A globally integrated structure of taxonomy to support biodiversity science and conservation.

All aspects of biodiversity research, from taxonomy to conservation, rely on data associated with species names. Effective integration of names across multiple fields is paramount and depends on the coordination and organization of taxonomic data. We assess current efforts and find that even key applications for well-studied taxa still lack commonality in taxonomic information required for integration. We identify essential taxonomic elements from our interoperability assessment to support improved access and integration of taxonomic data. A stronger focus on these elements has the potential to involve taxonomic communities in biodiversity science and overcome broken linkages currently limiting research capacity. We encourage a community effort to democratize taxonomic expertise and language in order to facilitate maximum interoperability and integration.

Climate-driven variation in dispersal ability predicts responses to forest fragmentation in birds.

Species sensitivity to forest fragmentation varies latitudinally, peaking in the tropics. A prominent explanation for this pattern is that historical landscape disturbance at higher latitudes has removed fragmentation-sensitive species or promoted the evolution of more resilient survivors. However, it is unclear whether this so-called extinction filter is the dominant driver of geographic variation in fragmentation sensitivity, particularly because climatic factors may also cause latitudinal gradients in dispersal ability, a key trait mediating sensitivity to habitat fragmentation. Here we combine field survey data with a morphological proxy for avian dispersal ability (hand-wing index) to assess responses to forest fragmentation in 1,034 bird species worldwide. We find that fragmentation sensitivity is strongly predicted by dispersal limitation and that other factors-latitude, body mass and historical disturbance events-have relatively limited explanatory power after accounting for species differences in dispersal. We also show that variation in dispersal ability is only weakly predicted by historical disturbance and more strongly associated with intra-annual temperature fluctuations (seasonality). Our results suggest that climatic factors play a dominant role in driving global variation in the impacts of forest fragmentation, emphasizing the need for more nuanced environmental policies that take into account local context and associated species traits.

Expert range maps of global mammal distributions harmonised to three taxonomic authorities.

Aim: Comprehensive, global information on species' occurrences is an essential biodiversity variable and central to a range of applications in ecology, evolution, biogeography and conservation. Expert range maps often represent a species' only available distributional information and play an increasing role in conservation assessments and macroecology. We provide global range maps for the native ranges of all extant mammal species harmonised to the taxonomy of the Mammal Diversity Database (MDD) mobilised from two sources, the Handbook of the Mammals of the World (HMW) and the Illustrated Checklist of the Mammals of the World (CMW). Location: Global. Taxon: All extant mammal species. Methods: Range maps were digitally interpreted, georeferenced, error-checked and subsequently taxonomically aligned between the HMW (6253 species), the CMW (6431 species) and the MDD taxonomies (6362 species). Results: Range maps can be evaluated and visualised in an online map browser at Map of Life (mol.org) and accessed for individual or batch download for non-commercial use. Main conclusion: Expert maps of species' global distributions are limited in their spatial detail and temporal specificity, but form a useful basis for broad-scale characterizations and model-based integration with other data. We provide georeferenced range maps for the native ranges of all extant mammal species as shapefiles, with species-level metadata and source information packaged together in geodatabase format. Across the three taxonomic sources our maps entail, there are 1784 taxonomic name differences compared to the maps currently available on the IUCN Red List website. The expert maps provided here are harmonised to the MDD taxonomic authority and linked to a community of online tools that will enable transparent future updates and version control.

Sampling and modelling rare species: Conceptual guidelines for the neglected majority.

Biodiversity conservation faces a methodological conundrum: Biodiversity measurement often relies on species, most of which are rare at various scales, especially prone to extinction under global change, but also the most challenging to sample and model. Predicting the distribution change of rare species using conventional species distribution models is challenging because rare species are hardly captured by most survey systems. When enough data are available, predictions are usually spatially biased towards locations where the species is most likely to occur, violating the assumptions of many modelling frameworks. Workflows to predict and eventually map rare species distributions imply important trade-offs between data quantity, quality, representativeness and model complexity that need to be considered prior to survey and analysis. Our opinion is that study designs need to carefully integrate the different steps, from species sampling to modelling, in accordance with the different types of rarity and available data in order to improve our capacity for sound assessment and prediction of rare species distribution. In this article, we summarize and comment on how different categories of species rarity lead to different types of occurrence and distribution data depending on choices made during the survey process, namely the spatial distribution of samples (where to sample) and the sampling protocol in each selected location (how to sample). We then clarify which species distribution models are suitable depending on the different types of distribution data (how to model). Among others, for most rarity forms, we highlight the insights from systematic species-targeted sampling coupled with hierarchical models that allow correcting for overdispersion and spatial and sampling sources of bias. Our article provides scientists and practitioners with a much-needed guide through the ever-increasing diversity of methodological developments to improve the prediction of rare species distribution depending on rarity type and available data.

