Combining food web and species distribution models for improved community projections

The ability to model biodiversity patterns is of prime importance in this era of severe environmental crisis. Species assemblage along environmental gradient is subject to the interplay of biotic interactions in complement to abiotic environmental filtering. Accounting for complex biotic interactions for a wide array of species remains so far challenging. Here, we propose to use food web models that can infer the potential interaction links between species as a constraint in species distribution models. Using a plant-herbivore (butterfly) interaction dataset, we demonstrate that this combined approach is able to improve both species distribution and community forecasts. Most importantly, this combined approach is very useful in rendering models of more generalist species that have multiple potential interaction links, where gap in the literature may be recurrent. Our combined approach points a promising direction forward to model the spatial variation of entire species interaction networks. Our work has implications for studies of range shifting species and invasive species biology where it may be unknown how a given biota might interact with a potential invader or in future climate.

Warming experiments underpredict plant phenological responses to climate change.

Warming experiments are increasingly relied on to estimate plant responses to global climate change. For experiments to provide meaningful predictions of future responses, they should reflect the empirical record of responses to temperature variability and recent warming, including advances in the timing of flowering and leafing. We compared phenology (the timing of recurring life history events) in observational studies and warming experiments spanning four continents and 1,634 plant species using a common measure of temperature sensitivity (change in days per degree Celsius). We show that warming experiments underpredict advances in the timing of flowering and leafing by 8.5-fold and 4.0-fold, respectively, compared with long-term observations. For species that were common to both study types, the experimental results did not match the observational data in sign or magnitude. The observational data also showed that species that flower earliest in the spring have the highest temperature sensitivities, but this trend was not reflected in the experimental data. These significant mismatches seem to be unrelated to the study length or to the degree of manipulated warming in experiments. The discrepancy between experiments and observations, however, could arise from complex interactions among multiple drivers in the observational data, or it could arise from remediable artefacts in the experiments that result in lower irradiance and drier soils, thus dampening the phenological responses to manipulated warming. Our results introduce uncertainty into ecosystem models that are informed solely by experiments and suggest that responses to climate change that are predicted using such models should be re-evaluated.

Reconstructing the origins of high-alpine niches and cushion life form in the genus Androsace S.L. (Primulaceae).

Relatively, few species have been able to colonize extremely cold alpine environments. We investigate the role played by the cushion life form in the evolution of climatic niches in the plant genus Androsace s.l., which spreads across the mountain ranges of the Northern Hemisphere. Using robust methods that account for phylogenetic uncertainty, intraspecific variability of climatic requirements and different life-history evolution scenarios, we show that climatic niches of Androsace s.l. exhibit low phylogenetic signal and that they evolved relatively recently and punctually. Models of niche evolution fitted onto phylogenies show that the cushion life form has been a key innovation providing the opportunity to occupy extremely cold environments, thus contributing to rapid climatic niche diversification in the genus Androsace s.l. We then propose a plausible scenario for the adaptation of plants to alpine habitats.

Predicting reptile distributions at the mesoscale: relation to climate and topography

Aim To explore the respective power of climate and topography to predict the distribution of reptiles in Switzerland, hence at a mesoscale level. A more detailed knowledge of these relationships, in combination with maps of the potential distribution derived from the models, is a valuable contribution to the design of conservation strategies. Location All of Switzerland. Methods Generalized linear models are used to derive predictive habitat distribution models from eco-geographical predictors in a geographical information system, using species data from a field survey conducted between 1980 and 1999. Results The maximum amount of deviance explained by climatic models is 65%, and 50% by topographical models. Low values were obtained with both sets of predictors for three species that are widely distributed in all parts of the country (Anguis fragilis , Coronella austriaca , and Natrix natrix), a result that suggests that including other important predictors, such as resources, should improve the models in further studies. With respect to topographical predictors, low values were also obtained for two species where we anticipated a strong response to aspect and slope, Podarcis muralis and Vipera aspis . Main conclusions Overall, both models and maps derived from climatic predictors more closely match the actual reptile distributions than those based on topography. These results suggest that the distributional limits of reptile species with a restricted range in Switzerland are largely set by climatic, predominantly temperature-related, factors.

