Range Maps Research Articles

Extralimital terrestrials: A reassessment of range limits in Alaska's land mammals.

Understanding and mitigating the effects of anthropogenic climate change on species distributions requires the ability to track range shifts over time. This is particularly true for species occupying high-latitude regions, which are experiencing more extreme climate change than the rest of the world. In North America, the geographic ranges of many mammals reach their northernmost extent in Alaska, positioning this region at the leading edge of climate-induced distribution change. Over a decade has elapsed since the publication of the last spatial assessments of terrestrial mammals in the state. We compared public occurrence records against commonly referenced range maps to evaluate potential extralimital records and develop repeatable baseline range maps. We compared occurrence records from the Global Biodiversity Information Facility for 61 terrestrial mammal species native to mainland Alaska against a variety of range estimates (International Union for Conservation of Nature, Alaska Gap Analysis Project, and the published literature). We mapped extralimital records and calculated proportions of occurrences encompassed by range extents, measured mean direction and distance to prior range margins, evaluated predictive accuracy of published species models, and highlighted observations on federal lands in Alaska. Range comparisons identified 6,848 extralimital records for 39 of 61 (63.9%) terrestrial mainland Alaskan species. On average, 95.5% of Alaska Gap Analysis Project occurrence records and ranges were deemed accurate (i.e., > 90.0% correct) for 31 of 37 species, but overestimated extents for 13 species. The International Union for Conservation of Nature range maps encompassed 68.1% of occurrence records and were > 90% accurate for 17 of 39 species. Extralimital records represent either improved sampling and digitization or actual geographic range expansions. Here we provide new data-driven range maps, update standards for the archiving of museum-quality locational records and offer recommendations for mapping range changes for monitoring and conservation.

Response to Arbogast and Kerhoulas

Abstract We welcome feedback on the range maps published in Marsh et al. (2022) where it constructively improves our knowledge on species distributions. Unfortunately, we are concerned that criticisms raised by Arbogast and Kerhoulas are steps backward, not forward, particularly as they did not access the original range map data of Marsh et al. (2022). We stress that evaluating range maps using Global Biodiversity Information Facility data without the necessary quality control and filtering will lead to flawed interpretations—using the same approach, an even greater proportion, >99.5%, of IUCN mammal range maps would fail to meet their expectations. We take this opportunity to highlight the fine-scale inaccuracies, scale limitations, and range map variance that are expected across all expert range map sources and that any researcher should consider during any analysis. Finally, we again announce the availability of an online tool for providing annotations and proposing adjustments to range maps, and suggest this as a more appropriate forum for constructively and transparently improving range maps.

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

Abstract In a recent paper titled Expert range maps of global mammal distributions harmonised to three taxonomic authorities, Marsh et al. (2022) introduced a series of new geographic range maps for all extant species of mammals and made these maps available on the Map of Life (MoL) website (www.mol.org). The title of the paper and inclusion of over 140 prominent mammalogists and biogeographers as coauthors strongly suggested that these new range maps were carefully vetted. However, when examining the maps of Marsh et al. (2022) on the MoL web platform, we found a variety of serious problems, including, but not limited to: range exaggerations (inclusion of substantial geographic areas not represented by specimen records or verified observations); range maps that are geographically shifted so that species are shown as occurring in areas in which they do not, and not occurring in areas in which they do (and in some cases, these new maps do not even encompass the type locality of a species); range maps that simply omit peripheral populations of conservation concern; and range maps for fully marine mammals (i.e., those that do not spend any time on land) that include large swaths of both insular and continental landmasses. Overall, we evaluated the new “expert” mammal range maps on the MoL platform for 78 species (retrieved between 31 March 2022 and 1 April 2023) and show that there are serious, systemic problems with these maps, and that these problems are both geographically and taxonomically widespread. As such, we caution researchers to carefully review and evaluate the range maps of Marsh et al. (2022) on the MoL before using them for any research purpose—including conservation, biogeographical, and macroecological analyses of mammals.

