Establishing macroecological trait datasets: digitalization, extrapolation, and validation of diet preferences in terrestrial mammals worldwide

Ecological trait data are essential for understanding the broad-scale distribution of biodiversity and its response to global change. For animals, diet represents a fundamental aspect of species’ evolutionary adaptations, ecological and functional roles, and trophic interactions. However, the importance of diet for macroevolutionary and macroecological dynamics remains little explored, partly because of the lack of comprehensive trait datasets. We compiled and evaluated a comprehensive global dataset of diet preferences of mammals (“MammalDIET”). Diet information was digitized from two global and cladewide data sources and errors of data entry by multiple data recorders were assessed. We then developed a hierarchical extrapolation procedure to fill-in diet information for species with missing information. Missing data were extrapolated with information from other taxonomic levels (genus, other species within the same genus, or family) and this extrapolation was subsequently validated both internally (with a jack-knife approach applied to the compiled species-level diet data) and externally (using independent species-level diet information from a comprehensive continentwide data source). Finally, we grouped mammal species into trophic levels and dietary guilds, and their species richness as well as their proportion of total richness were mapped at a global scale for those diet categories with good validation results. The success rate of correctly digitizing data was 94%, indicating that the consistency in data entry among multiple recorders was high. Data sources provided species-level diet information for a total of 2033 species (38% of all 5364 terrestrial mammal species, based on the IUCN taxonomy). For the remaining 3331 species, diet information was mostly extrapolated from genus-level diet information (48% of all terrestrial mammal species), and only rarely from other species within the same genus (6%) or from family level (8%). Internal and external validation showed that: (1) extrapolations were most reliable for primary food items; (2) several diet categories (“Animal”, “Mammal”, “Invertebrate”, “Plant”, “Seed”, “Fruit”, and “Leaf”) had high proportions of correctly predicted diet ranks; and (3) the potential of correctly extrapolating specific diet categories varied both within and among clades. Global maps of species richness and proportion showed congruence among trophic levels, but also substantial discrepancies between dietary guilds. MammalDIET provides a comprehensive, unique and freely available dataset on diet preferences for all terrestrial mammals worldwide. It enables broad-scale analyses for specific trophic levels and dietary guilds, and a first assessment of trait conservatism in mammalian diet preferences at a global scale. The digitalization, extrapolation and validation procedures could be transferable to other trait data and taxa

Spatial autocorrelation and the selection of simultaneous autoregressive models

ABSTRACT Aim Spatial autocorrelation is a frequent phenomenon in ecological data and can affect estimates of model coefficients and inference from statistical models. Here, we test the performance of three different simultaneous autoregressive (SAR) model types (spatial error = SAR err , lagged = SAR lag and mixed = SAR mix ) and common ordinary least squares (OLS) regression when accounting for spatial autocorrelation in species distribution data using four artificial data sets with known (but different) spatial autocorrelation structures. Methods We evaluate the performance of SAR models by examining spatial patterns in model residuals (with correlograms and residual maps), by comparing model parameter estimates with true values, and by assessing their type I error control with calibration curves. We calculate a total of 3240 SAR models and illustrate how the best models [in terms of minimum residual spatial autocorrelation (minRSA), maximum model fit ( R 2 ), or Akaike information criterion (AIC)] can be identified using model selection procedures. Results Our study shows that the performance of SAR models depends on model specification (i.e. model type, neighbourhood distance, coding styles of spatial weights matrices) and on the kind of spatial autocorrelation present. SAR model parameter estimates might not be more precise than those from OLS regressions in all cases. SAR err models were the most reliable SAR models and performed well in all cases (independent of the kind of spatial autocorrelation induced and whether models were selected by minRSA, R 2 or AIC), whereas OLS, SAR lag and SAR mix models showed weak type I error control and/or unpredictable biases in parameter estimates. Main conclusions SAR err models are recommended for use when dealing with spatially autocorrelated species distribution data. SAR lag and SAR mix might not always give better estimates of model coefficients than OLS, and can thus generate bias. Other spatial modelling techniques should be assessed comprehensively to test their predictive performance and accuracy for biogeographical and macroecological research

