Functional traits and climate drive interspecific differences in disturbance-induced tree mortality.

With climate change, natural disturbances such as storm or fire are reshuffled, inducing pervasive shifts in forest dynamics. To predict how it will impact forest structure and composition, it is crucial to understand how tree species differ in their sensitivity to disturbances. In this study, we investigated how functional traits and species mean climate affect their sensitivity to disturbances while controlling for tree size and stand structure. With data on 130,594 trees located on 7617 plots that were disturbed by storm, fire, snow, biotic or other disturbances from the French, Spanish, and Finnish National Forest Inventory, we modeled annual mortality probability for 40 European tree species as a function of tree size, dominance status, disturbance type, and intensity. We tested the correlation of our estimated species probability of disturbance mortality with their traits and their mean climate niches. We found that different trait combinations controlled species sensitivity to disturbances. Storm-sensitive species had a high height-dbh ratio, low wood density and high maximum growth, while fire-sensitive species had low bark thickness and high P50. Species from warmer and drier climates, where fires are more frequent, were more resistant to fire. The ranking in disturbance sensitivity between species was overall consistent across disturbance types. Productive conifer species were the most disturbance sensitive, while Mediterranean oaks were the least disturbance sensitive. Our study identified key relations between species functional traits and disturbance sensitivity, that allows more reliable predictions of how changing climate and disturbance regimes will impact future forest structure and species composition at large spatial scales.

The function-dominance correlation drives the direction and strength of biodiversity-ecosystem functioning relationships.

Community composition is a primary determinant of how biodiversity change influences ecosystem functioning and, therefore, the relationship between biodiversity and ecosystem functioning (BEF). We examine the consequences of community composition across six structurally realistic plant community models. We find that a positive correlation between species' functioning in monoculture versus their dominance in mixture with regard to a specific function (the "function-dominance correlation") generates a positive relationship between realised diversity and ecosystem functioning across species richness treatments. However, because realised diversity declines when few species dominate, a positive function-dominance correlation generates a negative relationship between realised diversity and ecosystem functioning within species richness treatments. Removing seed inflow strengthens the link between the function-dominance correlation and BEF relationships across species richness treatments but weakens it within them. These results suggest that changes in species' identities in a local species pool may more strongly affect ecosystem functioning than changes in species richness.

Importance and effectiveness of correction methods for spatial sampling bias in species with sex-specific habitat preference.

AIM: Presence records from surveys with spatially heterogeneous sampling intensity are a key challenge for species distribution models (SDMs). When sex groups differ in their habitat association, the correction of the spatial bias becomes important for preventing model predictions that are biased toward one sex. The objectives of this study were to investigate the effectiveness of existing correction methods for spatial sampling bias for SDMs when male and female have different habitat preferences. LOCATION: Jura massif, France. METHODS: We used a spatially sex-segregated virtual species to understand the effect of three sampling designs (spatially biased, uniform random, and systematic), and two correction methods (targeted background points, and distance to trajectories) on estimated habitat preferences, sex ratios, and prediction accuracy. We then evaluated these effects for two empirical Capercaillie (Tetrao urogallus) presence-only datasets from a systematic and a spatially biased sampling design. RESULTS: Sampling design strongly affected parameter estimation accuracy for the virtual species: noncorrected spatially biased sampling resulted in biased estimates of habitat association and sex ratios. Both established methods of bias correction were successful in the case of virtual species, with the targeted correction methods showing stronger correction, as it more closely followed the simulated decay of detectability with distance from sampling locations. On the Capercaillie dataset, only the targeted background points method resulted in the same sex ratio estimate for the spatially biased sampling design as for the spatially unbiased sampling. MAIN CONCLUSIONS: We suggest that information on subgroups with distinct habitat associations should be included in SDMs analyses when possible. We conclude that current methods for correcting spatially biased sampling can improve estimates of both habitat association and subgroup ratios (e.g., sex and age), but that their efficiency depends on their ability to well represent the spatial observation bias.

Tree mortality submodels drive simulated long-term forest dynamics: assessing 15 models from the stand to global scale.

