Global Biodiversity Information Facility Research Articles

Bridging Biodiversity and Health: The Global Biodiversity Information Facility’s initiative on open data on vectors of human diseases

There is an increased awareness of the importance of data publication, data sharing, and open science to support research, monitoring and control of vector-borne disease (VBD). Here we describe the efforts of the Global Biodiversity Information Facility (GBIF) as well as the World Health Special Programme on Research and Training in Diseases of Poverty (TDR) to promote publication of data related to vectors of diseases. In 2020, a GBIF task group of experts was formed to provide advice and support efforts aimed at enhancing the coverage and accessibility of data on vectors of human diseases within GBIF. Various strategies, such as organizing training courses and publishing data papers, were used to increase this content. This editorial introduces the outcome of a second call for data papers partnered by the TDR, GBIF and GigaScience Press in the journal GigaByte. Biodiversity and infectious diseases are linked in complex ways. These links can involve changes from the microorganism level to that of the habitat, and there are many ways in which these factors interact to affect human health. One way to tackle disease control and possibly elimination, is to provide stakeholders with access to a wide range of data shared under the FAIR principles, so it is possible to support early detection, analyses and evaluation, and to promote policy improvements and/or development.

Making better use of tracking data can reveal the spatiotemporal and intraspecific variability of species distributions

Understanding geographic ranges and species distributions is crucial for effective conservation, especially in the light of climate and land use change. However, the spatial, temporal and intraspecific resolution of digital accessible information on species distributions is often limited. Here, we suggest to make better use of high‐resolution tracking data to address existing limitations of occurrence records such as spatial biases (e.g. lack of observations in parts of the geographic range), temporal biases (e.g. lack of observations during a certain period of the year), and insufficient information on intraspecific variability (e.g. lack of population‐ or individual‐level variation). Addressing these gaps can improve our knowledge on geographic ranges, intra‐annual changes in species distributions, and population‐level differences in habitat and space use. We demonstrate this with tracking data and species distribution models (SDMs) of the barnacle goose, a migratory bird species wintering in western Europe and breeding in the Arctic. Our analyses show that tracking data can 1) supplement occurrence records from the Global Biodiversity Information Facility (GBIF) in remote areas such as the European and Russian Arctic, 2) improve information on the temporal use of wintering, staging and breeding areas of migratory species and 3) be used to reveal distribution patterns at the population level. We recommend a broader use of tracking data to address the Wallacean shortfall (i.e. the incomplete knowledge on the geographic distribution of species) and to improve forecasts of biodiversity responses to climate and land use change (e.g. species vulnerability assessments). To avoid common pitfalls, we provide six recommendations for consideration during the research cycle when using tracking data in species distribution modelling, including steps to assess biases and integrate information on intraspecific variability in modelling approaches.

Geographic And Taxonomic Occurrence R‐based Scrubbing (gatoRs): An R package and workflow for processing biodiversity data

AbstractPremiseDigitized biodiversity data offer extensive information; however, obtaining and processing biodiversity data can be daunting. Complexities arise during data cleaning, such as identifying and removing problematic records. To address these issues, we created the R package Geographic And Taxonomic Occurrence R‐based Scrubbing (gatoRs).Methods and ResultsThe gatoRs workflow includes functions that streamline downloading records from the Global Biodiversity Information Facility (GBIF) and Integrated Digitized Biocollections (iDigBio). We also created functions to clean downloaded specimen records. Unlike previous R packages, gatoRs accounts for differences in download structure between GBIF and iDigBio and allows for user control via interactive cleaning steps.ConclusionsOur pipeline enables the scientific community to process biodiversity data efficiently and is accessible to the R coding novice. We anticipate that gatoRs will be useful for both established and beginning users. Furthermore, we expect our package will facilitate the introduction of biodiversity‐related concepts into the classroom via the use of herbarium specimens.

GINSA: an accumulator for paired locality and next-generation small ribosomal subunit sequence data.

Motivated by the challenges of decentralized genetic data spread across multiple international organizations, GINSA leverages the Global Biodiversity Information Facility infrastructure to automatically retrieve and link small ribosomal subunit sequences with locality information. Testing on taxa from major organism groups demonstrates broad applicability across taxonomic levels and dataset sizes. GINSA is a freely accessible Python program under the MIT License and can be installed from PyPI via pip.