Zoogeographical regions in the Atlantic Forest: patterns and potential drivers

AbstractAimTo delineate present‐day zoogeographical regions of terrestrial vertebrates (frogs, lizards, snakes, birds and non‐volant mammals) in the Atlantic Forest. Within each taxonomic group, we examine the relative importance of abrupt climatic transitions, orographic barriers, past climate change and rivers in shaping zoogeographical boundaries.LocationSouth America's Atlantic Forest.MethodsWe applied a network‐based method to delineate zoogeographical regions, using distribution data (range maps) for 455 species of frogs, 103 lizards, 220 snakes, 917 birds and 202 non‐volant mammals, in 50 × 50 km grid cells. We used hierarchical generalized linear mixed‐effects models to test environmental predictors associated with zoogeographical boundaries. Finally, we intersected the bioregion maps delineated for each group to identify general patterns across all vertebrates.ResultsWe identified four zoogeographical regions for birds and snakes, and five for frogs, lizards and non‐volant mammals. Depending on the group, contemporary and past climate conditions, elevation variation and/or rivers were associated with zoogeographical boundaries. The combined maps indicate that the Atlantic Forest retains four spatially cohesive zoogeographical regions based on present‐day distribution of vertebrates.Main conclusionsCross‐taxon congruence indicates that the geographical and environmental characteristics of the Atlantic Forest have a strong influence on the location of zoogeographical regions for vertebrates. In contrast, transition zones appear to be associated with the spatial distribution of life history traits of each group, potentially explaining the observed differences in the number of bioregions across groups and the position of zoogeographical boundaries. This work paves the way for further research into the evolutionary assembly of the Atlantic Forest's zoogeographical regions and may help inform conservation priorities for maintaining their distinctive faunas.

Updated range map of an endangered salamander and congeneric competitor reveals different niche preferences.

Estimating distributions for cryptic and highly range-restricted species induces unique challenges for species distribution modeling. In particular, bioclimatic covariates that are typically used to model species ranges at regional and continental scales may not show strong variation at scales of 100s and 10s of meters. This limits both the likelihood and usefulness of correlated occurrence to data typically used in distribution models. Here, we present analyses of species distributions, at 100 × 100 m resolution, for a highly range restricted salamander species (Shenandoah salamander, Plethodon shenandoah) and a closely related congener (red-backed salamander, Plethodon cinereus). We combined data across multiple survey types, account for seasonal variation in availability of our target species, and control for repeated surveys at locations- all typical challenges in range-scale monitoring datasets. We fit distribution models using generalized additive models that account for spatial covariates as well as unexplained spatial variation and spatial uncertainty. Our model accommodates different survey protocols using offsets and incorporates temporal variation in detection and availability resulting from survey-specific variation in temperature and precipitation. Our spatial random effect was crucial in identifying small-scale differences in the occurrence of each species and provides cell-specific estimates of uncertainty in the density of salamanders across the range. Counts of both species were seen to increase in the 3 days following a precipitation event. However, P. cinereus were observed even in extremely wet conditions, while surface activity of P. shenandoah was associated with a more narrow range. Our results demonstrate how a flexible analytical approach improves estimates of both distribution and uncertainty, and identify key abiotic relationships, even at small spatial scales and when scales of empirical data are mismatched. While our approach is especially valuable for species with small ranges, controlling for spatial autocorrelation, estimating spatial uncertainty, and incorporating survey-specific information in estimates can improve the reliability of distribution models in general.

Expert‐based range maps cannot be replicated using data‐driven methods but macroecological conclusions arising from them can

AbstractAimAnswering many fundamental and applied scientific questions relies on accurate geographic range maps for species, such as those compiled by experts working with the International Union for Conservation of Nature (IUCN). However, these maps are resource demanding to produce and only available for a limited number of organisms. Here, we test to what extent standardized, data‐driven methods based on publicly available occurrences can reproduce expert‐based IUCN range maps and the macroecological conclusions drawn from them.LocationGlobal.Time PeriodPresent.TaxaBirds.Materials and MethodsWe estimated the geographic ranges for 7385 non‐marine bird species which either were non‐migratory or had spatially connected breeding and wintering ranges from publicly available, georeferenced point occurrences. We then quantified the spatial overlap between these range estimates and the IUCN expert‐derived range estimates. Finally, we compared global species richness patterns and the environmental correlates that emerge from both approaches.ResultsWe find that range estimates based on point occurrence records overlap on average 52% with expert range estimates for the same species. The global species richness patterns estimated under both approaches are overall similar but show local and regional differences, for example, in the tropical Andes of northern South America and the Central Arc region of Africa. The estimated global drivers of richness are similar.Main ConclusionsExpert‐derived estimates of species distributions are not reproducible by data‐driven approaches relying on currently available public records, even for well‐documented taxa such as birds. However, these discrepancies do not substantially change our macroecological understanding of global drivers of bird diversity.