Models are pivotal for assessing future forest dynamics under the impacts of changing climate and management practices, incorporating representations of tree growth, mortality, and regeneration. Quantitative studies on the importance of mortality submodels are scarce. We evaluated 15 dynamic vegetation models (DVMs) regarding their sensitivity to different formulations of tree mortality under different degrees of climate change. The set of models comprised eight DVMs at the stand scale, three at the landscape scale, and four typically applied at the continental to global scale. Some incorporate empirically derived mortality models, and others are based on experimental data, whereas still others are based on theoretical reasoning. Each DVM was run with at least two alternative mortality submodels. Model behavior was evaluated against empirical time series data, and then, the models were subjected to different scenarios of climate change. Most DVMs matched empirical data quite well, irrespective of the mortality submodel that was used. However, mortality submodels that performed in a very similar manner against past data often led to sharply different trajectories of forest dynamics under future climate change. Most DVMs featured high sensitivity to the mortality submodel, with deviations of basal area and stem numbers on the order of 10-40% per century under current climate and 20-170% under climate change. The sensitivity of a given DVM to scenarios of climate change, however, was typically lower by a factor of two to three. We conclude that (1) mortality is one of the most uncertain processes when it comes to assessing forest response to climate change, and (2) more data and a better process understanding of tree mortality are needed to improve the robustness of simulated future forest dynamics. Our study highlights that comparing several alternative mortality formulations in DVMs provides valuable insights into the effects of process uncertainties on simulated future forest dynamics.

Classification of rare land cover types: Distinguishing annual and perennial crops in an agricultural catchment in South Korea.

Many environmental data are inherently imbalanced, with some majority land use and land cover types dominating over rare ones. In cultivated ecosystems minority classes are often the target as they might indicate a beginning land use change. Most standard classifiers perform best on a balanced distribution of classes, and fail to detect minority classes. We used the synthetic minority oversampling technique (smote) with Random Forest to classify land cover classes in a small agricultural catchment in South Korea using modis time series. This area faces a major soil erosion problem and policy measures encourage farmers to replace annual by perennial crops to mitigate this issue. Our major goal was therefore to improve the classification performance on annual and perennial crops. We compared four different classification scenarios on original imbalanced and synthetically oversampled balanced data to quantify the effect of smote on classification performance. smote substantially increased the true positive rate of all oversampled minority classes. However, the performance on minor classes remained lower than on the majority class. We attribute this result to a class overlap already present in the original data set that is not resolved by smote. Our results show that resampling algorithms could help to derive more accurate land use and land cover maps from freely available data. These maps can be used to provide information on the distribution of land use classes in heterogeneous agricultural areas and could potentially benefit decision making.

Scale-dependent effects of landscape composition and configuration on natural enemy diversity, crop herbivory, and yields.

(1) Land-use intensification in agricultural landscapes has led to changes in the way habitats and resources are distributed in space. Pests and their natural enemies are influenced by these changes, and by the farming intensity of crop fields. However, it is unknown whether the composition of landscapes (amount and diversity of land cover types) or their configuration (spatial arrangement of cover types) are more important for natural enemy diversity, and how they impact crop damage and yields. In addition, effects of interactions between local farming practices (organic vs. conventional) and landscape variables are unclear. (2) Here, we make use of a data set where landscape composition and configuration were uncorrelated across multiple spatial scales. Natural enemies, crop damage, and yields were sampled in 35 organic and conventional crop fields. Out of seven broad natural enemy taxa, five were positively affected by a complex landscape configuration. In contrast, only carabids were positively affected by the amount of seminatural habitat around fields. Increasing diversity of land cover types had positive effects on some, but negative effects on other taxa. Effect sizes varied among taxa but increased with increasing spatial scale, defined by circular areas of increasing radius around fields. (3) The diversity of aerial, but not of ground-dwelling enemies was higher in fields under organic than conventional management. Interactions of local and landscape variables were important for birds, but not other enemies. Bird richness was higher in organic fields in simple landscapes, but not in landscapes with complex configuration or high land cover diversity. (4) Crop damage decreased with landscape diversity, but increased in conventional fields with complex configuration. Yields increased with both parameters in conventional fields only, and were higher on average in organic compared to conventional fields. Enemy diversity was positively related to crop damage, indicating positive density-dependence of enemies on pests. However, the diversity of aerial enemies was also positively related to yields. (5) Our results suggest that the effectiveness of agrienvironmental schemes for managing natural enemy diversity, crop damage and yields could be enhanced by optimizing the effects of distinct landscape parameters, particularly landscape configuration and diversity, across scales.

Extensive management of field margins enhances their potential for off-site soil erosion mitigation.