Unveiling the impacts of land use on the phylogeography of zoonotic New World Hantaviruses

Billions of genomic sequences and records of species occurrence are available in public repositories (e.g. National Center for Biotechnology Information, NCBI and the Global Biodiversity Information Facility, GBIF). By implementing analytical tools from different scientific disciplines, data mining these databases can aid in the global surveillance of zoonotic pathogens that circulate among wildlife. We illustrate this by investigating the Hantavirus–rodent system in the Americas, i.e. New World Hantaviruses (NWH). First, we considered the circulation of pathogenic NWH among Cricetidae rodents, by inferring the phylogenetic links among 277 genomic samples of the S segment (N protein) of NWH found in 55 species. Second, we used machine learning to assess the impact of land use on the probability of presence of the rodent species linked with reservoirs of pathogenic Hantaviruses. Our results show that hosts are widely present across the Americas. Some hosts are present in the primary forest and agricultural land, but not in the secondary forest, whereas other hosts are present in secondary forest and agricultural land. The diversity of host species allows Hantavirus to circulate in a wide spectrum of habitats, in particular rural rather than urban. We highlight that public repositories of genomic data and species occurrence are very useful resources for monitoring potential enzootic transmission and spillover of zoonotic viruses in relation with the changes that humans produce in the biosphere.

The Dolichens database: the lichen biota of the Dolomites.

The Dolichens project provides the first dynamic inventory of the lichens of the Dolomites (Eastern Alps, Italy). Occurrence records were retrieved from published and grey literature, reviewed herbaria, unpublished records collected by the authors, and new sampling campaigns, covering a period from 1820 to 2022. Currently, the dataset contains 56,251 records, referring to 1,719 infrageneric taxa, reported from 1820 to 2022, from hilly to nival belts, and corresponding to about half of the species known for the whole Alpine chain. Amongst them, 98% are georeferenced, although most of them were georeferenced a posteriori. The dataset is available through the Global Biodiversity Information Facility (GBIF; https://www.gbif.org/es/dataset/cea3ee2c-1ff1-4f8e-bb37-a99600cb4134) and through the Dolichens website (https://italic.units.it/dolichens/). We expect that this open floristic inventory will contribute to tracking the lichen diversity of the Dolomites over the past 200 years, and providing the basis for future taxonomic, biogeographical, and ecological studies.

Planktonic, benthic and sympagic copepods collected from the desalination unit of Mario Zucchelli Research Station in Terra Nova Bay (Ross Sea, Antarctica).

Distributional data on planktonic, benthic and sympagic copepods collected in the framework of the XXXIVth Expeditions of the Italian National Antarctic Programme (PNRA) to the Ross Sea sector from 2018-2019 are here provided. These occurrences correspond to specimens collected from the 25 μm filters used in the desalination plant of the Italian research station "Mario Zucchelli" (MZS), located in the Terra Nova Bay area (TNB; Ross Sea, Antarctica). This dataset is a contribution to the Antarctic Biodiversity Portal, the thematic Antarctic node for both the Ocean Biogeographic Information System (AntOBIS) and the Global Biodiversity Information Facility Antarctic Biodiversity Information Facility (ANTABIF). The dataset was uploaded and integrated with the SCAR-AntOBIS database (the geospatial component of SCAR-MarBIN). Please follow the guidelines from the SCAR Data Policy (ISSN 1998-0337) when using the data. If you have any questions regarding this dataset, please contact us via the contact information provided in the metadata or via data-biodiversity-aq@naturalsciences.be. Issues with the dataset can be reported at the biodiversity-aq GitHub project. We describe the diversity of marine copepods Terra Nova Bay sampled by the filters installed in the desalination unit (DU) of the Italian research station "Mario Zucchelli" described in recent work. The opening of the intake pipe of the DU is positioned at a depth of 4 m and allowed a total of 2,116 specimens to be sampled and recognised. In addition, new occurrence records of copepod genera and species are reported in the same zone. We provide an overview of the marine copepod diversity reported for TNB. The total of 2,116 individuals corresponds to 14 genera and 15 species and is represented by 136 occurrence records in this dataset. Around 52% of the total number of species are new records for the TNB area. The publication of this data paper was funded by the Belgian Science Policy Office (BELSPO, contract n°FR/36/AN1/AntaBIS) in the Framework of EU-Lifewatch as a contribution to the SCAR Antarctic biodiversity portal (biodiversity.aq).