Update of the geographic range of Humboldt's squirrel monkeys (Saimiri cassiquiarensis cassiquiarensis Lesson, 1840) using a model-based approach.

Saimiri cassiquiarensis cassiquiarensis (Cebidae) is a primate subspecies with a wide distribution in the Amazonian region of Brazil, Colombia, and Venezuela. However, the boundaries of its geographic range remain poorly defined. This study presents new occurrence localities for this subspecies and updates its distribution using a compiled data set of 140 occurrence records based on literature, specimens vouchered in scientific collections, and new field data to produce model-based range maps. After cleaning our data set, we updated the subspecies' extent of occurrence, which was used in model calibration. We then modeled the subspecies' range using a maximum entropy algorithm (MaxEnt). The final model was adjusted using a fixed threshold, and we revised this polygon based on known geographic barriers and parapatric congeneric ranges. Our findings indicate that this subspecies is strongly associated with lowland areas, with consistently high daily temperatures. We propose modifications to all range boundaries and estimate that 3% of the area of occupancy (AOO,as defined by IUCN) has already been lost due to deforestation, resulting in a current range of 224,469 km2. We also found that 54% of their AOO is currently covered by protected areas (PAs). Based on these results, we consider that this subspecies is currently properly classified as Least Concern, because it occupies an extensive range, which is relatively well covered by PAs, and is currently experiencing low rates of deforestation.

Longitudinal population dynamics of Mediterranean-Atlantic Arbutus during the last 30 ka

The current distribution of the genus Arbutus in the Old World prompts questions about its long-term population dynamics, location and extent of refuge areas, and modern vulnerability in relation to climate change and human activity. Our work aims to address these questions by combining modern occurrence data with a comprehensive survey of pollen and macrofossil records. Range maps of past distribution have been produced for the last 32 ka to investigate geographical trends in population dynamics and the timing of the appearance of Arbutus across different biogeographical regions. In the Atlantic domain, Arbutus has been consistently present during the last 32 ka, even during the Last Glacial Maximum. In the central and eastern Mediterranean regions, it progressively increased since the beginning of the Holocene, appearing along the coasts of the Black Sea and in the Levant during the Middle Holocene. In addition, the dynamics of Arbutus in a number of peripherals stands (Ireland, Canary Islands, Cyrenaica, Crimea, and Black Sea coasts) is discussed. The palaeobotanical evidence suggests that the delayed emergence of eastern populations and peripheral stands in the fossil record may be ascribed to a very low population density, rather than to a sequential migration process from the western sectors of the range. The comparison of fossil records and modern occurrences highlights an overall temporal continuity between long-term persistence areas and current centers of gravity and calls for density-weighted ecological models that may contribute to an informed assessment of conservation actions and strategies.

Combining camera trap surveys and IUCN range maps to improve knowledge of species distributions.

Reliable maps of species distributions are fundamental for biodiversity research and conservation. The International Union for Conservation of Nature (IUCN) range maps are widely recognized as authoritative representations of species' geographic limits, yet they might not always align with actual occurrence data. In recent area of habitat (AOH) maps, areas that are not habitat have been removed from IUCN ranges to reduce commission errors, but their concordance with actual species occurrence also remains untested. We tested concordance between occurrences recorded in camera trap surveys and predicted occurrences from the IUCN and AOH maps for 510 medium- to large-bodied mammalian species in 80 camera trap sampling areas. Across all areas, cameras detected only 39% of species expected to occur based on IUCN ranges and AOH maps; 85% of the IUCN only mismatches occurred within 200km of range edges. Only 4% of species occurrences were detected by cameras outside IUCN ranges. The probability of mismatches between cameras and the IUCN range was significantly higher for smaller-bodied mammals and habitat specialists in the Neotropics and Indomalaya and in areas with shorter canopy forests. Our findings suggest that range and AOH maps rarely underrepresent areas where species occur, but they may more often overrepresent ranges by including areas where a species may be absent, particularly at range edges. We suggest that combining range maps with data from ground-based biodiversity sensors, such as camera traps, provides a richer knowledge base for conservation mapping and planning.

