were driven by climate, plant growth form, and their interaction Th ese diff erences may refl ect diff erences in nutrient cycling and physiological regulations of P and N Our results should help understand the ecological patterns of leaf chemical traits and modeling ecosystem nutrient cycling

Inference from presence-only data; the ongoing controversy

Abstract: Presence-only data abounds in ecology, often accompanied by a background sample. Although many interesting aspects of the species’ distribution can be learned from such data, one cannot learn the overall species occurrence probability, or prevalence, without making unjustified simplifying assumptions. In this forum article we question the approach of Royle et al. (2012) that claims to be able to do this.

Habitat specifity, endemism and the neotropical distribution of Amazonian white-water floodplain trees

Abstract: The Amazon basin is covered by the most species-rich forests in the world and is considered to house many endemic tree species. Yet, most Amazonian ecosystems lack reliable estimates of their degree of endemism, and causes of tree diversity and endemism are intense matters of debate. We reviewed the spatial distribution of 658 of the most important floodtolerant Amazonian white-water (varzea) tree species across the entire Neotropics by using data from herbaria, floras, inventories and checklists. Our results show that 90% of the varzea tree species are partially or widely distributed across neotropical macro-regions and biomes. Chi-square analyses indicated that varzea species richness in non-varzea macro-regions was dependent on the flooding gradient and the longitudinal position. Cluster analysis combined with association tests indicated four significant patterns of varzea species distributions depending on species flood-tolerance (low vs high) and spatial distribution (restricted vs widespread). We predict that the predominance of Andean substrates is the most important factor that determines the distribution of varzea tree species within and beyond the Amazon basin and explains the high floristic similarity to the Orinoco floodplains. Distribution patterns in other extra-Amazonian macro-regions are more likely linked to climatic factors, with rainforest climates housing more varzea species than savanna climates. 130 tree species were restricted to South-American freshwater floodplains, and 68 ( 10%) were endemic to Amazonian varzea. We detected two centers of endemism, one in the western Amazon characterized by low and brief floods, and one in the central Amazon, characterized by high and prolonged floods. Differences in taxonomic composition of endemic centers in the western and central Amazon are the result of different abiotic factors (i.e. flood regimes), as well as the regional species pools from where the species are recruited from. We hypothesize that numerous morphological, physiological and biochemical adaptations permit survival of trees in flooded environments. Furthermore, these adaptations are independently derived across many taxa and result in a highly specialized flora. We attribute higher than expected levels of endemism to the great spatial extent and age of floodplain ecosystems in the Amazon basin, and highlight the role of Amazonian varzea as an potential driver in speciation and diversification processes. Freshwater floodplains cover an area of approximately 1.7

Landscape of fear in Europe: wolves affect spatial patterns of ungulate browsing in Białowieża Primeval Forest, Poland.

Abstract: Large carnivores can either directly influence ungulate populations or indirectly affect their behaviour. Knowledge from European systems, in contrast to North American systems, on how this might lead to cascading effects on lower trophic levels is virtually absent. We studied whether wolves Canis lupus via density-mediated and behaviorally-mediated effects on their ungulate prey species influence patterns of browsing and tree regeneration inside the Bialowieza National Park, Poland. Browsing intensity of tree saplings (height class <150 cm), irrespective of tree species or forest type, was lower inside a wolf core area (50.5%) where predator presence is highest, than in the remainder of the wolf pack’s home range (58.3%). Additionally, browsing intensity was reduced when the amount of coarse woody debris (CWD), which can act as a ?ungulate escape impediment', increased (within 5-m radius) inside the wolf core area. No relationship existed outside the core area. As a result, the proportion of trees growing out of herbivore control increased more strongly with increasing amount of CWD inside compared to outside the wolf core area. This suggests that next to direct effects of wolves on ungulate density caused by a higher predation pressure inside the core area, risk effects are important and are enhanced by habitat characteristics. These results indicate that behaviorally-mediated effects of predators on prey can become more important than density-mediated effects in affecting lower trophic levels. This is the first study we are aware of, that shows CWD can create fine-scale risk effects on ungulates with the potential for cascading effects of large predators on patterns of tree regeneration for a European forest system. This knowledge broadens the discussion on how the impact of large predators on ecosystem functioning depends on the physical landscape, by illustrating these effects for a system which largely contrasts in this respect to the North American systems.