Arctic warming will promote Atlantic-Pacific fish interchange

Throughout much of the Quaternary Period, inhospitable environmental conditions above the Arctic Circle have been a formidable barrier separating most marine organisms in the North Atlantic from those in the North Pacific(1,2). Rapid warming has begun to lift this barrier(3), potentially facilitating the interchange of marine biota between the two seas(4). Here, we forecast the potential northward progression of 515 fish species following climate change, and report the rate of potential species interchange between the Atlantic and the Pacific via the Northwest Passage and the Northeast Passage. For this, we projected niche-based models under climate change scenarios and simulated the spread of species through the passages when climatic conditions became suitable. Results reveal a complex range of responses during this century, and accelerated interchange after 2050. By 2100 up to 41 species could enter the Pacific and 44 species could enter the Atlantic, via one or both passages. Consistent with historical and recent biodiversity interchanges(5,6), this exchange of fish species may trigger changes for biodiversity and food webs in the North Atlantic and North Pacific, with ecological and economic consequences to ecosystems that at present contribute 39% to global marine fish landings.

Will climate change drive alien invasive plants into areas of high protection value? An improved model-based regional assessment to prioritise the management of invasions.

Species distribution models (SDMs) studies suggest that, without control measures, the distribution of many alien invasive plant species (AIS) will increase under climate and land-use changes. Due to limited resources and large areas colonised by invaders, management and monitoring resources must be prioritised. Choices depend on the conservation value of the invaded areas and can be guided by SDM predictions. Here, we use a hierarchical SDM framework, complemented by connectivity analysis of AIS distributions, to evaluate current and future conflicts between AIS and high conservation value areas. We illustrate the framework with three Australian wattle (Acacia) species and patterns of conservation value in Northern Portugal. Results show that protected areas will likely suffer higher pressure from all three Acacia species under future climatic conditions. Due to this higher predicted conflict in protected areas, management might be prioritised for Acacia dealbata and Acacia melanoxylon. Connectivity of AIS suitable areas inside protected areas is currently lower than across the full study area, but this would change under future environmental conditions. Coupled SDM and connectivity analysis can support resource prioritisation for anticipation and monitoring of AIS impacts. However, further tests of this framework over a wide range of regions and organisms are still required before wide application.

Climate change impact on biodiversity in Switzerland: a review. Journal for Nature Conservation

A noticeable increase in mean temperature has already been observed in Switzerland and summer temperatures up to 4.8 K warmer are expected by 2090. This article reviews the observed impacts of climate change on biodiversity and consider some perspectives for the future at the national level. The following impacts are already evident for all considered taxonomic groups: elevation shifts of distribution toward mountain summits, spread of thermophilous species, colonisation by new species from warmer areas and phenological shifts. Additionally, in the driest areas, increasing droughts are affecting tree survival and fish species are suffering from warm temperatures in lowland regions. These observations are coherent with model projections, and future changes will probably follow the current trends. These changes will likely cause extinctions for alpine species (competition, loss of habitat) and lowland species (temperature or drought stress). In the very urbanised Swiss landscape, the high fragmentation of the natural ecosystems will hinder the dispersal of many species towards mountains. Moreover, disruptions in species interactions caused by individual migration rates or phenological shifts are likely to have consequences for biodiversity. Conversely, the inertia of the ecosystems (species longevity, restricted dispersal) and the local persistence of populations will probably result in lower extinction rates than expected with some models, at least in 21st century. It is thus very difficult to estimate the impact of climate change in terms of species extinctions. A greater recognition by society of the intrinsic value of biodiversity and of its importance for our existence will be essential to put in place effective mitigation measures and to safeguard a maximum number of native species.

Self-expanding mini-cannula for remote perfusion with pediatric scenarios.