Large‐scale validation of 46 invasive species assays using an enhanced in silico framework

AbstractThe need for widespread occurrence data to inform species conservation has prompted interest in large, national‐scale environmental DNA (eDNA) monitoring strategies. However, targeted eDNA assays are seldom validated for use across broad geographic areas. Here, we validated 46 new and previously published probe‐based qPCR assays targeting invasive species throughout the continental United States. We drew upon current taxonomies, range maps, publicly available sequences, and tissue archives to evaluate all potentially sympatric confamilial species and genetically similar extrafamilial taxa. Out of 5276 unique assay‐nontarget taxon combinations, we were able to test 4206 (80%). We characterized levels of validation and specificity for each of eight federal geographic regions and provided an online tool with state‐level information, as well as detailed assay descriptions in an appendix. Specificity testing benefited from extensive use of eDNAssay—a machine learning classifier trained to predict qPCR cross‐amplification—which we found to be 96% accurate in 649 unique tests that underwent paired in silico and in vitro testing. Predictions of assay specificity (the true negative rate) were 98–100% accurate, depending on the classification threshold used. This work provides both an immediate resource for invasive species surveillance and demonstrates an enhanced in silico, geographically subdivided validation framework to aid in future large‐scale validation efforts.

Blockchain-Enabled Transfer Learning for Vulnerability Detection and Mitigation in Maritime Logistics

Abstract With the increasing demand for efficient maritime logistic management, industries are striving to develop automation software. However, collecting data for analytics from diverse sources like shipping routes, weather conditions, historical incidents, and cargo specifications has become a challenging task in the distribution environment. This challenge gives rise to the possibility of faulty products and traditional testing techniques fall short of achieving optimal performance. To address this issue, we propose a novel decentralised software system based on Transfer Learning and blockchain technology named as BETL (Blockchain -Enabled Transfer Learning). Our proposed system aims to automatically detect and prevent vulnerabilities in maritime operational data by harnessing the power of transfer learning and smart contract-driven blockchain. The vulnerability detection process is automated and does not rely on manually written rules. We introduce a non-vulnerability score range map for the effective classification of operational factors. Additionally, to ensure efficient storage over the blockchain, we integrate an InterPlanetary File System (IPFS). To demonstrate the effectiveness of transfer learning and blockchain integration for secure logistic management, we conduct a testbed-based experiment. The results show that this approach can achieve high precision (98.00%), detection rate (98.98%), accuracy (97.90%), and F-score (98.98), which highlights its benefits in enhancing the safety and reliability of maritime logistics processes. Additionally, the computational time of BETL (the proposed approach) was improved by 18.9% compared to standard transfer learning.

Updated distribution of spotted hyaenas in Gabon reveals resident populations

AbstractSpotted hyaena distribution currently widely encompasses sub‐Saharan Africa, apart from the Congo Basin. Formerly described as residents of Gabon but considered extinct, vagrant individuals have been recorded since 2003, but no systematic species presence assessment has been made. Based on records of killed individuals, tracks and camera‐trap sightings, we show that not only vagrant individuals are roaming in Gabon, but a small resident population occurs in the North‐East of the country. The records collated here formed the basis for spotted hyaenas to be listed as protected in Gabon, were included in the IUCN Red List species' range map update and showcased the importance of large‐scale by‐catch data analysis in updating species distributions.

A collection and analysis of amphibians and reptiles from Nicaragua with new country and departmental records

Nicaragua is a biodiverse country, but documented herpetological specimens are underrepresented compared to neighboring countries. In 2018 we conducted a collaborative expedition between the University of Michigan Museum of Zoology and Nicaraguan biologists. We visited sites in the Pacific Low‑ lands, Caribbean Lowlands, and the Central Highlands, representing the three major biogeographic regions of Nicaragua. We collected specimens of 100 species from a total of 106 encountered. We provide acces‑ sion numbers and morphological, genetic, and ecological information for these specimens. We recorded 23 new departmental records and the first country record of Metlapilcoatlus indomitus (Smith & Ferrari‑Castro, 2008), filling gaps in the known distribution of the species within Nicaragua and across Central America. When available for each species, we provide range maps and comparative genetic trees including conspecific reference sequences from the region, making this work a significant addition to existing checklists of the herpetofauna in Nicaragua.