Quantifying island isolation – insights from global patterns of insular plant species richness

Abstract: Isolation is a driving factor of species richness and other island community attributes. Most empirical studies have investigated the effect of isolation measured as distance to the nearest continent. Here we expanded this perspective by comparing the explanatory power of seventeen isolation metrics in sixty-eight variations for vascular plant species richness on 453 islands worldwide. Our objectives were to identify ecologically meaningful metrics and to quantify their relative importance for species richness in a globally representative data set. We considered the distances to the nearest mainland and to other islands, stepping stone distances, the area of surrounding landmasses, prevailing wind and ocean currents and climatic similarity between source and target areas. These factors are closely linked to colonization and maintenance of plant species richness on islands. We tested the metrics in spatial multi-predictor models accounting for area, climate, topography and island geology. Besides area, isolation was the second most important factor determining species richness on the studied islands. A model including the proportion of surrounding land area as the isolation metric had the highest predictive power, explaining 86.1% of the variation. Distances to large islands, stepping stone distances and distances to climatically similar landmasses performed slightly better than distance to the nearest mainland. The effect of isolation was weaker for large islands suggesting that speciation counteracts the negative effect of isolation on immigration on large islands. Continental islands were less affected by isolation than oceanic islands. Our results suggest that a variety of immigration mechanisms influence plant species richness on islands and we show that this can be detected at macro-scales. Although the distance to the nearest mainland is an adequate and easy-to-calculate measure of isolation, accounting for stepping stones, large islands as source landmasses, climatic similarity and the area of surrounding landmasses increases the explanatory power of isolation for species richness.

Multiple site dissimilarity quantifies compositional heterogeneity among several sites, while average pairwise dissimilarity may be misleading

Abstract: Several measures of multiple site dissimilarity have been proposed to quantify the overall heterogeneity in assemblage composition among any number of sites. It is also a common practice to quantify such overall heterogeneity by averaging pairwise dissimilarities between all pairs of sites in the pool. However, pairwise dissimilarities do not account for patterns of co-occurrence among more than two sites. In consequence, the average of pairwise dissimilarities may not accurately reflect the overall compositional heterogeneity within a pool of more than two sites. Here I use several idealized examples to illustrate why pairwise dissimilarity measures fail to properly quantify overall heterogeneity. Thereafter, the effect of this potential problem in empirical patterns is exemplified with data of world amphibians. In conclusion, when the attribute of interest is the overall heterogeneity in a pool of sites (i.e. beta diversity) or its turnover or nestedness components, only multiple site dissimilarity measures are recommended.

Multi‐generational long‐distance migration of insects: studying the painted lady butterfly in the Western Palaearctic

Abstract: Long-range, seasonal migration is a widespread phenomenon among insects, allowing them to track and exploit abundant but ephemeral resources over vast geographical areas. However, the basic patterns of how species shift across multiple locations and seasons are unknown in most cases, even though migrant species comprise an important component of the temperate-zone biota. The painted lady butterfly Vanessa cardui is such an example; a cosmopolitan continuously-brooded species which migrates each year between Africa and Europe, sometimes in enormous numbers. The migration of 2009 was one of the most impressive recorded, and thousands of observations were collected through citizen science programmes and systematic entomological surveys, such as high altitude insect-monitoring radar and ground-based butterfly monitoring schemes. Here we use V. cardui as a model species to better understand insect migration in the Western Palaearctic, and we capitalise on the complementary data sources available for this iconic butterfly. The migratory cycle in this species involves six generations, encompassing a latitudinal shift of thousands of kilometres (up to 60 degrees of latitude). The cycle comprises an annual poleward advance of the populations in spring followed by an equatorward return movement in autumn, with returning individuals potentially flying thousands of kilometres. We show that many long-distance migrants take advantage of favourable winds, moving downwind at high elevation (from some tens of metres from the ground to altitudes over 1000 m), pointing at strong similarities in the flight strategies used by V. cardui and other migrant Lepidoptera. Our results reveal the highly successful strategy that has evolved in these insects, and provide a useful framework for a better understanding of long-distance seasonal migration in the temperate regions worldwide.

