Uses of GBIF in scientific research

Peer-reviewed research citing GBIF as a data source, with at least one author from United States.
Extracted from the Mendeley GBIF Public Library.

List of publications

  • Ahrends A, Hollingsworth P, Ziegler A, Fox J, Chen H, Su Y et al. (2015)

    Current trends of rubber plantation expansion may threaten biodiversity and livelihoods

    Global Environmental Change 34 48-58.

    The first decade of the new millennium saw a boom in rubber prices. This led to rapid and widespread land conversion to monoculture rubber plantations in continental SE Asia, where natural rubber production has increased >50% since 2000. Here, we analyze the subsequent spread of rubber between 2005 and 2010 in combination with environmental data and reports on rubber plantation performance. We show that rubber has been planted into increasingly sub-optimal environments. Currently, 72% of plantation area is in environmentally marginal zones where reduced yields are likely. An estimated 57% of the area is susceptible to insufficient water availability, erosion, frost, or wind damage, all of which may make long-term rubber production unsustainable. In 2013 typhoons destroyed plantations worth US$ >250 million in Vietnam alone, and future climate change is likely to lead to a net exacerbation of environmental marginality for both current and predicted future rubber plantation area. New rubber plantations are also frequently placed on lands that are important for biodiversity conservation and ecological functions. For example, between 2005 and 2010 >2500km2 of natural tree cover and 610km2 of protected areas were converted to plantations. Overall, expansion into marginal areas creates potential for loss-loss scenarios: clearing of high-biodiversity value land for economically unsustainable plantations that are poorly adapted to local conditions and alter landscape functions (e.g. hydrology, erosion) – ultimately compromising livelihoods, particularly when rubber prices fall.

    Keywords: Biodiversity, Cash crops, Deforestation, Rubber, South East Asia

  • Albuquerque F, Beier P (2015)

    Rarity-weighted richness: a simple and reliable alternative to integer programming and heuristic algorithms for minimum set and maximum coverage problems in conservation planning.

    PloS one 10(3) e0119905.

    Here we report that prioritizing sites in order of rarity-weighted richness (RWR) is a simple, reliable way to identify sites that represent all species in the fewest number of sites (minimum set problem) or to identify sites that represent the largest number of species within a given number of sites (maximum coverage problem). We compared the number of species represented in sites prioritized by RWR to numbers of species represented in sites prioritized by the Zonation software package for 11 datasets in which the size of individual planning units (sites) ranged from <1 ha to 2,500 km2. On average, RWR solutions were more efficient than Zonation solutions. Integer programming remains the only guaranteed way find an optimal solution, and heuristic algorithms remain superior for conservation prioritizations that consider compactness and multiple near-optimal solutions in addition to species representation. But because RWR can be implemented easily and quickly in R or a spreadsheet, it is an attractive alternative to integer programming or heuristic algorithms in some conservation prioritization contexts.

    Keywords: Biodiversity, Cash crops, Deforestation, Rubber, South East Asia

  • Alhajeri B, Hunt O, Steppan S (2015)

    Molecular systematics of gerbils and deomyines (Rodentia: Gerbillinae, Deomyinae) and a test of desert adaptation in the tympanic bulla

    Journal of Zoological Systematics and Evolutionary Research.

    Recent molecular studies in gerbils found multiple instances of discordance between molecular and morphological phylogenies. In this study, we analyse the largest molecular data set to date of gerbils and their sister group the deomyines to estimate their phylogenetic relationships. Maximum-likelihood and Bayesian analyses were largely concordant, and both generally had high levels of node support. For gerbils, the results were generally concordant with previous molecular phylogenies based on allozymes, chromosomes, DNA/DNA hybridization and DNA sequences, and discordant with morphological phylogenies. None of the traditional gerbil tribes and subtribes were monophyletic. In addition, paraphyly was found in the genera Gerbillus, Gerbilliscus and Meriones as well as in five subgenera within Dipodillus, Gerbillurus and Meriones. Short branches separating taxa in small clusters within Dipodillus and Meriones suggest synonymy. Within deomyines, all genera and subgenera were monophyletic; however, two species groups within Acomys appear to contain synonymous taxa. We also find support for the discordance between molecular and morphological phylogenies in gerbils being partly due to convergent adaptations to arid environments, primarily in the suite of traits associated with inflation of the tympanic bullae. Relative bullar size does appear to be a desert adaptation and is correlated with aridity independent of phylogeny. Further, it varies more strongly along bioclimatic clines than between binary habitat classifications (desert versus mesic).