The aim of this report is to address the benefits of the minimal invasive venous drainage in a pediatric cardio surgical scenario. Juvenile bovine experiments (67.4+/-11 kg) were performed. The right atrium was cannulated in a trans-jugular way by using the self-expandable (Smart Stat, 12/20F, 430 mm) venous cannula (Smartcannula LLC, Lausanne, Switzerland) vs. a 14F 250 mm (Polystan Lighthouse) standard pediatric venous cannula. Establishing the cardiopulmonary bypass (CPB), the blood flows were assessed for 20 mmHg, 30 mmHg and 40 mmHg of driving pressure. Venous drainage (flow in l/min) at 20 mmHg, 30 mmHg, and 40 mmHg drainage load was 0.26+/-0.1, 0.35+/-0.2 and 0.28+/-0.08 for the 14F standard vs. 1.31+/-0.22, 1.35+/-0.24 and 1.9+/-0.2 for the Smart Stat 12/20F cannula. The 43 cm self-expanding 12/20F Smartcannula outperforms the 14F standard cannula. The results described herein allow us to conclude that usage of the self-expanding Smartcannula also in the pediatric patients improves the flow and the drainage capacity, avoiding the insufficient and excessive drainage. We believe that similar results may be expected in the clinical settings.

Overcoming the rare species modelling paradox: test of a novel hierarchical framework with an Iberian endemic plant

Rare species have restricted geographic ranges, habitat specialization, and/or small population sizes. Datasets on rare species distribution usually have few observations, limited spatial accuracy and lack of valid absences; conversely they provide comprehensive views of species distributions allowing to realistically capture most of their realized environmental niche. Rare species are the most in need of predictive distribution modelling but also the most difficult to model. We refer to this contrast as the "rare species modelling paradox" and propose as a solution developing modelling approaches that deal with a sufficiently large set of predictors, ensuring that statistical models aren't overfitted. Our novel approach fulfils this condition by fitting a large number of bivariate models and averaging them with a weighted ensemble approach. We further propose that this ensemble forecasting is conducted within a hierarchic multi-scale framework. We present two ensemble models for a test species, one at regional and one at local scale, each based on the combination of 630 models. In both cases, we obtained excellent spatial projections, unusual when modelling rare species. Model results highlight, from a statistically sound approach, the effects of multiple drivers in a same modelling framework and at two distinct scales. From this added information, regional models can support accurate forecasts of range dynamics under climate change scenarios, whereas local models allow the assessment of isolated or synergistic impacts of changes in multiple predictors. This novel framework provides a baseline for adaptive conservation, management and monitoring of rare species at distinct spatial and temporal scales.

Species distributions and interactions in a changing world : from understanding to forecasting