Climate change-induced degradation of expert range maps drawn for kissing bugs (Hemiptera: Reduviidae) and long-standing current and future sampling gaps across the Americas.

Kissing bugs are the vectors of Trypanosoma cruzi, the etiological agent of Chagas disease (CD). Despite their epidemiological relevance, kissing bug species are under sampled in terms of their diversity and it is unclear what biases exist in available kissing bug data. Under climate change, range maps for kissing bugs may become less accurate as species shift their ranges to track climatic tolerance. Quantify inventory completeness in available kissing bug data. Assess how well range maps are at conveying information about current distributions and potential future distributions subject to shift under climate change. Intersect forecasted changes in kissing bug distributions with contemporary sampling gaps to identify regions for future sampling of the group. Identify whether a phylogenetic signal is present in expert range knowledge as more closely related species may be similarly well or lesser understood. We used species distribution models (SDM), specifically constructed from Bayesian additive regression trees, with Bioclim variables, to forecast kissing bug distributions into 2100 and intersect these with current sampling gaps to identify priority regions for sampling. Expert range maps were assessed by the agreement between the expert map and SDM generated occurrence probability. We used classical hypothesis testing methods as well as tests of phylogenetic signal to meet our objectives. Expert range maps vary in their quality of depicting current kissing bug distributions. Most expert range maps decline in their ability to convey information about kissing bug occurrence over time, especially in under sampled areas. We found limited evidence for a phylogenetic signal in expert range map performance. Expert range maps are not a perfect account of species distributions and may degrade in their ability to accurately convey distribution knowledge under future climates. We identify regions where future sampling of kissing bugs will be crucial for completing biodiversity inventories.

Primeiro registro brasileiro de Chiroxiphia napensis (Aves: Pipridae) e revisão da distribuição do complexo C. pareola na Amazônia

ABSTRACT We present the first Brazilian record of Chiroxiphia napensis, documented by an adult male specimen collected on the right bank of the upper Japurá River. We also compiled verifiable records of all Amazonian taxa in the C. pareola complex to update their range maps. New records extended considerably the ranges of all taxa. By assuming river-delimited distributions to infer areas from point records, we generated a predictive distributional map that suggests testable hypotheses about occurrence in unstudied areas and that pinpoints topics for future research. We interpret C. napensis as endemic to the Amazon-Japurá interfluve, its range extending narrowly beyond this area in the foothills of the Andes. We suggest that the unusual distribution pattern of C. regina could be the result of river avulsion. We also detected a region of possible contact between C. regina and C. pareola, and a large area in northern Amazonia from which the complex appears to be absent.

Potential application of GBIF platform for flora inventory of Karaganda region

The current biodiversity inventory has important scientific and practical implications for the country. In Kazakhstan, data on the flora of spore and vascular plants are outdated; there is a significant gap in assessing the current species composition of certain regions of Kazakhstan, including Central Kazakhstan (Karaganda and Ulytau regions). The problems of formation of a modern flora abstract are determined by the need to use the entire volume of accumulated information, both for individual findings of naturalists and multi-year collections in domestic and international herbarium collections. When carrying out research to analyze the current state of the flora of Karaganda region, the GBIF platform resources containing information on the biological diversity of flora and fauna were used. Data analysis showed that the platform has more than 130 thousand records of vascular plant finds for the territory of Kazakhstan, including 2241 records for Karaganda region with geo-referencing. The main funds containing the largest number of collections made on the territory of our region were determined. The stages of data processing and geo-linking of herbarium collections are defined. In general, a high potential for supplementing field collections with GBIF data to clarify the distribution of individual taxa and make range maps was determined.

Range Map Interpolation-Based 3-D LiDAR Truncated Signed Distance Fields Mapping in Outdoor Environments

Range Map Interpolation-Based 3-D LiDAR Truncated Signed Distance Fields Mapping in Outdoor Environments

To the methodology for the study of intraspecific variability and selection of wild forms of Viburnum opulus L.