    Keywords: Arid environments, Muroidea, geometric morphometrics, molecular phylogenetics, skull morphology

  • Alimi T, Fuller D, Qualls W, Herrera S, Arevalo-Herrera M, Quinones M et al. (2015)

    Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population.

    Parasites & vectors 8 431.

    BACKGROUND: Changes in land use and land cover (LULC) as well as climate are likely to affect the geographic distribution of malaria vectors and parasites in the coming decades. At present, malaria transmission is concentrated mainly in the Amazon basin where extensive agriculture, mining, and logging activities have resulted in changes to local and regional hydrology, massive loss of forest cover, and increased contact between malaria vectors and hosts. METHODS: Employing presence-only records, bioclimatic, topographic, hydrologic, LULC and human population data, we modeled the distribution of malaria and two of its dominant vectors, Anopheles darlingi, and Anopheles nuneztovari s.l. in northern South America using the species distribution modeling platform Maxent. RESULTS: Results from our land change modeling indicate that about 70,000 km(2) of forest land would be lost by 2050 and 78,000 km(2) by 2070 compared to 2010. The Maxent model predicted zones of relatively high habitat suitability for malaria and the vectors mainly within the Amazon and along coastlines. While areas with malaria are expected to decrease in line with current downward trends, both vectors are predicted to experience range expansions in the future. Elevation, annual precipitation and temperature were influential in all models both current and future. Human population mostly affected An. darlingi distribution while LULC changes influenced An. nuneztovari s.l. distribution. CONCLUSION: As the region tackles the challenge of malaria elimination, investigations such as this could be useful for planning and management purposes and aid in predicting and addressing potential impediments to elimination.

    Keywords: An. darlingi, An. nuneztovari s.l, Climate, Land-use changes, Malaria, Maxent, Population expansion, South America, Species distribution models, change

  • Alter S, Meyer M, Post K, Czechowski P, Gravlund P, Gaines C et al. (2015)

    Climate impacts on transocean dispersal and habitat in gray whales from the Pleistocene to 2100.

    Molecular ecology 24(7) 1510-22.

    Arctic animals face dramatic habitat alteration due to ongoing climate change. Understanding how such species have responded to past glacial cycles can help us forecast their response to today's changing climate. Gray whales are among those marine species likely to be strongly affected by Arctic climate change, but a thorough analysis of past climate impacts on this species has been complicated by lack of information about an extinct population in the Atlantic. While little is known about the history of Atlantic gray whales or their relationship to the extant Pacific population, the extirpation of the Atlantic population during historical times has been attributed to whaling. We used a combination of ancient and modern DNA, radiocarbon dating and predictive habitat modelling to better understand the distribution of gray whales during the Pleistocene and Holocene. Our results reveal that dispersal between the Pacific and Atlantic was climate dependent and occurred both during the Pleistocene prior to the last glacial period and the early Holocene immediately following the opening of the Bering Strait. Genetic diversity in the Atlantic declined over an extended interval that predates the period of intensive commercial whaling, indicating this decline may have been precipitated by Holocene climate or other ecological causes. These first genetic data for Atlantic gray whales, particularly when combined with predictive habitat models for the year 2100, suggest that two recent sightings of gray whales in the Atlantic may represent the beginning of the expansion of this species' habitat beyond its currently realized range.

    Keywords: Animals, Arctic Regions, Atlantic Ocean, Biological, Climate Change, DNA, Ecosystem, Fossils, Genetic Variation, Haplotypes, Mitochondrial, Mitochondrial: genetics, Models, Molecular Sequence Data, Phylogeography, Population Dynamics, Sequence Analysis, Whales, Whales: genetics

  • Baltensperger A, Huettmann F (2015)

    Predicted Shifts in Small Mammal Distributions and Biodiversity in the Altered Future Environment of Alaska: An Open Access Data and Machine Learning Perspective.

    PloS one 10(7) e0132054.