Les écosystèmes fournissent de nombreuses ressources et services écologiques qui sont utiles à la population humaine. La biodiversité est une composante essentielle des écosystèmes et maintient de nombreux services. Afin d'assurer la permanence des services écosystémiques, des mesures doivent être prises pour conserver la biodiversité. Dans ce but, l'acquisition d'informations détaillées sur la distribution de la biodiversité dans l'espace est essentielle. Les modèles de distribution d'espèces (SDMs) sont des modèles empiriques qui mettent en lien des observations de terrain (présences ou absences d'une espèce) avec des descripteurs de l'environnement, selon des courbes de réponses statistiques qui décrive la niche réalisée des espèces. Ces modèles fournissent des projections spatiales indiquant les lieux les plus favorables pour les espèces considérées. Le principal objectif de cette thèse est de fournir des projections plus réalistes de la distribution des espèces et des communautés en montagne pour le climat présent et futur en considérant non-seulement des variables abiotiques mais aussi biotiques. Les régions de montagne et l'écosystème alpin sont très sensibles aux changements globaux et en même temps assurent de nombreux services écosystémiques. Cette thèse est séparée en trois parties : (i) fournir une meilleure compréhension du rôle des interactions biotiques dans la distribution des espèces et l'assemblage des communautés en montagne (ouest des Alpes Suisses), (ii) permettre le développement d'une nouvelle approche pour modéliser la distribution spatiale de la biodiversité, (iii) fournir des projections plus réalistes de la distribution future des espèces ainsi que de la composition des communautés. En me focalisant sur les papillons, bourdons et plantes vasculaires, j'ai détecté des interactions biotiques importantes qui lient les espèces entre elles. J'ai également identifié la signature du filtre de l'environnement sur les communautés en haute altitude confirmant l'utilité des SDMs pour reproduire ce type de processus. A partir de ces études, j'ai contribué à l'amélioration méthodologique des SDMs dans le but de prédire les communautés en incluant les interactions biotiques et également les processus non-déterministes par une approche probabiliste. Cette approche permet de prédire non-seulement la distribution d'espèces individuelles, mais également celle de communautés dans leur entier en empilant les projections (S-SDMs). Finalement, j'ai utilisé cet outil pour prédire la distribution d'espèces et de communautés dans le passé et le futur. En particulier, j'ai modélisé la migration post-glaciaire de Trollius europaeus qui est à l'origine de la structure génétique intra-spécifique chez cette espèce et évalué les risques de perte face au changement climatique. Finalement, j'ai simulé la distribution des communautés de bourdons pour le 21e siècle afin d'évaluer les changements probables dans ce groupe important de pollinisateurs. La diversité fonctionnelle des bourdons va être altérée par la perte d'espèces spécialistes de haute altitude et ceci va influencer la pollinisation des plantes en haute altitude. - Ecosystems provide a multitude of resources and ecological services, which are useful to human. Biodiversity is an essential component of those ecosystems and guarantee many services. To assure the permanence of ecosystem services for future generation, measure should be applied to conserve biodiversity. For this purpose, the acquisition of detailed information on how biodiversity implicated in ecosystem function is distributed in space is essential. Species distribution models (SDMs) are empirical models relating field observations to environmental predictors based on statistically-derived response surfaces that fit the realized niche. These models result in spatial predictions indicating locations of the most suitable environment for the species and may potentially be applied to predict composition of communities and their functional properties. The main objective of this thesis was to provide more accurate projections of species and communities distribution under current and future climate in mountains by considering not solely abiotic but also biotic drivers of species distribution. Mountain areas and alpine ecosystems are considered as particularly sensitive to global changes and are also sources of essential ecosystem services. This thesis had three main goals: (i) a better ecological understanding of biotic interactions and how they shape the distribution of species and communities, (ii) the development of a novel approach to the spatial modeling of biodiversity, that can account for biotic interactions, and (iii) ecologically more realistic projections of future species distributions, of future composition and structure of communities. Focusing on butterfly and bumblebees in interaction with the vegetation, I detected important biotic interactions for species distribution and community composition of both plant and insects along environmental gradients. I identified the signature of environmental filtering processes at high elevation confirming the suitability of SDMs for reproducing patterns of filtering. Using those case-studies, I improved SDMs by incorporating biotic interaction and accounting for non-deterministic processes and uncertainty using a probabilistic based approach. I used improved modeling to forecast the distribution of species through the past and future climate changes. SDMs hindcasting allowed a better understanding of the spatial range dynamic of Trollius europaeus in Europe at the origin of the species intra-specific genetic diversity and identified the risk of loss of this genetic diversity caused by climate change. By simulating the future distribution of all bumblebee species in the western Swiss Alps under nine climate change scenarios for the 21st century, I found that the functional diversity of this pollinator guild will be largely affected by climate change through the loss of high elevation specialists. In turn, this will have important consequences on alpine plant pollination.

How robust are global conservation priorities to climate change?

International conservation organisations have identified priority areas for biodiversity conservation. These global-scale prioritisations affect the distribution of funds for conservation interventions. As each organisation has a different focus, each prioritisation scheme is determined by different decision criteria and the resultant priority areas vary considerably. However, little is known about how the priority areas will respond to the impacts of climate change. In this paper, we examined the robustness of eight global-scale prioritisations to climate change under various climate predictions from seven global circulation models. We developed a novel metric of the climate stability for 803 ecoregions based on a recently introduced method to estimate the overlap of climate envelopes. The relationships between the decision criteria and the robustness of the global prioritisation schemes were statistically examined. We found that decision criteria related to level of endemism and landscape fragmentation were strongly correlated with areas predicted to be robust to a changing climate. Hence, policies that prioritise intact areas due to the likely cost efficiency, and assumptions related to the potential to mitigate the impacts of climate change, require further examination. Our findings will help determine where additional management is required to enable biodiversity to adapt to the impacts of climate change