Spatiotemporal dynamics in a seasonal metacommunity structure is predictable: the case of floodplain‐fish communities

Abstract: The metacommunity framework has greatly advanced our understanding about the importance of local and regional processes structuring ecological communities. However, information on how metacommunity structure and the relative strengths of their underlying mechanisms change through time is largely lacking. Dynamic systems that undergo environmental temporal changes and disturbances, such as floodplains, serve as natural laboratories to explore how their metacommunity structure change in time. Here we applied the Elements of Metacommunity Structure framework and variation partitioning analysis to assess how temporal changes in the local environmental factors and regional dispersal processes in the rain season influence a seasonal floodplain-fish metacommunity. Across four months, relevant environmental factors were measured across 21 patches where over 3500 individual fish were sampled. Connectivity was measured using landscape resistance-based metrics and additional spatial variation in metacommunity structure was assessed via spatial autocorrelation functions. The metacommunity structure changed from nestedness, at the beginning of the flood season, to a quasi-Clementsian gradient at the end. Our analyses show that connectivity is only important in the beginning of the flood season whereas environment is only important at the end. These results suggest that this metacommunity is structured by changes between dispersal limitation and environmental filtering through time.

Improving species distribution models using biotic interactions: a case study of parasites, pollinators and plants

Abstract: Biotic interactions have been considered as an important factor to be included in species distribution modelling, but little is known about how different types of interaction or different strategies for modelling affect model performance. This study compares different methods for including interspecific interactions in distribution models for bees, their brood parasites, and the plants they pollinate. Host–parasite interactions among bumble bees (genus Bombus: generalist pollinators and brood parasites) and specialist plant–pollinator interactions between Centris bees and Krameria flowers were used as case studies. We used 7 different modelling algorithms available in the BIOMOD R package. For Bombus, the inclusion of interacting species distributions generally increased model predictive accuracy. The improvement was better when the interacting species was included with its raw distribution rather than with its modeled suitability. However, incorporating the distributions of non-interacting species sometimes resulted in similarly increased model accuracy despite their being no significance of any interaction for the distribution. For the Centris-Krameria system the best strategy for modelling biotic interactions was to include the interacting species model-predicted values. However, the results were less consistent than those for Bombus species, and most models including biotic interactions showed no significant improvement over abiotic models. Our results are consistent with previous studies showing that biotic interactions can be important in structuring species distributions at regional scales. However, correlations between species distributions are not necessarily indicative of interactions. Therefore, choosing the correct biotic information, based on biological and ecological knowledge, is critical to improve the accuracy of species distribution models and forecast distribution change.

Global patterns and predictors of tropical reef fish species richness

Abstract: In the marine realm, the tropics host an extraordinary diversity of taxa but the drivers underlying the global distribution of marine organisms are still under scrutiny and we still lack an accurate global predictive model. Using a spatial database for 6336 tropical reef fishes, we attempted to predict species richness according to geometric, biogeographical and environmental explanatory variables. In particular, we aimed to evaluate and disentangle the predictive performances of temperature, habitat area, connectivity, mid-domain effect and biogeographical region on reef fish species richness. We used boosted regression trees, a flexible machine-learning technique, to build our predictive model and structural equation modeling to test for potential 'mediation effects' among predictors. Our model proved to be accurate, explaining 80% of the total deviance in fish richness using a cross-validated procedure. Coral reef area and biogeographical region were the primary predictors of reef fish species richness, followed by coast length, connectivity, mid-domain effect and sea surface temperature, with interactions between the region and other predictors. Important indirect effects of water temperature on reef fish richness, mediated by coral reef area, were also identified. The relationship between environmental predictors and species richness varied markedly among biogeographical regions. Our analysis revealed that a few easily accessible variables can accurately predict reef fish species richness. They also highlight concerns regarding ongoing environmental declines, with region-specific responses to variation in environmental conditions predicting a variable response to anthropogenic impacts.