A new R package to parse plant species occurrence records into unique collection events efficiently reduces data redundancy

Biodiversity data aggregators, such as Global Biodiversity Information Facility (GBIF) suffer from inflation of the number of occurrence records when data from different databases are merged but not fully reconciled. The ParseGBIF workflow is designed to parse duplicate GBIF species occurrence records into unique collection events (gatherings) and to optimise the quality of the spatial data associated with them. ParseGBIF provides tools to verify and standardize species scientific names according to the World Checklist of Vascular Plants taxonomic backbone, and to parse duplicate records into unique ‘collection events’, in the process compiling the most informative spatial data, where more than one duplicate is available, and providing crude estimates of taxonomic and spatial data quality. When GBIF occurrence records for a medium-sized vascular plant family, the Myrtaceae, were processed by ParseGBIF, the average number of records useful for spatial analysis increased by 180%. ParseGBIF could therefore be valuable in the evaluation of species’ occurrences at the national scale in support for national biodiversity plans, identification of plant areas important for biodiversity, sample bias estimation to inform future sampling efforts, and to forecast species range shifts in response to global climate change.

Mapping wing morphs of Tetrix subulata using citizen science data: Flightless groundhoppers are more prevalent in grasslands near water

Abstract The slender groundhopper (Orthoptera: Tetrigidae) Tetrix subulata (Linnaeus, 1758), like several other taxa of winged insects, has a long‐winged and a short‐winged form, the latter incapable of flight. The optimal habitat of T. subulata consists of wet meadows and flat shores, as they feed mostly on algae and mosses in damp, sun‐exposed, open patches. Contrasting hypotheses predict either short‐ or long‐winged morphs to be relatively more prevalent in optimal habitats. Previous investigations were limited in their spatial extent. To strongly increase the number of study locations, we obtained, through the Global Biodiversity Information Facility (GBIF), geo‐referenced observations made by citizen scientists in the Netherlands. We determined individuals' wing form based on photographs accompanying these observations and related wing‐form patterns to large‐ and medium‐scale landscape characteristics. Our analyses revealed that in grasslands near the major rivers, relatively more short‐winged individuals were found. In drier landscapes consisting of coniferous forests and heath on the higher sand areas, more long‐winged individuals were observed. Built‐up areas had no significant effect on the wing length. These patterns might be caused by the oogenesis‐flight syndrome or small‐scale spatial sorting, but the exact mechanism is yet unknown, as size‐dependency might also play a role. Although opportunistic observations are biased by where and when observers prefer to go, and by reporting probabilities varying between species groups, these biases are not likely to have affected our conclusions. Citizen science data appear to be suitable for analyses of spatial distribution and sorting of morphological types within species.

Modelling heterogeneity in the classification process in multi-species distribution models can improve predictive performance.

Species distribution models and maps from large-scale biodiversity data are necessary for conservation management. One current issue is that biodiversity data are prone to taxonomic misclassifications. Methods to account for these misclassifications in multi-species distribution models have assumed that the classification probabilities are constant throughout the study. In reality, classification probabilities are likely to vary with several covariates. Failure to account for such heterogeneity can lead to biased prediction of species distributions. Here, we present a general multi-species distribution model that accounts for heterogeneity in the classification process. The proposed model assumes a multinomial generalised linear model for the classification confusion matrix. We compare the performance of the heterogeneous classification model to that of the homogeneous classification model by assessing how well they estimate the parameters in the model and their predictive performance on hold-out samples. We applied the model to gull data from Norway, Denmark and Finland, obtained from the Global Biodiversity Information Facility. Our simulation study showed that accounting for heterogeneity in the classification process increased the precision of true species' identity predictions by 30% and accuracy and recall by 6%. Since all the models in this study accounted for misclassification of some sort, there was no significant effect of accounting for heterogeneity in the classification process on the inference about the ecological process. Applying the model framework to the gull dataset did not improve the predictive performance between the homogeneous and heterogeneous models (with parametric distributions) due to the smaller misclassified sample sizes. However, when machine learning predictive scores were used as weights to inform the species distribution models about the classification process, the precision increased by 70%. We recommend multiple multinomial regression to be used to model the variation in the classification process when the data contains relatively larger misclassified samples. Machine learning prediction scores should be used when the data contains relatively smaller misclassified samples.