The methodological recommendation for the study of intraspecific variability and the selection of wild-growing promising for breedingforms of common Viburnumis written on the basis of a large amount of factual material obtained from the study of this species in the East Kazakhstan region. It includes an assessment of the current state of Viburnum opulus L. populations, with range mapping in ArcMap and ArcGis programs. The geobotanical, phytocenotic description is given. First, the forms are described according to 25 quantitative and qualitative features. Then, on the basis of this, the selection of promising forms, the collection of seeds and cloning with green cuttings is carried out. The distribution of Viburnum plants occurred according to the degree of flowering, fruiting, fruit length and diameter. The data were divided into classes with the smallest, average and largest values into five groups, by weight and number of fruits into four groups. The scoring system was applied to seven characteristics: the general condition of plants, winter hardiness, the degree of flowering and fruiting, color, taste, and the nature of the detachment of fruits. The study of endogenous variability of morphological and economic-biological characters is carried out in the crown of one individual. After studying the average indicator of the trait and the amplitude of its variation for different individuals, they proceed to the study of intra-population variability. After mathematical processing, a questionnaire is filled out for each plant according to the selected form, which will make it possible to better represent the studied form to study genotypic and phenotypic variability in the future. The use of this recommendation in research work will allow assessing the genetic potential of the species, the level of its intraspecific variability, and selecting promising forms.

The influence of the number and distribution of background points in presence-background species distribution models

Species distribution models (SDMs), which relate recorded observations (presences) and absences or background points to environmental characteristics, are powerful tools used to generate hypotheses about the biogeography, ecology, and conservation of species. Although many researchers have examined the effects of presence and background point distributions on model outputs, they have not systematically evaluated the effects of various methods of background point sampling on the performance of a single model algorithm across many species. Therefore, a consensus on the preferred methods of background point sampling is lacking. Here, we conducted presence-background SDMs for 20 vertebrate species in North America under a variety of background point conditions, varying the number of background points used, the size of the buffer used to constrain the background points around the occurrences, and the percentage of background points sampled within the buffer (“spatial weighting”). We evaluated the accuracy and transferability of the models using Boyce index, overlap with expert-generated range maps, and area overpredicted and underpredicted by the SDM (and AUC for comparability with other studies).SDM performance is highly dependent on the species modelled but is affected by the number and spread of background points. Models with little spatial weighting had high accuracy (overlap values), but extreme extrapolation errors and overprediction. In contrast, SDMs with high transferability (high Boyce index values and low overprediction) had moderate-to-high spatial weighting. These results emphasize the importance of both background points and evaluation metric selection in SDMs. For other, more successful metrics, using many background points with spatial weighting may be preferred for models with large extents. These results can assist researchers in selecting the background point parameters most relevant for their research question, allowing them to fine-tune their hypotheses on the distribution of species through space and time.

Shifting hotspots: Climate change projected to drive contractions and expansions of invasive plant abundance habitats

AbstractAimPreventing the spread of range‐shifting invasive species is a top priority for mitigating the impacts of climate change. Invasive plants become abundant and cause negative impacts in only a fraction of their introduced ranges, yet projections of invasion risk are almost exclusively derived from models built using all non‐native occurrences and neglect abundance information.LocationEastern USA.MethodsWe compiled abundance records for 144 invasive plant species from five major growth forms. We fit over 600 species distribution models based on occurrences of abundant plant populations, thus projecting which areas in the eastern United States (U.S.) will be most susceptible to invasion under current and +2°C climate change.ResultsWe identified current invasive plant hotspots in the Great Lakes region, mid‐Atlantic region, and along the northeast coast of Florida and Georgia, each climatically suitable for abundant populations of over 30 invasive plant species. Under a +2°C climate change scenario, hotspots will shift an average of 213 km, predominantly towards the northeast U.S., where some areas are projected to become suitable for up to 21 new invasive plant species. Range shifting species could exacerbate impacts of up to 40 invasive species projected to sustain populations within existing hotspots. On the other hand, within the eastern U.S., 62% of species will experience decreased suitability for abundant populations with climate change. This trend is consistent across five plant growth forms.Main ConclusionsWe produced species range maps and state‐specific watch lists from these analyses, which can inform proactive regulation, monitoring, and management of invasive plants most likely to cause future ecological impacts. Additionally, areas we identify as becoming less suitable for abundant populations could be prioritized for restoration of climate‐adapted native species. This research provides a first comprehensive assessment of risk from abundant plant invasions across the eastern U.S.