BIOFRAG - a new database for analyzing BIOdiversity responses to forest FRAGmentation.

Habitat fragmentation studies have produced complex results that are challenging to synthesize. Inconsistencies among studies may result from variation in the choice of landscape metrics and response variables, which is often compounded by a lack of key statistical or methodological information. Collating primary datasets on biodiversity responses to fragmentation in a consistent and flexible database permits simple data retrieval for subsequent analyses. We present a relational database that links such field data to taxonomic nomenclature, spatial and temporal plot attributes, and environmental characteristics. Field assessments include measurements of the response(s) (e.g., presence, abundance, ground cover) of one or more species linked to plots in fragments within a partially forested landscape. The database currently holds 9830 unique species recorded in plots of 58 unique landscapes in six of eight realms: mammals 315, birds 1286, herptiles 460, insects 4521, spiders 204, other arthropods 85, gastropods 70, annelids 8, platyhelminthes 4, Onychophora 2, vascular plants 2112, nonvascular plants and lichens 320, and fungi 449. Three landscapes were sampled as long-term time series (>10 years). Seven hundred and eleven species are found in two or more landscapes. Consolidating the substantial amount of primary data available on biodiversity responses to fragmentation in the context of land-use change and natural disturbances is an essential part of understanding the effects of increasing anthropogenic pressures on land. The consistent format of this database facilitates testing of generalizations concerning biologic responses to fragmentation across diverse systems and taxa. It also allows the re-examination of existing datasets with alternative landscape metrics and robust statistical methods, for example, helping to address pseudo-replication problems. The database can thus help researchers in producing broad syntheses of the effects of land use. The database is dynamic and inclusive, and contributions from individual and large-scale data-collection efforts are welcome.

Optimising bait for pitfall trapping of Amazonian dung beetles (Coleoptera: Scarabaeinae).

The accurate sampling of communities is vital to any investigation of ecological processes and biodiversity. Dung beetles have emerged as a widely used focal taxon in environmental studies and can be sampled quickly and inexpensively using baited pitfalls. Although there is now a wealth of available data on dung beetle communities from around the world, there is a lack of standardisation between sampling protocols for accurately sampling dung beetle communities. In particular, bait choice is often led by the idiosyncrasies of the researcher, logistic problems and the dung sources available, which leads to difficulties for inter-study comparisons. In general, human dung is the preferred choice, however, it is often in short supply, which can severely limit sampling effort. By contrast, pigs may produce up to 20 times the volume. We tested the ability of human and pig dung to attract a primary forest dung beetle assemblage, as well as three mixes of the two baits in different proportions. Analyses focussed on the comparability of sampling with pig or human-pig dung mixes with studies that have sampled using human dung. There were no significant differences between richness and abundance sampled by each bait. The assemblages sampled were remarkably consistent across baits, and ordination analyses showed that the assemblages sampled by mixed dung baits were not significantly different from that captured by pure human dung, with the assemblages sampled by 10% and 90% pig mixes structurally most similar to assemblages sampled by human dung. We suggest that a 10:90 human:pig ratio, or similar, is an ideal compromise between sampling efficiency, inter-study comparability and the availability of large quantities of bait for sampling Amazonian dung beetles. Assessing the comparability of assemblage samples collected using different baits represents an important step to facilitating large-scale meta-analyses of dung beetle assemblages collected using non-standard methodology.

Making statistics biologically relevant in fragmented landscapes.

The biological impacts of habitat fragmentation are routinely assessed using standard statistical modelling techniques that are used across many ecological disciplines. However, to assess the biological relevance of fragmentation impacts, we must consider an extra, spatial dimension to the standard statistical model: the biological importance of a significant and well supported model with large effect sizes crucially depends on the configuration of habitat within the study area. We argue that mapping the outputs from statistical models across a study area generates biologically meaningful estimates of fragmentation impacts. Integrating traditional statistical approaches with geographic information systems will facilitate rigorous comparisons of fragmentation impacts between taxa, studies and ecosystems.