Soil erosion is a widespread problem in agricultural landscapes, particularly in regions with strong rainfall events. Vegetated field margins can mitigate negative impacts of soil erosion off-site by trapping eroded material. Here we analyse how local management affects the trapping capacity of field margins in a monsoon region of South Korea, contrasting intensively and extensively managed field margins on both steep and shallow slopes. Prior to the beginning of monsoon season, we equipped a total of 12 sites representing three replicates for each of four different types of field margins ("intensive managed flat", "intensive managed steep", "extensive managed flat" and "extensive managed steep") with Astroturf mats. The mats (n = 15/site) were placed before, within and after the field margin. Sediment was collected after each rain event until the end of the monsoon season. The effect of management and slope on sediment trapping was analysed using linear mixed effects models, using as response variable either the sediment collected within the field margin or the difference in sediment collected after and before the field margin. There was no difference in the amount of sediment reaching the different field margin types. In contrast, extensively managed field margins showed a large reduction in collected sediment before and after the field margins. This effect was pronounced in steep field margins, and increased with the size of rainfall events. We conclude that a field margin management promoting a dense vegetation cover is a key to mitigating negative off-site effects of soil erosion in monsoon regions, particularly in field margins with steep slopes.

Country, cover or protection: what shapes the distribution of red deer and roe deer in the Bohemian Forest Ecosystem?

The Bohemian Forest Ecosystem encompasses various wildlife management systems. Two large, contiguous national parks (one in Germany and one in the Czech Republic) form the centre of the area, are surrounded by private hunting grounds, and hunting regulations in each country differ. Here we aimed at unravelling the influence of management-related and environmental factors on the distribution of red deer (Cervus elaphus) and roe deer (Capreolus capreolus) in this ecosystem. We used the standing crop method based on counts of pellet groups, with point counts every 100 m along 218 randomly distributed transects. Our analysis, which accounted for overdispersion as well as zero inflation and spatial autocorrelation, corroborated the view that both human management and the physical and biological environment drive ungulate distribution in mountainous areas in Central Europe. In contrast to our expectations, protection by national parks was the least important variable for red deer and the third important out of four variables for roe deer; protection negatively influenced roe deer distribution in both parks and positively influenced red deer distribution in Germany. Country was the most influential variable for both red and roe deer, with higher counts of pellet groups in the Czech Republic than in Germany. Elevation, which indicates increasing environmental harshness, was the second most important variable for both species. Forest cover was the least important variable for roe deer and the third important variable for red deer; the relationship for roe deer was positive and linear, and optimal forest cover for red deer was about 70% within a 500 m radius. Our results have direct implications for the future conservation management of deer in protected areas in Central Europe and show in particular that large non-intervention zones may not cause agglomerations of deer that could lead to conflicts along the border of protected, mountainous areas.

Pest control of aphids depends on landscape complexity and natural enemy interactions.

Aphids are a major concern in agricultural crops worldwide, and control by natural enemies is an essential component of the ecological intensification of agriculture. Although the complexity of agricultural landscapes is known to influence natural enemies of pests, few studies have measured the degree of pest control by different enemy guilds across gradients in landscape complexity. Here, we use multiple natural-enemy exclosures replicated in 18 fields across a gradient in landscape complexity to investigate (1) the strength of natural pest control across landscapes, measured as the difference between pest pressure in the presence and in the absence of natural enemies; (2) the differential contributions of natural enemy guilds to pest control, and the nature of their interactions across landscapes. We show that natural pest control of aphids increased up to six-fold from simple to complex landscapes. In the absence of pest control, aphid population growth was higher in complex than simple landscapes, but was reduced by natural enemies to similar growth rates across all landscapes. The effects of enemy guilds were landscape-dependent. Particularly in complex landscapes, total pest control was supplied by the combined contribution of flying insects and ground-dwellers. Birds had little overall impact on aphid control. Despite evidence for intraguild predation of flying insects by ground-dwellers and birds, the overall effect of enemy guilds on aphid control was complementary. Understanding pest control services at large spatial scales is critical to increase the success of ecological intensification schemes. Our results suggest that, where aphids are the main pest of concern, interactions between natural enemies are largely complementary and lead to a strongly positive effect of landscape complexity on pest control. Increasing the availability of seminatural habitats in agricultural landscapes may thus benefit not only natural enemies, but also the effectiveness of aphid natural pest control.

Species-specific traits plus stabilizing processes best explain coexistence in biodiverse fire-prone plant communities.

Coexistence in fire-prone Mediterranean-type shrublands has been explored in the past using both neutral and niche-based models. However, distinct differences between plant functional types (PFTs), such as fire-killed vs resprouting responses to fire, and the relative similarity of species within a PFT, suggest that coexistence models might benefit from combining both neutral and niche-based (stabilizing) approaches. We developed a multispecies metacommunity model where species are grouped into two PFTs (fire-killed vs resprouting) to investigate the roles of neutral and stabilizing processes on species richness and rank-abundance distributions. Our results show that species richness can be maintained in two ways: i) strictly neutral species within each PFT, or ii) species within PFTs differing in key demographic properties, provided that additional stabilizing processes, such as negative density regulation, also operate. However, only simulations including stabilizing processes resulted in structurally realistic rank-abundance distributions over plausible time scales. This result underscores the importance of including both key species traits and stabilizing (niche) processes in explaining species coexistence and community structure.