    Climate change is acting to reallocate biomes, shift the distribution of species, and alter community assemblages in Alaska. Predictions regarding how these changes will affect the biodiversity and interspecific relationships of small mammals are necessary to pro-actively inform conservation planning. We used a set of online occurrence records and machine learning methods to create bioclimatic envelope models for 17 species of small mammals (rodents and shrews) across Alaska. Models formed the basis for sets of species-specific distribution maps for 2010 and were projected forward using the IPCC (Intergovernmental Panel on Climate Change) A2 scenario to predict distributions of the same species for 2100. We found that distributions of cold-climate, northern, and interior small mammal species experienced large decreases in area while shifting northward, upward in elevation, and inland across the state. In contrast, many southern and continental species expanded throughout Alaska, and also moved down-slope and toward the coast. Statewide community assemblages remained constant for 15 of the 17 species, but distributional shifts resulted in novel species assemblages in several regions. Overall biodiversity patterns were similar for both time frames, but followed general species distribution movement trends. Biodiversity losses occurred in the Yukon-Kuskokwim Delta and Seward Peninsula while the Beaufort Coastal Plain and western Brooks Range experienced modest gains in species richness as distributions shifted to form novel assemblages. Quantitative species distribution and biodiversity change projections should help land managers to develop adaptive strategies for conserving dispersal corridors, small mammal biodiversity, and ecosystem functionality into the future.

    Keywords: Animals, Arctic Regions, Atlantic Ocean, Biological, Climate Change, DNA, Ecosystem, Fossils, Genetic Variation, Haplotypes, Mitochondrial, Mitochondrial: genetics, Models, Molecular Sequence Data, Phylogeography, Population Dynamics, Sequence Analysis, Whales, Whales: genetics

  • Baltensperger A, Huettmann F (2015)

    Predictive spatial niche and biodiversity hotspot models for small mammal communities in Alaska: applying machine-learning to conservation planning

    Landscape Ecology.

    Context Changing global environmental conditions, especially at northern latitudes, are threatening to shift species distributions and alter wildlife communities. Objective We aimed to establish current distributions and community arrangements of small mammals to provide important baselines for monitoring and conserving biodiversity into the future. Methods We used 4,408 archived museum and open-access records and the machine learning algorithm, RandomForests, to create high-resolution spatial niche models for 17 species of rodents and shrews in Alaska. Models were validated using independent trapping results from 20 locations stratified along statewide mega-transects, and an average species richness curve was calculated for field samples. Community cluster analyses (varclus) identified geographic patterns of sympatry among species. Species models were summed to create the first small-mammal species richness map for Alaska. Results Species richness increased logarithmically to a mean of 3.3 species per location over 1,500 trap-nights. Distribution models yielded mean accuracies of 71 % (45–90 %), and maps correctly predicted a mean of 75 % (60–95 %) of occurrences correctly in the field. Top predictors included Soil Type, Ecoregion, Landfire Land-cover, December Sea Ice, and July Temperature at the geographic scale. Cluster analysis delineated five community groups (3–4 species/group), and species richness was highest (11–13 species) over the Yukon-Tanana Uplands. Conclusions Models presented here provide spatial predictions of current small mammal biodiversity in Alaska and an initial framework for mapping and monitoring wildlife distributions across broad landscapes into the future.

    Keywords: Arctic, Boreal Forest, Ecological niche modeling, Lemmings, Machine learning, Megatransect sampling, Open-access data, RandomForests, Shrews, Voles

  • Barker B, Rodríguez-Robles J, Cook J (2015)

    Climate as a driver of tropical insular diversity: comparative phylogeography of two ecologically distinctive frogs in Puerto Rico

    Ecography n/a-n/a.

    The effects of late Quaternary climate on distributions and evolutionary dynamics of insular species are poorly understood in most tropical archipelagoes. We used ecological niche models under past and current climate to derive hypotheses regarding how stable climatic conditions shaped genetic diversity in two ecologically distinctive frogs in Puerto Rico. Whereas the mountain coquí Eleutherodactylus portoricensis is restricted to montane forest in the Cayey and Luquillo Mountains, the red-eyed coquí E. antillensis is a habitat generalist distributed across the entire Puerto Rican Bank (Puerto Rico and the Virgin Islands, excluding St Croix). To test our hypotheses, we conducted phylogeographic and population genetic analyses based on mitochondrial and nuclear loci of each species across their range in Puerto Rico. Patterns of population differentiation in E. portoricensis, but not in E. antillensis, supported our hypotheses. For E. portoricensis, these patterns include: individuals isolated by long-term unsuitable climate in the Río Grande de Loíza Basin in eastern Puerto Rico belong to different genetic clusters; past and current climate strongly predicted genetic differentiation; and Cayey and Luquillo Mountains populations split prior to the last interglacial. For E. antillensis, these patterns include: genetic clusters did not fully correspond to predicted long-term unsuitable climate; and past and current climate weakly predicted patterns of genetic differentiation. Genetic signatures in E. antillensis are consistent with a recent range expansion into western Puerto Rico, possibly resulting from climate change and anthropogenic influences. As predicted, regions with a large area of long-term suitable climate were associated with higher genetic diversity in both species, suggesting larger and more stable populations. Finally, we discussed the implications of our findings for developing evidence-based management decisions for E. portoricensis, a taxon of special concern. Our findings illustrate the role of persistent suitable climatic conditions in promoting the persistence and diversification of tropical island organisms

    Keywords: Arctic, Boreal Forest, Ecological niche modeling, Lemmings, Machine learning, Megatransect sampling, Open-access data, RandomForests, Shrews, Voles

  • Beier P, de Albuquerque F (2015)

    Environmental diversity as a surrogate for species representation.