Spatial extent drives patterns of relative climate change sensitivity for freshwater fishes of the United States

AbstractAssessing the sensitivity of freshwater species to climate change is an essential component of prioritizing conservation efforts for threatened freshwater ecosystems and organisms. Sensitivity to climate change can be systematically evaluated for multiple species using geographic attributes such as range size and climate niche breadth, and using species traits associated with climate change sensitivity. These systematic evaluations produce relative rankings of species sensitivity to aid conservation prioritization and to identify relatively sensitive species that may otherwise be understudied or overlooked. Due in part to biogeographic constraints, species assemblages change across regions and spatial extents; yet, the degree to which spatial factors influence relative rankings of species sensitivity is unclear. The spatial extent of multispecies analyses may alter relative rankings of species climate sensitivity; alternatively, relative climate sensitivity may be conserved among spatial scales, resulting in consistent identification of sensitive species among regions and spatial extents. We investigated how spatial extent influences our understanding of relative climate sensitivity for 137 native freshwater fishes of the United States that were representative of taxonomic, trait, and geographic diversity. Using publicly available occurrence data from the Global Biodiversity Information Facility, we calculated a systematic, geographically derived index of climate change sensitivity for study species at national and regional extents, including within four major hydrologic subregions of the United States. We examined the effects of spatial extent on the relative ranking of climate sensitivity among species, and we explored relationships among climate sensitivity, species traits, and conservation status at regional and national extents. We found that climate sensitivity rankings of species were influenced by spatial extent in some specific instances, but that relative rankings were largely conserved across spatial scales. However, correlations among geographically derived climate sensitivity rankings and species traits associated with climate sensitivity were variable across scales and regions, suggesting that links between geographic rarity and species traits may be scale‐dependent in some cases. Finally, we found few associations between climate sensitivity and current conservation status among species. Systematic approaches to quantifying climate sensitivity may offer an opportunity to identify sensitive but overlooked species for pre‐listing actions such as monitoring or conservation agreements.

The global atlas of edible insects: analysis of diversity and commonality contributing to food systems and sustainability

The future of the food system on the planet is increasingly facing uncertainties that are attributable to population growth and a surge in demand for nutritious food. Traditional agricultural practices are poised to place strain on production, as well as natural resources and ecosystem services provided, particularly under a changing climate. Given their remarkable attributes, including a low environmental footprint, high food conversion ratio, rapid growth and nutritional values, edible insects can play a vital role in the global food system. Nonetheless, substantial knowledge gaps persist regarding their diversity, global distribution, and shared characteristics across regions, potentially impeding effective scaling and access to edible insects. Therefore, we compiled and analysed the fragmented database on edible insects and identified potential drivers that elucidate insect consumption, globally, focusing on promoting a sustainable food system. We collated data from various sources, including the literature for a list of edible insect species, the Global Biodiversity Information Facility and iNaturalist for the geographical presence of edible insects, the Copernicus Land Service library for Global Land Cover, and FAOSTAT for population, income, and nutritional security parameters. Subsequently, we performed a series of analytics at the country, regional and continental levels. Our study identifies 2205 insect species, consumed across 128 countries globally. Among continents, Asia has the highest number of edible insects (932 species), followed by North America (mainly Mexico) and Africa. The countries with the highest consumption of insects are Mexico (450 species), Thailand (272 species), India (262 species), DRC (255 species), China (235 species), Brazil (140 species), Japan (123 species), and Cameroon (100 species). Our study also revealed some common and specific practices related to edible insect access and utilisation among countries and regions. Although insect consumption is often rooted in cultural practices, it exhibits correlations with land cover, the geographical presence of potentially edible insects, the size of a country’s population, and income levels. The practice of eating insects is linked to the culture of people in Africa, Asia, and Latin America, while increased consciousness and the need for food sustainability are driving most of the European countries to evaluate eating insects. Therefore, edible insects are becoming an increasingly significant part of the future of planetary food systems. Therefore, more proactive efforts are required to promote them for their effective contribution to achieving sustainable food production.