Natural enemy interactions constrain pest control in complex agricultural landscapes.

Biological control of pests by natural enemies is a major ecosystem service delivered to agriculture worldwide. Quantifying and predicting its effectiveness at large spatial scales is critical for increased sustainability of agricultural production. Landscape complexity is known to benefit natural enemies, but its effects on interactions between natural enemies and the consequences for crop damage and yield are unclear. Here, we show that pest control at the landscape scale is driven by differences in natural enemy interactions across landscapes, rather than by the effectiveness of individual natural enemy guilds. In a field exclusion experiment, pest control by flying insect enemies increased with landscape complexity. However, so did antagonistic interactions between flying insects and birds, which were neutral in simple landscapes and increasingly negative in complex landscapes. Negative natural enemy interactions thus constrained pest control in complex landscapes. These results show that, by altering natural enemy interactions, landscape complexity can provide ecosystem services as well as disservices. Careful handling of the tradeoffs among multiple ecosystem services, biodiversity, and societal concerns is thus crucial and depends on our ability to predict the functional consequences of landscape-scale changes in trophic interactions.

Intraspecific variation buffers projected climate change impacts on Pinus contorta.

Species distribution modeling (SDM) is an important tool to assess the impact of global environmental change. Many species exhibit ecologically relevant intraspecific variation, and few studies have analyzed its relevance for SDM. Here, we compared three SDM techniques for the highly variable species Pinus contorta. First, applying a conventional SDM approach, we used MaxEnt to model the subject as a single species (species model), based on presence-absence observations. Second, we used MaxEnt to model each of the three most prevalent subspecies independently and combined their projected distributions (subspecies model). Finally, we used a universal growth transfer function (UTF), an approach to incorporate intraspecific variation utilizing provenance trial tree growth data. Different model approaches performed similarly when predicting current distributions. MaxEnt model discrimination was greater (AUC - species model: 0.94, subspecies model: 0.95, UTF: 0.89), but the UTF was better calibrated (slope and bias - species model: 1.31 and -0.58, subspecies model: 1.44 and -0.43, UTF: 1.01 and 0.04, respectively). Contrastingly, for future climatic conditions, projections of lodgepole pine habitat suitability diverged. In particular, when the species' intraspecific variability was acknowledged, the species was projected to better tolerate climatic change as related to suitable habitat without migration (subspecies model: 26% habitat loss or UTF: 24% habitat loss vs. species model: 60% habitat loss), and given unlimited migration may increase amount of suitable habitat (subspecies model: 8% habitat gain or UTF: 12% habitat gain vs. species model: 51% habitat loss) in the climatic period 2070-2100 (SRES A2 scenario, HADCM3). We conclude that models derived from within-species data produce different and better projections, and coincide with ecological theory. Furthermore, we conclude that intraspecific variation may buffer against adverse effects of climate change. A key future research challenge lies in assessing the extent to which species can utilize intraspecific variation under rapid environmental change.

Integrating movement ecology with biodiversity research - exploring new avenues to address spatiotemporal biodiversity dynamics.

Movement of organisms is one of the key mechanisms shaping biodiversity, e.g. the distribution of genes, individuals and species in space and time. Recent technological and conceptual advances have improved our ability to assess the causes and consequences of individual movement, and led to the emergence of the new field of 'movement ecology'. Here, we outline how movement ecology can contribute to the broad field of biodiversity research, i.e. the study of processes and patterns of life among and across different scales, from genes to ecosystems, and we propose a conceptual framework linking these hitherto largely separated fields of research. Our framework builds on the concept of movement ecology for individuals, and demonstrates its importance for linking individual organismal movement with biodiversity. First, organismal movements can provide 'mobile links' between habitats or ecosystems, thereby connecting resources, genes, and processes among otherwise separate locations. Understanding these mobile links and their impact on biodiversity will be facilitated by movement ecology, because mobile links can be created by different modes of movement (i.e., foraging, dispersal, migration) that relate to different spatiotemporal scales and have differential effects on biodiversity. Second, organismal movements can also mediate coexistence in communities, through 'equalizing' and 'stabilizing' mechanisms. This novel integrated framework provides a conceptual starting point for a better understanding of biodiversity dynamics in light of individual movement and space-use behavior across spatiotemporal scales. By illustrating this framework with examples, we argue that the integration of movement ecology and biodiversity research will also enhance our ability to conserve diversity at the genetic, species, and ecosystem levels.

