A web-based GIS tool for exploring the world's biodiversity: The Global Biodiversity Information Facility Mapping and Analysis Portal Application (GBIF-MAPA)

Legacy biodiversity data from natural history and survey collections are rapidly becoming available in a common format over the Internet. Over 110 million records are already being served from the Global Biodiversity Information Facility (GBIF). However, our ability to use this information effectively for ecological research, management and conservation lags behind. A solution is a web-based Geographic Information System for enabling visualization and analysis of this rapidly expanding data resource. In this paper we detail a case study system, GBIF Mapping and Analysis Portal Application (MAPA), developed for deployment at distributed database portals. Building such a system requires overcoming a series of technical and research challenges. These challenges include: assuring fast speed of access to the vast amounts of data available through these distributed biodiversity databases; developing open standards based access to suitable environmental data layers for analyzing biodiversity distribution; building suitably flexible and intuitive map interfaces for refining the scope and criteria of an analysis; and building appropriate web-services based analysis tools that are of primary importance to the ecological community and make manifest the value of online biodiversity GBIF data. After discussing how we overcome these challenges, we provide case studies showing two examples of the use of GBIF-MAPA analysis tools.     

Multidimensional biases,gaps and uncertainties in global plant occurrence information

Plants are a hyperdiverse clade that plays a key role in maintaining ecological and evolutionary processes as well as human livelihoods. Biases, gaps and uncertainties in plant occurrence information remain a central problem in ecology and conservation, but these limitations remain largely unassessed globally. In this synthesis, we propose a conceptual framework for analysing gaps in information coverage, information uncertainties and biases in these metrics along taxonomic, geographical and temporal dimensions, and apply it to all c. 370 000 species of land plants. To this end, we integrated 120 million point‐occurrence records with independent databases on plant taxonomy, distributions and conservation status. We find that different data limitations are prevalent in each dimension. Different metrics of information coverage and uncertainty are largely uncorrelated, and reducing taxonomic, spatial or temporal uncertainty by filtering out records would usually come at great costs to coverage. In light of these multidimensional data limitations, we discuss prospects for global plant ecological and biogeographical research, monitoring and conservation and outline critical next steps towards more effective information usage and mobilisation. Our study provides an empirical baseline for evaluating and improving global floristic knowledge, along with a conceptual framework that can be applied to study other hyperdiverse clades.     

Linking political and scientifically derived targets for global biodiversity conservation: implications for the expansion of the global network of protected areas

Despite the global network of protected areas covers 12% of the world's land surface, its performance is still unsatisfactory. Although political and scientifically sound conservation targets usually portray different pictures of the task ahead, we show that in terms of priority areas for expanding the global network of reserves, there is much agreement between the political targets of the Convention on Biological Diversity (CBD), and the scientifically derived goals endorsed by international conservation organizations. Here we analyse four global databases to identify priority areas for fulfilling the CBD target of representing 10% of every ecological region within protected areas, and compare the distribution of priority regions for fulfilling that political target, with the distribution of the priority areas for global biodiversity conservation identified by Conservation International, the WWF, and the Wildlife Conservation Society on scientific basis. For 63% (549) of the world's terrestrial ecoregions the CBD 10% target is still not met; fulfilling it requires protecting another 4.6% of the Earth's land surface (6,239,894 km²). Yet, at least 78% of the priority regions for fulfilling that target lay within priority regions for the main global conservation strategies. By pursuing the political target set by the CBD much ancillary gains in terms of other global conservation objectives can be obtained.     

BioFTF: An R package for biodiversity assessment with the functional data analysis approach

This paper presents the R package BioFTF, which is a tool for statistical biodiversity assessment in the functional data analysis framework. Diversity is a key topic in many research fields; however, in the literature, it is demonstrated that the existing indices do not capture the different aspects of this concept. Thus, a main drawback is that different indicators may lead to different orderings among communities according to their biodiversity. A possible method to evaluate biodiversity consists in using diversity profiles that are curves depending on a specific parameter. In this setting, it is possible to adopt some functional instruments proposed in the literature, such as the first and second derivatives, the curvature, the radius of curvature and the arc length. Specifically, the derivatives and the curvature (or the radius of curvature) highlight any peculiar behaviour of the profiles, whereas the arc length helps in ranking curves, given the richness. Because these instruments do not solve the issue of ranking communities with different numbers of species, we propose an important methodological contribution that introduces the surface area. Indeed, this tool is a scalar measure that reflects the information provided by the biodiversity profile and allows for ordering communities with different richness. However, this approach requires mathematical skills that the average user may not have; thus, our idea is to provide a user-friendly tool for both non-statistician and statistician practitioners to measure biodiversity in a functional context.     

sampbias,a method for quantifying geographic sampling biases in species distribution data