Fossil Collection at the Zoology Museum of the University of Concepción: enhancing understanding of Chile's past biodiversity.

The digital inventory of paleontological material stored in Chilean museums is highly relevant as it increases accessibility to information, both locally and over long distances, while reducing wear and tear on specimens caused by physical manipulation. The Fossil Collection database of the Museum of Zoology of the University of Concepción (UCC_MZUC_FOS) includes 144 records, with the main representatives being marine invertebrates of the Bivalvia, Echinoidea and Gastropoda classes. Notable species include Encopecalderensis, Hemiasterwayensis, Zygochlamyspatagonica and Retrotapesexalbidus, most of which come from important Chilean fossil sites. Material was collected between 1970 and 2017, with a large portion of it being donated and identified by Professor Emeritus Hugo I. Moyano and Dr. Alberto Larraín. Although the specimens contained in the resource offer basic collecting information, they substantially contribute to sharing knowledge on the fossils kept in the museums throughout the country, while providing data on their distribution. This resource corresponds to the first publication of data on faunal fossils from a museum collection in Chile on the Global Biodiversity Information Facility (GBIF) platform, thereby enhancing the understanding and documentation of Chile's paleontological heritage and its national biodiversity.

Mapping the potential distribution of Asian elephants: Implications for conservation and human–elephant conflict mitigation in South and Southeast Asia

Asian elephants play a pivotal role in their ecosystem. Understanding the potential distribution area of this species is vital for effective conservation efforts and mitigation of human-elephant conflicts. In this study, we used the maximum entropy to simulate the potential distribution area of Asian elephants across South and Southeast Asia, leveraging Maximum Entropy (MaxEnt) and presence data sourced from the Global Biodiversity Information Facility (GBIF). The analysis revealed that the potential distribution area of Asian elephants spans 530,418 km2 (10.59% of the study area), with significant potential distribution areas observed in Indonesia (136,890 km2) and Malaysia (119,497 km2). Vegetation type emerged as the dominant environmental factor influencing model outcomes, encompassing aspects such as broadleaved evergreen tree coverage, broadleaved deciduous closed tree coverage and EVI. The potential distribution area of Asian elephants overlaps with regions inhabited by 55.25 million people, with 6.07 million people residing in highly suitable habitats. India and Malaysia have high potential for human-elephant conflict (HEC) due to the high number of people living in potential and highly suitable habitats for elephants. Bangladesh and Nepal, on the other hand, have fewer people living in these habitats suitable for elephants, but they face relatively high human population density in these areas.

Current and future distribution of Eucalyptus globulus under changing climate in Ethiopia: implications for forest management

Eucalyptus globulus is a species endemic to southeastern Australia. It has naturalized non-native ranges in other parts of Australia, Europe, Africa, and the western United States. This study is the first of its kind in Ethiopia to model and map the spatiotemporal distribution of the species using species distribution models (SDMs). A total of 874 occurrence records were used from the online Global Biodiversity Information Facility (GBIF) database and field observation. Three environmental variables, including terrain, climate, and soil were used to predict the species’ distribution. The terrain, climate, and soil raster grids were resampled to a 200-meter resolution. The Global Circulation Model (GCM) HadGEM3-GC3.1 was used to extract future climate data. This GCM has a good match between the atmospheric and oceanic components showing little drift in its surface climate. Besides, it has the best coverage of Africa. Three climate change scenarios (SSPs 1-2.6, SSPs 2-4.5, and SSPs 5-8.5) were used for predicting suitable habitat of the species. The jackknife test was chosen to assess the importance of each environmental predictor variable. The model’s performance was evaluated using the Area under the Curve (AUC) of the Receiver Operating Characteristic (ROC) curve. The model had excellent predictive performance with an average AUC of 0.94. Altitude, rooting conditions, slope, dry-month precipitation, and temperature seasonality are the most important environmental factors in shaping E. globulus distribution. Ethiopian highlands are predicted to be more suitable to the species, but the increase in temperature seasonality may reduce suitable habitat under the high-forcing climate change scenario. Climate change is expected to create more suitable habitats for eucalyptus in the future which may encourage plantations in potential distribution areas. Consequently, ensuring long-term forest health necessitates robust management systems prioritizing native trees and responsible grower or farmer practices.