Modeling the biophysical impacts of global change in mountain biosphere reserves

Mountains and mountain societies provide a wide range of goods and services to humanity, but they are particularly sensitive to the effects of global environmental change. Thus, the definition of appropriate management regimes that maintain the multiple functions of mountain regions in a time of greatly changing climatic, economic, and societal drivers constitutes a significant challenge. Management decisions must be based on a sound understanding of the future dynamics of these systems. The present article reviews the elements required for an integrated effort to project the impacts of global change on mountain regions, and recommends tools that can be used at 3 scientific levels (essential, improved, and optimum). The proposed strategy is evaluated with respect to UNESCO's network of Mountain Biosphere Reserves (MBRs), with the intention of implementing it in other mountain regions as well. First, methods for generating scenarios of key drivers of global change are reviewed, including land use/land cover and climate change. This is followed by a brief review of the models available for projecting the impacts of these scenarios on (1) cryospheric systems, (2) ecosystem structure and diversity, and (3) ecosystem functions such as carbon and water relations. Finally, the cross-cutting role of remote sensing techniques is evaluated with respect to both monitoring and modeling efforts. We conclude that a broad range of techniques is available for both scenario generation and impact assessments, many of which can be implemented without much capacity building across many or even most MBRs. However, to foster implementation of the proposed strategy, further efforts are required to establish partnerships between scientists and resource managers in mountain areas.

Predicting global change impacts on plant species' distributions: Future challenges

Given the rate of projected environmental change for the 21st century, urgent adaptation and mitigation measures are required to slow down the on-going erosion of biodiversity. Even though increasing evidence shows that recent human-induced environmental changes have already triggered species' range shifts, changes in phenology and species' extinctions, accurate projections of species' responses to future environmental changes are more difficult to ascertain. This is problematic, since there is a growing awareness of the need to adopt proactive conservation planning measures using forecasts of species' responses to future environmental changes. There is a substantial body of literature describing and assessing the impacts of various scenarios of climate and land-use change on species' distributions. Model predictions include a wide range of assumptions and limitations that are widely acknowledged but compromise their use for developing reliable adaptation and mitigation strategies for biodiversity. Indeed, amongst the most used models, few, if any, explicitly deal with migration processes, the dynamics of population at the "trailing edge" of shifting populations, species' interactions and the interaction between the effects of climate and land-use. In this review, we propose two main avenues to progress the understanding and prediction of the different processes A occurring on the leading and trailing edge of the species' distribution in response to any global change phenomena. Deliberately focusing on plant species, we first explore the different ways to incorporate species' migration in the existing modelling approaches, given data and knowledge limitations and the dual effects of climate and land-use factors. Secondly, we explore the mechanisms and processes happening at the trailing edge of a shifting species' distribution and how to implement them into a modelling approach. We finally conclude this review with clear guidelines on how such modelling improvements will benefit conservation strategies in a changing world. (c) 2007 Rubel Foundation, ETH Zurich. Published by Elsevier GrnbH. All rights reserved.

BIOMOD - a platform for ensemble forecasting of species distributions

BIOMOD is a computer platform for ensemble forecasting of species distributions, enabling the treatment of a range of methodological uncertainties in models and the examination of species-environment relationships. BIOMOD includes the ability to model species distributions with several techniques, test models with a wide range of approaches, project species distributions into different environmental conditions (e.g. climate or land use change scenarios) and dispersal functions. It allows assessing species temporal turnover, plot species response curves, and test the strength of species interactions with predictor variables. BIOMOD is implemented in R and is a freeware, open source, package

Predicting species distribution: offering more than simple habitat models

n the last two decades, interest in species distribution models (SDMs) of plants and animals has grown dramatically. Recent advances in SDMs allow us to potentially forecast anthropogenic effects on patterns of biodiversity at different spatial scales. However, some limitations still preclude the use of SDMs in many theoretical and practical applications. Here, we provide an overview of recent advances in this field, discuss the ecological principles and assumptions underpinning SDMs, and highlight critical limitations and decisions inherent in the construction and evaluation of SDMs. Particular emphasis is given to the use of SDMs for the assessment of climate change impacts and conservation management issues. We suggest new avenues for incorporating species migration, population dynamics, biotic interactions and community ecology into SDMs at multiple spatial scales. Addressing all these issues requires a better integration of SDMs with ecological theory.