Mammal predator and prey species richness are strongly linked at macroscales

Predator-prey interactions play an important role for species composition and community dynamics at local scales, but their importance in shaping large-scale gradients of species richness remains unexplored. Here, we use global range maps, structural equation models (SEM), and comprehensive databases of dietary preferences and body masses of all terrestrial, non-volant mammals worldwide, to test whether (1) prey bottom-up or predator top-down relationships are important drivers of broad-scale species richness gradients once the environment and human influence have been accounted for, (2) predator-prey richness associations vary among biogeographic regions, and (3) body size influences large-scale covariation between predators and prey. SEMs including only productivity, climate, and human factors explained a high proportion of variance in prey richness (R2 = 0.56) but considerably less in predator richness (R2 = 0.13). Adding predator-to-prey or prey-topredator paths strongly increased the explained variance in both cases (prey R2 = 0.79, predator R2 = 0.57), suggesting that predator-prey interactions play an important role in driving global diversity gradients. Prey bottom-up effects prevailed over productivity, climate, and human influence to explain predator richness, whereas productivity and climate were more important than predator top-down effects for explaining prey richness, although predator top-down effects were still significant. Global predator-prey associations were not reproduced in all regions, indicating that distinct paleoclimate and evolutionary histories (Africa and Australia) may alter species interactions across trophic levels. Stronger crosstrophic- level associations were recorded within categories of similar body size (e.g., large prey to large predators) than between them (e.g., large prey to small predators), suggesting that mass-related energetic and physiological constraints influence broad-scale richness links, especially for large-bodied mammals. Overall, our results support the idea that trophic interactions can be important drivers of large-scale species richness gradients in combination with environmental effects. © 2013 by the Ecological Society of America

Minimum Information Standards for Essential Biodiversity Variables

Minimum Information Standards (MIS) are sets of specifications for describing datasets that aim to standardize data reporting and to maximize its discoverability and interoperability. While MIS have greatly contributed to enhance the distribution and reuse of datasets in the biological and biomedical sciences, their adoption in ecology and biodiversity sciences is still incipient. Here we present a community effort to generate minimum standards for Essential Biodiversity Variables (EBVs). The operationalization of EBVs require integrating heterogeneous datasets of disparate origin and, often, to combine information from different geographic areas and time periods. Furthermore, developing policy-relevant indicators from EBVs requires an additional level of integration between datasets that inform on different facets of biodiversity, e.g. at levels from species to ecosystems. MIS for Essential Biodiversity Variables is founded in the description of the EBV-data cube as the unifying framework to deliver interoperable biodiversity observations. They summarize aspects of the spatial and temporal domains of the datasets, as well as uncertainty and bias reporting. MIS also incorporate the GEOSS proposed principles for data management. Finally, a metadata publishing toolkit will be developed in order to ensure that EBVs are discoverable and used under the auspices of GEO BON

Towards global data products of Essential Biodiversity Variables on species traits

Essential Biodiversity Variables (EBVs) allow observation and reporting of global biodiversity change, but a detailed framework for the empirical derivation of specific EBVs has yet to be developed. Here, we re-examine and refine the previous candidate set of species traits EBVs and show how traits related to phenology, morphology, reproduction, physiology and movement can contribute to EBV operationalization. The selected EBVs express intra-specific trait variation and allow monitoring of how organisms respond to global change. We evaluate the societal relevance of species traits EBVs for policy targets and demonstrate how open, interoperable and machine-readable trait data enable the building of EBV data products. We outline collection methods, meta(data) standardization, reproducible workflows, semantic tools and licence requirements for producing species traits EBVs. An operationalization is critical for assessing progress towards biodiversity conservation and sustainable development goals and has wide implications for data-intensive science in ecology, biogeography, conservation and Earth observation

A new prescription model for regional citrate anticoagulation in therapeutic plasma exchanges