VisTrails SAHM: visualization and workflow management for species habitat modeling

Abstract: The Software for Assisted Habitat Modeling (SAHM) has been created to both expedite habitat modeling and help maintain a record of the various input data, pre- and post-processing steps and modeling options incorporated in the construction of a species distribution model through the established workflow management and visualization VisTrails software This paper provides an overview of the VisTrails:SAHM software including a link to the open source code, a table detailing the current SAHM modules, and a simple example modeling an invasive weed species in Rocky Mountain National Park, USA

Tools for integrating range change, extinction risk and climate change information into conservation management

Abstract: Ecological niche models (ENMs) are the primary tool used to describe and forecast the potential influence of climate change on biodiversity. However, ENMs do not directly account for important biological and landscape processes likely to affect range dynamics at a variety of spatial scales. Recent advances to link ENMs with population models have focused on the fundamental step of integrating dispersal and metapopulation dynamics into forecasts of species geographic ranges. Here we use a combination of novel analyses and a synthesis of findings from published plant and animal case studies to highlight three seldom recognised, yet important, advantages of linking ENMs with demographic modelling approaches: 1) they provide direct measures of extinction risk in addition to measures of vulnerability based on change in the potential range area or total habitat suitability. 2) They capture life-history traits that permit population density to vary in different ways in response to key spatial drivers, conditioned by the processes of global change. 3) They can be used to explore and rank the cost effectiveness of regional conservation alternatives and demographically oriented management interventions. Given these advantages, we argue that coupled methods should be used preferentially where data permits and when conservation management decisions require intervention, prioritization, or direct estimates of extinction risk.

Rapid changes in bird community composition at multiple temporal and spatial scales in response to recent climate change

Abstract: Although climate change is acknowledged to affect population dynamics and species distribution, details of how community composition is affected are still lacking. We investigate whether ongoing changes in bird community composition can be explained by contemporary changes in summer temperatures, using four independent long-term bird census schemes from Sweden (up to 57 yr); two at the national scale and two at local scales. The change in bird community composition was represented by a community temperature index (CTI) that reflects the balance in abundance between low- and high-temperature dwelling species. In all schemes, CTI tracked patterns of temperature increase, stability or decrease remarkably well, with a lag period of 13 yr. This response was similar at both the national and local scale. However, the communities did not respond fast enough to cope with temperature increase, suggesting that community composition lags behind changes in temperature. The change in CTI was caused mainly by changes in species' relative abundances, and less so by changes in species composition. We conclude that ongoing changes in bird community structure are driven to a large extent by contemporary changes in climate and that CTI can be used as a simple indicator for how bird communities respond. (Less)

Historical climate‐change influences modularity and nestedness of pollination networks

Abstract: The structure of species interaction networks is important for species coexistence, community stability and exposure of species to extinctions. Two widespread structures in ecological networks are modularity, i.e. weakly connected subgroups of species that are internally highly interlinked, and nestedness, i.e. specialist species that interact with a subset of those species with which generalist species also interact. Modularity and nestedness are often interpreted as evolutionary ecological structures that may have relevance for community persistence and resilience against perturbations, such as climate-change. Therefore, historical climatic fluctuations could influence modularity and nestedness, but this possibility remains untested. This lack of research is in sharp contrast to the considerable efforts to disentangle the role of historical climate-change and contemporary climate on species distributions, richness and community composition patterns. Here, we use a global database of pollination networks to show that historical climate-change is at least as important as contemporary climate in shaping modularity and nestedness of pollination networks. Specifically, on the mainland we found a relatively strong negative association between Quaternary climate-change and modularity, whereas nestedness was most prominent in areas having experienced high Quaternary climate-change. On islands, Quaternary climate-change had weak effects on modularity and no effects on nestedness. Hence, for both modularity and nestedness, historical climate-change has left imprints on the network structure of mainland communities, but had comparably little effect on island communities. Our findings highlight a need to integrate historical climate fluctuations into eco-evolutionary hypotheses of network structures, such as modularity and nestedness, and then test these against empirical data. We propose that historical climate-change may have left imprints in the structural organisation of species interactions in an array of systems important for maintaining biological diversity.