    Conservation biology : the journal of the Society for Conservation Biology.

    Because many species have not been described and most species ranges have not been mapped, conservation planners often use surrogates for conservation planning, but evidence for surrogate effectiveness is weak. Surrogates are well-mapped features such as soil types, landforms, occurrences of an easily observed taxon (discrete surrogates), and well-mapped environmental conditions (continuous surrogate). In the context of reserve selection, the idea is that a set of sites selected to span diversity in the surrogate will efficiently represent most species. Environmental diversity (ED) is a rarely used surrogate that selects sites to efficiently span multivariate ordination space. Because it selects across continuous environmental space, ED should perform better than discrete surrogates (which necessarily ignore within-bin and between-bin heterogeneity). Despite this theoretical advantage, ED appears to have performed poorly in previous tests of its ability to identify 50 × 50 km cells that represented vertebrates in Western Europe. Using an improved implementation of ED, we retested ED on Western European birds, mammals, reptiles, amphibians, and combined terrestrial vertebrates. We also tested ED on data sets for plants of Zimbabwe, birds of Spain, and birds of Arizona (United States). Sites selected using ED represented European mammals no better than randomly selected cells, but they represented species in the other 7 data sets with 20% to 84% effectiveness. This far exceeds the performance in previous tests of ED, and exceeds the performance of most discrete surrogates. We believe ED performed poorly in previous tests because those tests considered only a few candidate explanatory variables and used suboptimal forms of ED's selection algorithm. We suggest future work on ED focus on analyses at finer grain sizes more relevant to conservation decisions, explore the effect of selecting the explanatory variables most associated with species turnover, and investigate whether nonclimate abiotic variables can provide useful surrogates in an ED framework.

    Keywords: complementareidad, complementarity, conservation planning, diversidad ambiental, environmental diversity, minisum, planeación de la conservación, species accumulation index, surrogates, sustitutos, índice de acumulación de especies

  • Botello F, Sarkar S, Sánchez-Cordero V (2015)

    Impact of habitat loss on distributions of terrestrial vertebrates in a high-biodiversity region in Mexico

    Biological Conservation 184 59-65.

    Mexico is considered a country of biological megadiversity because of its exceptional species richness and endemism. However, much of Mexico’s biodiversity is under threat due to a variety of factors, in particular, habitat loss. The Mexican legal standard (Norma Oficial Mexicana; NOM-ECOL-059-2010) uses four criteria to analyze specieś extinction risk at a national scale. However, when prioritizing areas for biodiversity conservation it is also important to incorporate knowledge of the conservation status of species at a more localized scale (regional, state, or municipal levels) for identifying possible risks associated with population declines. This paper focuses on Guerrero, which is the fourth most biologically diverse state in Mexico. The total extent of the conservation areas in Guerrero is low, amounting to 0.09% of its total area. We analyzed data for 582 terrestrial vertebrate species in Guerrero (53 amphibians, 115 reptiles, 334 birds and 80 mammals), modeling their potential distribution using a maximum entropy algorithm, and 114,555 occurrence records, and 23 predictive environmental (19 climatic and four topographical) variables. The portion of the potential distribution for each species including only remnant natural habitat was designated as its predicted distribution. The area of the predicted distribution was used to compute the fraction of natural habitat remaining for each species overlapping within decreed protected areas at the state and national levels, that is, for Guerrero and all of Mexico. Results show significant differences in the fraction of species’ predicted distribution and species’ potential distribution at different scales (state and national) and differences between the vertebrate groups analyzed. Because quantitative conservation targets are typically set for individual species, this exercise enables an analysis of the impact of the habitat lost on each species’ distribution by assessing the fraction of its predicted distribution that coincides with protected areas. We conclude that this must be part of systematic conservation planning to prioritize areas for potential conservation in Guerrero.

    Keywords: Biodiversity, Deforestation, Distribution, Guerrero, Maximum entropy modeling, Protected areas