Using remote-sensing and citizen-science data to assess urban biodiversity for sustainable cityscapes: the case study of Athens, Greece

ContextUrban biodiversity is an important and growing research area as cities continue to expand and human populations concentrate in urban centers. In order to effectively conserve urban biodiversity and inform future urban planning, a thorough understanding of the patterns and underlying factors affecting biodiversity is essential. However, a methodology of assessing urban biodiversity that would be replicable to different cities has been challenging, primarily due to data limitation on habitats and species in urban areas.ObjectivesIn response to these challenges, this work implements a biodiversity analysis framework, adapted for the municipality of Athens, Greece, a city that is facing its own unique challenges in preserving biodiversity while accommodating urban growth. The analysis granularity is at the zipcode level.MethodsA k-means clustering scheme that leads to theclassification of urban habitats is incorporated using earth observation data, while citizen science-generated species occurrence data from the Global Biodiversity Information Facility (GBIF) platform is used for biodiversity analysis and validation. This integrative approach allows us to account for fine-scale environmental variation, which plays a crucial role in species' abundances and distributions in urban settings.ResultsOur analysis shows that the fact that almost 80% of the Athens land cover is impervious and lacks vegetation has serious effects on biodiversity in the city, which is very limited and is only abundant in Urban Green areas. The city’s dense urban fabric, followed by intense cementification, lack of open streams and noisy large arterial roads take a toll on urban species occurrences, which are up to 100 times less than the green and blue areas.ConclusionsThis work highlights the significance of zipcode-level analyses in understanding the complex interplay between urbanization and biodiversity. Furthermore, it shows that it is possible to assess urban biodiversity using free and open satellite data, without previously acquiring a high-resolution species occurrence dataset through field surveys, thus providing a comprehensive understanding of urban biodiversity patterns in cities like Athens.

3000 leagues under the sea: the voyages of vagrant walruses (Odobenus rosmarus) in temperate Europe

Sightings of vagrant walruses in Europe have been known since historic times, yet whether this phenomenon remains constant or changes over time is unclear. In this study, we conducted a comprehensive cross-reference of information on vagrant walruses observed in temperate Europe (below 61° N) between 1923 and 2022 utilising data from the Global Biodiversity Information Facility depository. In addition, we conducted an online search of records from the last ten years, resulting in a detailed reconstruction of the movements of the most recently observed individuals. We estimated that between 31 and 36 different individuals have been observed over the last century, with most of these likely originating from the Svalbard region and only a few from Greenland. A comparison in the yearly number of records showed a significant increase over time, suggesting that vagrant walruses reach Europe as a result of a combination of climatic and meteorological events as well as of demographic changes in the populations of the North Atlantic.

Predicting the global potential distribution of two major vectors of Rocky Mountain Spotted Fever under conditions of global climate change.