Geo‐referenced species occurrences from public databases have become essential to biodiversity research and conservation. However, geographical biases are widely recognized as a factor limiting the usefulness of such data for understanding species diversity and distribution. In particular, differences in sampling intensity across a landscape due to differences in human accessibility are ubiquitous but may differ in strength among taxonomic groups and data sets. Although several factors have been described to influence human access (such as presence of roads, rivers, airports and cities), quantifying their specific and combined effects on recorded occurrence data remains challenging. Here we present sampbias, an algorithm and software for quantifying the effect of accessibility biases in species occurrence data sets. sampbias uses a Bayesian approach to estimate how sampling rates vary as a function of proximity to one or multiple bias factors. The results are comparable among bias factors and data sets. We demonstrate the use of sampbias on a data set of mammal occurrences from the island of Borneo, showing a high biasing effect of cities and a moderate effect of roads and airports. sampbias is implemented as a well‐documented, open‐access and user‐friendly R package that we hope will become a standard tool for anyone working with species occurrences in ecology, evolution, conservation and related fields.     

Strengths and weaknesses of museum and national survey data sets for predicting regional species richness: comparative and combined approaches

We compiled three independent data sets of bird species occurrences in northeastern Colorado to test how predicted species richness compared to a combined analysis using all the data. The first data set was a georeferenced regional museum data set from two major repositories — the Denver Museum of Nature, and the Science and University of Colorado Museum. The two national survey data sets were the Breeding Bird Survey (summer), and the Great Backyard Bird Count (winter). Resulting analyses show that the museum data sets give richness estimates closest to the combined data set while exhibiting a skewed abundance distribution, whereas survey data sets do not accurately estimate overall richness even though they contain far more records. The combined data set allows the strengths of one data set to augment weaknesses in others. It is likely some museum data sets display skewed abundance distributions due to collectors’ potentially self‐selecting under‐represented species over common ones.     

Impacts of invasive plants on resident animals across ecosystems,taxa, and feeding types: a global assessment

As drivers of global change, biological invasions have fundamental ecological consequences. However, it remains unclear how invasive plant effects on resident animals vary across ecosystems, animal classes, and functional groups. We performed a comprehensive meta‐analysis covering 198 field and laboratory studies reporting a total of 3624 observations of invasive plant effects on animals. Invasive plants had reducing (56%) or neutral (44%) effects on animal abundance, diversity, fitness, and ecosystem function across different ecosystems, animal classes, and feeding types while we could not find any increasing effect. Most importantly, we found that invasive plants reduced overall animal abundance, diversity and fitness. However, this significant overall effect was contingent on ecosystems, taxa, and feeding types of animals. Decreasing effects of invasive plants were most evident in riparian ecosystems, possibly because frequent disturbance facilitates more intense plant invasions compared to other ecosystem types. In accordance with their immediate reliance on plants for food, invasive plant effects were strongest on herbivores. Regarding taxonomic groups, birds and insects were most strongly affected. In insects, this may be explained by their high frequency of herbivory, while birds demonstrate that invasive plant effects can also cascade up to secondary consumers. Since data on impacts of invasive plants are rather limited for many animal groups in most ecosystems, we argue for overcoming gaps in knowledge and for a more differentiated discussion on effects of invasive plant on native fauna.     

Assessing high conservation value areas for rare,endemic and threatened (RET) species: A study in high altitude Changthang landscape of India

The Forest Stewardship Council developed the concept of High Conservation Values (HCVs) as a criteria in the forest certification process in order to promote sustainable forest management. It has six major components or values and component one and two of HCVs deal with the habitat for viable populations of “rare, endemic and threatened (RET) species” using the IUCN Red List category and other national / regional / local lists. But a consistent robust methodology for identification of these areas, does not exist. The present study tried to develop for the first time, a straight forward inclusive methodology for identification of HCVAs for the RET species on a spatio-temporal scale. A total of 50 RET and other significant species (32 flora, 10 fauna and 8 avifauna) were identified after a thorough literature review, field surveys and consultations with experts. Occurrence data of the selected species was collected from different secondary sources, field surveys, institutes and scientists who have worked on them. A 10 km grid-based approach and stratified random sampling was used for the primary GPS field surveys conducted during 2018–2019. MaxEnt species distribution model (SDM) software was used based on the occurrence data and environmental variables for identification of potential suitable habitats for the selected species. Linear support vector machine (LSVM) model was used for assessing the performance of the SDMs. The performance of each SDM has been validated through Cohen's Kappa (KAPPA), true skill statistic (TSS) and receiver operating characteristics (ROC) models. The proposed methodology addresses the urgent need for a holistic and robust set of techniques to apply the HCV toolkit. This is key to identify and map HCVAs for RET species at the landscape level and can be easily adapted to and adopted at the national, regional, state or local level in India. The methods offer an efficient, reliable approach for the application of the HCV concept, elsewhere in the world.