Regional citrate anticoagulation (RCA) is proposed for various extracorporeal purification techniques to overcome the risk of bleeding that might result from systemic anticoagulation. Yet, no individualized treatment protocol has been proposed for therapeutic plasma exchange (TPE) so far. The objective of this study was to assess the determinants of blood citrate concentration needed and to develop an individualized RCA protocol useful for clinical practice. The study population included 14 patients who underwent a total of 47 TPE sessions. Citrate was infused pre-plasmafilter. Post-plasmafilter and systemic plasma ionized calcium concentrations were measured at standardized time intervals. An algorithm was proposed for the supplementation of calcium. During the discovery phase, citrate was infused at a fixed starting rate, and adapted accordingly to obtained post-plasmafilter ionized calcium levels. Using a mathematical approach, an algorithm was thereafter developed for individualized prescriptions of citrate. Pre-treatment values of hematocrit and plasma ionized calcium were the main determinants of the required rate of citrate infusion. These can be integrated into a final equation enabling to individualize the prescription. A prefilter ionized calcium concentration between 0.24 and 0.33 mmol/l prevented coagulation of the extracorporeal circuit. Significant hypocalcemia occurred in 8.5% of treatments. There were no significant acid-base disturbances. We propose a new protocol, which enables for the first time to individualize the prescription of regional citrate anticoagulation during TPE, in an efficient manner. The immediately obtained regional anticoagulation protects against both the risk of coagulation of the membrane and the exposure to an excess of citrate

The Cenozoic history of palms:Global diversification, biogeography and the decline of megathermal forests

10.1111/geb.13436GLOBAL ECOLOGY AND BIOGEOGRAPHY313425-43

Downsizing of animal communities triggers stronger functional than structural decay in seed-dispersal networks

Downsizing of animal communities due to defaunation is prevalent in many ecosystems. Yet, we know little about its consequences for ecosystem functions such as seed dispersal. Here, we use eight seed-dispersal networks sampled across the Andes and simulate how downsizing of avian frugivores impacts structural network robustness and seed dispersal. We use a trait-based modeling framework to quantify the consequences of downsizing—relative to random extinctions—for the number of interactions and secondary plant extinctions (as measures of structural robustness) and for long-distance seed dispersal (as a measure of ecosystem function). We find that downsizing leads to stronger functional than structural losses. For instance, 10% size-structured loss of bird species results in almost 40% decline of long-distance seed dispersal, but in less than 10% of structural loss. Our simulations reveal that measures of the structural robustness of ecological networks underestimate the consequences of animal extinction and downsizing for ecosystem functioning.Fil: Donoso, Isabel. Senckenberg Biodiversity and Climate Research Centre; AlemaniaFil: Sorensen, Marjorie C.. Senckenberg Biodiversity and Climate Research Centre; Alemania. University of Guelph; Canadá. Goethe Universitat Frankfurt; AlemaniaFil: Blendinger, Pedro Gerardo. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Kissling, W. Daniel. University of Amsterdam; Países BajosFil: Neuschulz, Eike Lena. Senckenberg Biodiversity and Climate Research Centre; AlemaniaFil: Mueller, Thomas. Senckenberg Biodiversity and Climate Research Centre; AlemaniaFil: Schleuning, Matthias. Senckenberg Biodiversity and Climate Research Centre; Alemani

To adapt or go extinct? The fate of megafaunal palm fruits under past global change

Past global change may have forced animal-dispersed plants with megafaunal fruits to adapt or go extinct, but these processes have remained unexplored at broad spatio-temporal scales. Here, we combine phylogenetic, distributional and fruit size data for more than 2500 palm (Arecaceae) species in a time-slice diversification analysis to quantify how extinction and adaptation have changed over deep time. Our results indicate that extinction rates of palms with megafaunal fruits have increased in the New World since the onset of the Quaternary (2.6 million years ago). In contrast, Old World palms show a Quaternary increase in transition rates towards evolving small fruits from megafaunal fruits. We suggest that Quaternary climate oscillations and concurrent habitat fragmentation and defaunation of megafaunal frugivores in the New World have reduced seed dispersal distances and geographical ranges of palms with megafaunal fruits, resulting in their extinction. The increasing adaptation to smaller fruits in the Old World could reflect selection for seed dispersal by ocean-crossing frugivores (e.g. medium-sized birds and bats) to colonize Indo-Pacific islands against a background of Quaternary sea-level fluctuations. Our macro-evolutionary results suggest that megafaunal fruits are increasingly being lost from tropical ecosystems, either due to extinctions or by adapting to smaller fruit sizes.</p