Introducing the biogeographic species pool

Abstract: D. W. Carstensen (daniel.carstensen@gmail.com), Depto de Botânica, Laboratorio de Fenologia, Plant Phenology and Seed Dispersal Group, Inst. de Biociencias, Univ. Estadual Paulista (UNESP), Avenida 24-A no. 1515, 13506-900 Rio Claro, Sao Paulo, Brazil. – J.-P. Lessard, B. G. Holt, M. Krabbe Borregaard and C. Rahbek, Center for Macroecology, Evolution and Climate, Dept of Biology, Univ. of Copenhagen, Universitetsparken 15, DK-2100 Copenhagen, Denmark. J-PL also at: Quebec Centre for Biodiversity Science, Dept of Biology, McGill Univ., Montreal, QC H3A-1B1, Canada. BGH also at: School of Biological Sciences, Univ. of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK. MKB also at: School of Geography and the Environment, Univ. of Oxford, South Parks Road, Oxford, OX1 3CY, UK.

Wolves, white-tailed deer, and beaver: implications of seasonal prey switching for woodland caribou declines

Abstract: Population increases of primary prey can negatively impact alternate prey populations via demographic and behavioural responses of a shared predator through apparent competition. Seasonal variation in prey selection patterns by predators also can aff ect secondary and incidental prey by reducing spatial separation. Global warming and landscape changes in Alberta ’ s bitumen sands have resulted in prey enrichment, which is changing the large mammal predator – prey system and causing declines in woodland caribou Rangifer tarandus caribou populations. We assessed seasonal patterns of prey use and spatial selection by wolves Canis lupus in two woodland caribou ranges in northeastern Alberta, Canada, that have undergone prey enrichment following recent white-tailed deer Odocoileus virginianus invasion. We determined whether risk of predation for caribou (incidental prey) and the proportion of wolf-caused-caribou mortalities varied with season. We found that wolves showed seasonal variation in primary prey use, with deer and beaver Castor canadensis being the most common prey items in wolf diet in winter and summer, respectively. Th ese seasonal dietary patterns were refl ected in seasonal wolf spatial resource selection and resulted in contrasting spatial relationships between wolves and caribou. During winter, wolf selection for areas used by deer maintained strong spatial separation between wolves and caribou, whereas wolf selection for areas used by beaver in summer increased the overlap with caribou. Changing patterns in wolf resource selection were refl ected by caribou mortality patterns, with 76.2% of 42 adult female caribou mortalities occurring in summer. Understanding seasonal patterns of predation following prey enrichment in a multiprey system is essential when assessing the eff ect of predation on an incidental prey species. Our results support the conclusion that wolves are proximately responsible for woodland caribou population declines throughout much of their range.

A systematic comparison of summary characteristics for quantifying point patterns in ecology

Abstract: Many functional summary characteristics such as Ripley's K function have been used in ecology to describe the spatial structure of point patterns to aid understanding of the underlying processes However, their use is poorly guided in ecology because little is understood how well single summary characteristics, or a combination of them, capture the spatial structure of real world patterns Here, we systematically tested the performance of combinations of eight summary characteristics [ie pair correlation function g(r), K-function K(r), the proportion E(r) of points with no neighbor at distance r, the nearest neighbor distribution function D(r), the spherical contact distribution Hs(r), the kth nearest-neighbor distribution functions Dk(r), the mean distance nn(k) to the kth neighbor, and the intensity function λ(x)] To this end we used point pattern data covering a wide range of spatial structures including simulated (stationary) as well as real, possibly non-stationary, patterns on tree species in a tropical forest in Panama To measure the information contained in a given combination of summary characteristics we used simulated annealing to reconstruct the observed patterns based only on the limited information provided by this combination and assessed how well other characteristics of the observed pattern were recovered We found that the number of summary characteristics required to capture the spatial structure of stationary patterns varied between one (for patterns with near random structures) and three (for patterns with complex cluster and superposition structures), but with a robust ranking g(r), Dk(r), and Hs(r) that was largely independent on pattern idiosyncrasies Stationary summary characteristics [with ranking g(r), Dk(r), Hs(r), E(r)] captured small- to intermediate scale properties of non-stationary patterns, but for describing large-scale spatial structures the intensity function was required Our finding revealed that the current practice in ecology of using only one or two summary characteristics bears danger that essential characteristics of more complex patterns would not be detected The technique of pattern reconstruction presented here has wide applications in ecology

Building megaphylogenies for macroecology: taking up the challenge.