Biotic interactions in the face of climate change: a comparison of three modelling approaches.

Climate change is expected to alter biotic interactions, and may lead to temporal and spatial mismatches of interacting species. Although the importance of interactions for climate change risk assessments is increasingly acknowledged in observational and experimental studies, biotic interactions are still rarely incorporated in species distribution models. We assessed the potential impacts of climate change on the obligate interaction between Aeshna viridis and its egg-laying plant Stratiotes aloides in Europe, based on an ensemble modelling technique. We compared three different approaches for incorporating biotic interactions in distribution models: (1) We separately modelled each species based on climatic information, and intersected the future range overlap ('overlap approach'). (2) We modelled the potential future distribution of A. viridis with the projected occurrence probability of S. aloides as further predictor in addition to climate ('explanatory variable approach'). (3) We calibrated the model of A. viridis in the current range of S. aloides and multiplied the future occurrence probabilities of both species ('reference area approach'). Subsequently, all approaches were compared to a single species model of A. viridis without interactions. All approaches projected a range expansion for A. viridis. Model performance on test data and amount of range gain differed depending on the biotic interaction approach. All interaction approaches yielded lower range gains (up to 667% lower) than the model without interaction. Regarding the contribution of algorithm and approach to the overall uncertainty, the main part of explained variation stems from the modelling algorithm, and only a small part is attributed to the modelling approach. The comparison of the no-interaction model with the three interaction approaches emphasizes the importance of including obligate biotic interactions in projective species distribution modelling. We recommend the use of the 'reference area approach' as this method allows a separation of the effect of climate and occurrence of host plant.

Statistical inference for stochastic simulation models--theory and application.

Statistical models are the traditional choice to test scientific theories when observations, processes or boundary conditions are subject to stochasticity. Many important systems in ecology and biology, however, are difficult to capture with statistical models. Stochastic simulation models offer an alternative, but they were hitherto associated with a major disadvantage: their likelihood functions can usually not be calculated explicitly, and thus it is difficult to couple them to well-established statistical theory such as maximum likelihood and Bayesian statistics. A number of new methods, among them Approximate Bayesian Computing and Pattern-Oriented Modelling, bypass this limitation. These methods share three main principles: aggregation of simulated and observed data via summary statistics, likelihood approximation based on the summary statistics, and efficient sampling. We discuss principles as well as advantages and caveats of these methods, and demonstrate their potential for integrating stochastic simulation models into a unified framework for statistical modelling.

Alien species in a warmer world: risks and opportunities.

Climate change and biological invasions are key processes affecting global biodiversity, yet their effects have usually been considered separately. Here, we emphasise that global warming has enabled alien species to expand into regions in which they previously could not survive and reproduce. Based on a review of climate-mediated biological invasions of plants, invertebrates, fishes and birds, we discuss the ways in which climate change influences biological invasions. We emphasise the role of alien species in a more dynamic context of shifting species' ranges and changing communities. Under these circumstances, management practices regarding the occurrence of 'new' species could range from complete eradication to tolerance and even consideration of the 'new' species as an enrichment of local biodiversity and key elements to maintain ecosystem services.

Road traffic and nearby grassland bird patterns in a suburbanizing landscape.

An extensive road system with rapidly increasing traffic produces diverse ecological effects that cover a large land area. Our objective was to evaluate the effect of roads with different traffic volumes on surrounding avian distributions, and its importance relative to other variables. Grassland bird data (5 years) for 84 open patches in an outer suburban/rural landscape near Boston were analyzed relative to: distance from roads with 3000-8000 to >30,000 vehicles/day; open-habitat patch size; area of quality microhabitat within a patch; adjacent land use; and distance to other open patches. Grassland bird presence and regular breeding correlated significantly with both distance from road and habitat patch size. Distance to nearest other open patch, irrespective of size, was not significant. Similarly, except for one species, adjacent land use, in this case built area, was not significant. A light traffic volume of 3000-8000 vehicles/day (local collector street here) had no significant effect on grassland bird distribution. For moderate traffic of 8000-15,000 (through street), there was no effect on bird presence although regular breeding was reduced for 400 m from a road. For heavier traffic of 15,000-30,000 (two-lane highway), both bird presence and breeding were decreased for 700 m. For a heavy traffic volume of > or =30,000 vehicles/day (multilane highway), bird presence and breeding were reduced for 1200 m from a road. The results suggest that avian studies and long-term surveys near busy roads may be strongly affected by traffic volume or changes in volume. We conclude that road ecology, especially the effects extending outward >100 m from roads with traffic, is a sine qua non for effective land-use and transportation policy.