Rocky Mountain spotted fever is a tick-borne disease that is highly dangerous but often overlooked by the public. To prevent the spread of the disease, it is important to understand the distribution patterns of its vectors' suitable areas. This study aims to explore the potential global suitability of areas for the vectors of Rocky Mountain spotted fever, including Dermacentor variabilis and Amblyomma cajennense under both historical and future climate scenarios. The study also seeks to investigate the impact of climatic factors on the distribution patterns of these vectors. Data on species distribution were downloaded from the Global Biodiversity Information Facility, Web of Science and PubMed database. The climatic variables were downloaded from WorldClim Global Climate Database. The Maximum Entropy Model was used to evaluate the contribution of monthly precipitation, monthly maximum temperature, monthly minimum temperature, elevation, and nineteen other climatic variables to vector survival, as well as to predict the suitable area for the vectors. We found that D. variabilis is distributed in North America, while A. cajennense is mainly distributed in South America, but all other continents except Antarctica have a suitable distribution. D. variabilis is more likely to survive in temperate regions, and A. cajennense is more likely to survive in tropical zones. D. variabilis is more sensitive to temperature, whereas A. cajennense is sensitive to both temperature and precipitation, and A. cajennense prefers tropical regions with hot and humid characteristics. The high suitable areas of both vectors were almost expanded in the ssp5-8.5 scenario, but not so much in the ssp1-2.6 scenario. Highly suitable areas with vectors survival should be strengthened with additional testing to prevent related diseases from occurring, and other highly suitable areas should be alert for entry and exit monitoring to prevent invasion and colonization of vectors.

Is the GBIF appropriate for use as input in models of predicting species distributions? Study from the Czech Republic

Questions concerning species diversity have attracted ecologists and biogeographers for over a century, mainly because the diversity of life on Earth is in rapid decline, which is expected to continue in the future. One of the most important current database on species distribution data is the Global Biodiversity Information Facility (GBIF), which contains more than 2 billion occurrences for all organisms, and this number is continuously increasing with the addition of new data and by combining with other applications. Such data also exist in several national databases, most of which are unfortunately often not freely available and not included in GBIF. We suspected that the national databases, mostly professionally maintained by governmental organisations, may be more comprehensive than GBIF, which is not centrally organised and therefore the national databases may give more accurate predictions than GBIF. To test our assumptions, we have compared: (i) the amount of data included in the Czech database called Nálezová databáze ochrany přírody (NDOP, Discovery database of nature protection) with the amount of data in GBIF after its restriction to the Czech Republic, and (ii) the overlap of the predictions of species distributions for the Czech Republic, based on these two databases. We have used the family Orchidaceae as a model group. We found that: (i) there is a significantly larger number of records per studied region (Czech Republic) in NDOP, compared with GBIF, and (ii) the predictions of Maxent based on orchid records in NDOP are overlapping to a great degree with the predictions based on data based on orchid records in GBIF. Bearing in mind these results, we suggest that if only one database is available for the region studied, we must use this one. If more databases are available for the region studied, we should use the database containing most locations (usually some of the local ones, like NDOP), because using more locations implies larger significance of predictions of species distributions.

Climate and human stressors on global penguin hotspots: Current assessments for future conservation.

As charismatic and iconic species, penguins can act as "ambassadors" or flagship species to promote the conservation of marine habitats in the Southern Hemisphere. Unfortunately, there is a lack of reliable, comprehensive, and systematic analysis aimed at compiling spatially explicit assessments of the multiple impacts that the world's 18 species of penguin are facing. We provide such an assessment by combining the available penguin occurrence information from Global Biodiversity Information Facility (>800,000 occurrences) with three main stressors: climate-driven environmental changes at sea, industrial fisheries, and human disturbances on land. Our analyses provide a quantitative assessment of how these impacts are unevenly distributed spatially within species' distribution ranges. Consequently, contrasting pressures are expected among species, and populations within species. The areas coinciding with the greatest impacts for penguins are the coast of Perú, the Patagonian Shelf, the Benguela upwelling region, and the Australian and New Zealand coasts. When weighting these potential stressors with species-specific vulnerabilities, Humboldt (Spheniscus humboldti), African (Spheniscus demersus), and Chinstrap penguin (Pygoscelis antarcticus) emerge as the species under the most pressure. Our approach explicitly differentiates between climate and human stressors, since the more achievable management of local anthropogenic stressors (e.g., fisheries and land-based threats) may provide a suitable means for facilitating cumulative impacts on penguins, especially where they may remain resilient to global processes such as climate change. Moreover, our study highlights some poorly represented species such as the Northern Rockhopper (Eudyptes moseleyi), Snares (Eudyptes robustus), and Erect-crested penguin (Eudyptes sclateri) that need internationally coordinated efforts for data acquisition and data sharing to understand their spatial distribution properly.