Abstract: The last decades have seen an upsurge in ecological studies incorporating phylogenetic information with increasing species samples, motivated by the common conjecture that species with common ancestors should share some ecological characteristics due to niche conservatism. This has been carried out using various methods of increasing complexity and reliability: using only taxonomical classification; constructing supertrees that incorporate only topological information from previously published phylogenies; or building supermatrices of molecular data that are used to estimate phylogenies with evolutionary meaningful branch lengths. Although the latter option is more informative than the others, it remains under-used in ecology because ecologists are generally unaware of or unfamiliar with modern molecular phylogenetic methods. However, a solid phylogenetic hypothesis is necessary to conduct reliable ecological analysis integrating evolutive aspects. Our aim here is to clarify the concepts and methodological issues associated with the reconstruction of dated megaphylogenies, and to show that it is nowadays possible to obtain accurate and well sampled megaphylogenies with informative branch-lengths on large species samples. This is possible thanks to improved phylogenetic methods, vast amounts of molecular data available from databases such as Genbank, and consensus knowledge on deep phylogenetic relationships for an increasing number of groups of organisms. Finally, we include a detailed step-by-step workflow pipeline (Supplementary material), from data acquisition to phylogenetic inference, mainly based on the R environment (widely used by ecologists) and the use of free web-servers, that has been applied to the reconstruction of a species-level phylogeny of all breeding birds of Europe.

Spore rain in relation to regional sources and beyond

Abstract: While patterns of spore dispersal from single sources at short distances are fairly well known, information about spore rain' from numerous sources and at larger spatial scales is generally lacking. In this study, I sampled spore rain using a novel method consisting of 0.250.5 m2 cotton cloth traps at nine sites in the boreo-nemoral vegetation zone in eastern Sweden during two seasons, using Sphagnum spores as a model. Traps were located in various landscapes (mainland, islands). Additional trapping was done in an arctic area (Svalbard) without spore production. Spore densities were tested against distance from the nearest source and area of sources (open peatlands) within different radii around each site (5, 10, 20, 50, 100, 200, 300, 400 km). The cloth method appeared reliable when accounting for precipitation losses, retaining approximately 2060% of the spores under the recorded amounts of precipitation. Estimated spore densities ranged from 6 million m2 and season within a large area source, via regional deposition of 50 000240 000 spores m2, down to 1000 m2 at Svalbard. Spore rain for all sites was strongly related to distance from the nearest source, but when excluding samples taken within a source peatland, the amount of sources within 200 km was most important. Spores were larger at isolated island sites, indicating that a higher proportion originated from distant, humid areas. Immense amounts of Sphagnum spores are dispersed across regional distances annually in boreal areas, explaining the success of the genus to colonise nutrient poor wetlands. The detectable deposition at Svalbard indicates that about 1% of the regional spore rain has a trans- or intercontinental origin. The regional spore rain, originating from numerous sources in the landscape, is probably valid for most organisms with small diaspores and provides a useful insight in ecology, habitat restoration and conservation planning.

Home range, activity and sociality of a top predator, the dingo: a test of the Resource Dispersion Hypothesis

Abstract: The idea that groups of individuals may develop around resource patches led to the formulation of the Resource Dispersion Hypothesis (RDH). We tested the predictions of the RDH, within a quasi-experimental framework, using Australia’s largest terrestrial predator, the dingo Canis lupus dingo. Average dingo group sizes were higher in areas with abundant focal food sources around two mine sites compared with those in more distant areas. This supports the notion that resource richness favours larger group size, consistent with the RDH. Irrespective of season or sex, average home range estimates and daily activity for dingoes around the mine sites were significantly less than for dingoes that lived well away. Assuming that a territory is the defended part of the home range and that territory size is correlated with home range size, consistent with the RDH, the spatial dispersion of food patches therefore determined territory size for dingoes in our study. However, although sample size was small, some dingoes that accessed the supplementary food resource at the mines also spent a large proportion of their time away, suggesting a breakdown of territorial defence around the focal food resource. This, in combination with the large variation in home range size among dingoes that accessed the same supplementary food resource, limits the predictive capabilities of the RDH for this species. We hypothesize that constraints on exclusive home range occupancy will arise if a surfeit of food resources (in excess of requirements for homeostasis) is available in a small area, and that this will have further effects on access to mates and social structure. We present a conceptual model of facultative territorial defence where focal resources are available to demonstrate our findings.

Migratory strategies of waterbirds shape the continental-scale dispersal of aquatic organisms

Abstract: The study was funded by ESF - EURODIVERSITY project BIOPOOL. DSV was supported by the Fundacao para a Ciencia e Tecnologia grant SFRH/BD/48091/2008, co-financed by the European Social Fund (ESF)

Aquatic insects in a sea of desert: population genetic structure is shaped by limited dispersal in a naturally fragmented landscape

Abstract: Habitat requirements and landscape features can exert strong influences on the population structure of organisms. For aquatic organisms in particular, hydrologic requirements can dictate the extent of available habitat, and thus the degree of genetic connectivity among populations. We used a landscape genetics approach to evaluate hypotheses regarding the influence of landscape features on connectivity among populations of the giant water bug Abedus herberti (Hemiptera: Belostomatidae). Abedus herberti is restricted to naturally-fragmented, perennial stream habitats in arid regions of North America. This species is exceptional because it is flightless at all life stages. Thus, we hypothesized a high degree of population genetic structure in A. herberti due to hydrologic constraints on habitat and low dispersal ability of the organism. A total of 617 individuals were sampled from 20 populations across southeastern Arizona, USA and genotyped at 10 microsatellite loci. We used a Bayesian clustering method to delineate genetic groups among populations. To determine which of six landscape variables (representing hypotheses of landscape-level connectivity) has the strongest association with genetic connectivity in A. herberti, we used information-theoretic model selection. Strong population structure was evident among A. herberti populations, even at small spatial scales. At a larger scale, A. herberti populations were hierarchically structured across the study region, with groups of related populations generally occurring in the same mountain range, rather than in the same major watershed. Surprisingly, stream network connectivity was not important for explaining among-population patterns. Only the Curvature landscape variable was identified as having an association with genetic connectivity in A. herberti. The Curvature variable hypothesizes that gene flow tends to occur where local topography is concave, such as within stream drainages and dry gullies. Thus, our results suggest that population connectivity may depend on the shape of local overland topography rather than direct connectivity within stream drainage networks.

Predicting current and future spatial community patterns of plant functional traits

Abstract: Community-level patterns of functional traits relate to community assembly and ecosystem functioning. By modelling the changes of different indices describing such patterns – trait means, extremes and diversity in communities – as a function of abiotic gradients, we could understand their drivers and build projections of the impact of global change on the functional components of biodiversity. We used five plant functional traits (vegetative height, specific leaf area, leaf dry matter content, leaf nitrogen content and seed mass) and non-woody vegetation plots to model several indices depicting community-level patterns of functional traits from a set of abiotic environmental variables (topographic, climatic and edaphic) over contrasting environmental conditions in a mountainous landscape. We performed a variation partitioning analysis to assess the relative importance of these variables for predicting patterns of functional traits in communities, and projected the best models under several climate change scenarios to examine future potential changes in vegetation functional properties. Not all indices of trait patterns within communities could be modelled with the same level of accuracy: the models for mean and extreme values of functional traits provided substantially better predictive accuracy than the models calibrated for diversity indices. Topographic and climatic factors were more important predictors of functional trait patterns within communities than edaphic predictors. Overall, model projections forecast an increase in mean vegetation height and in mean specific leaf area following climate warming. This trend was important at mid elevation particularly between 1000 and 2000 m a.s.l. With this study we showed that topographic, climatic and edaphic variables can successfully model descriptors of community-level patterns of plant functional traits such as mean and extreme trait values. However, which factors determine the diversity of functional traits in plant communities remains unclear and requires more investigations.