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opennotspecifiedApr 2020View details →

FIGURE1. Lateral view of Siphamia guttulata (CSIRO H 6930-02, 25 mm SL). Scale bar = 5 mm. in Redescription and distributional range extension of the Speckled Siphonfish, Siphamia guttulata (Pisces: Apogonidae)

FIGURE1. Lateral view of Siphamia guttulata (CSIRO H 6930-02, 25 mm SL). Scale bar = 5 mm.

opennotspecifiedJun 2020View details →

FIGURE 70 in Forty-seven new species of Sinopoda from Asia with a considerable extension of the distribution range to the South and description of a new species group (Sparassidae: Heteropodinae)

FIGURE 70. Distribution of Sinopoda species in Thailand, Laos, Vietnam and South-China.

Figure 5 in Demographic characteristics, seasonal range and habitat topography of Balkan chamois population in its southernmost limit of its distribution (Giona mountain, Greece)

Figure 5. Used elevation, inclination (violin plots) and aspect (histogram) of the Balkan chamois in Giona Mt. Black lines in the violin plots indicate 95% probability of occurrence in terms of Fixed Kernel Density Estimator and white dots indicate median values.

Figure 4. Seasonal range generated from a in Demographic characteristics, seasonal range and habitat topography of Balkan chamois population in its southernmost limit of its distribution (Giona mountain, Greece)

Figure 4. Seasonal range generated from a Fixed Kernel Density Estimator (FKDE) (95% probability) and respective core areas of Balkan chamois in Giona Mt for (A) winter, (B) spring, (C) summer and (D) autumn. In the upper right corner the diagram presents the delineation of the probability of species occurrence within the core area.

Figure 3 in Demographic characteristics, seasonal range and habitat topography of Balkan chamois population in its southernmost limit of its distribution (Giona mountain, Greece)

Figure 3. Annual range and core area of Balkan chamois in the study area, and overlap with the Natura 2000 site in Giona Mt.

Figure 1 in Demographic characteristics, seasonal range and habitat topography of Balkan chamois population in its southernmost limit of its distribution (Giona mountain, Greece)

Figure 1. Balkan chamois distribution in Greece, modified from Papaioannou and Kati 2007 (see Appendix 1).

opencc-zeroSep 2020View details →

Predictive multi-scale occupancy models at range-wide extents: effects of habitat and human disturbance on distributions of wetland birds

Aim: Predicting distributions is fundamental to ecology, yet hindered by spatially-restricted sampling, scale-dependent relationships, and detection error associated with field surveys. Predictive species distribution models (SDMs) are nonetheless vital for conservation of many species. We developed a framework for building predictive SDMs with multi-scale data, and used it to develop range-wide breeding-season SDMs for 14 marsh bird species of concern. Location: USA. Methods: We built SDMs using data from range-wide surveys conducted over 14 years, and habitat and disturbance covariates measured at multiple spatial scales. We built hierarchical occupancy models that included heterogeneity in detectability during sampling, and used Bayesian model selection to regulate model complexity (covariates and scales) based explicitly on spatial predictive abilities. We thus integrated model selection for optimizing out-of-sample prediction, range-wide sampling over broad conditions, multi-scale analyses and scale-optimization, and species-specific detectability for a suite of wide-ranging species. Results: Distributions of marsh birds were affected by local wetland conditions, but also by agricultural, urban, and hydrologic disturbances operating from local scales (100 – 500 m) to the watershed level. Variables measuring human disturbances improved prediction for most species, and every species was affected by attributes at > 1 scale. Five species showed evidence for continental-scale range contraction during the study. Main conclusions: We demonstrate how hierarchical occupancy models can be optimized for prediction across a species' range at the extent of a continent while also accounting for imperfect detection, and thus describe a generalizable approach that can be used for any species. We provide the first data-driven, empirical SDMs built at the range-wide extent for most of our 14 study species and demonstrate that previous studies focused on local distributions and the effects of fine-scale wetland vegetation missed important broad-scale drivers of occupancy for marsh birds.

opencc-zeroDec 2019View details →

Data from: High genetic diversity and stable Pleistocene distributional ranges in the widespread Mexican red oak Quercus castanea Née (1801) (Fagaceae)

The Mexican highlands are areas of high biological complexity where taxa of Nearctic and Neotropical origin and different population histories are found. To gain a more detailed view of the evolution of the biota in these regions, it is necessary to evaluate the effects of historical tectonic and climate events on species. Here, we analyzed the phylogeographic structure, historical demographic processes, and the contemporary period, Last Glacial Maximum (LGM) and Last Interglacial (LIG) ecological niche models of Quercus castanea, to infer the historical population dynamics of this oak distributed in the Mexican highlands. A total of 36 populations of Q. castanea were genotyped with seven chloroplast microsatellite loci in four recognized biogeographic provinces of Mexico: the Sierra Madre Occidental (western mountain range), the Central Plateau, the Trans-Mexican Volcanic Belt (TMVB, mountain range crossing central Mexico from west to east) and the Sierra Madre del Sur (SMS, southern mountain range). We obtained standard statistics of genetic diversity and structure and tested for signals of historical demographic expansions. A total of 90 haplotypes were identified and 29 of these haplotypes were restricted to sngle populations. The within-population genetic diversity was high (mean hS = 0.72), and among-population genetic differentiation showed a strong phylogeographic structure (NST = 0.630 > GST = 0.266; P < 0.001). Signals of demographic expansion were identified in the TMVB and the SMS. The ecological niche models suggested a considerable percentage of stable distribution area for the species during the LGM and connectivity between the TMVB and the SMS. High genetic diversity, strong phylogeographic structure and potential distribution models suggest in situ permanence of Q. castanea populations with large effective population sizes. The complex geological and climatic histories of the TMVB help to explain the origin and maintenance of a large proportion of the genetic diversity in this oak species.

opencc-zeroDec 2017View details →

Data from: The demographic history of Atlantic salmon (Salmo salar) across its distribution range reconstructed from approximate Bayesian computations

Understanding the dual roles of demographic and selective processes in the buildup of population divergence is one of the most challenging tasks in evolutionary biology. Here, we investigated the demographic history of Atlantic Salmon across the entire species range using 2035 anadromous individuals from North America and Eurasia. By combining results from admixture graphs, geo-genetic maps and an Approximate Bayesian Computation (ABC) framework, we validated previous hypotheses pertaining to secondary contact between European and Northern American populations, but also identified secondary contacts in European populations from different glacial refugia. We further identified the major sources of admixture from the southern range of North America into more northern populations along with a strong signal of secondary gene flow between genetic regional groups. We hypothesize that these patterns reflects the spatial redistribution of ancestral variation across the entire North American range. Results also support a role for linked selection and differential introgression that likely played an under-appreciated role in shaping the genomic landscape of species in the Northern hemisphere. We conclude that studies between partially isolated populations should systematically include heterogeneity in selective and introgressive effects among loci to perform more rigorous demographic inferences of the divergence process.

opencc-zeroDec 2009View details →

Data from: Correlations of life-history and distributional-range variation with salamander diversification rates: evidence for species selection

Evolutionary biologists have long debated the relative influence of species selection on evolutionary patterns. As a test, we apply a statistical phylogenetic approach to evaluate the influence of traits related to species distribution and life-history characteristics on patterns of diversification in salamanders. We use independent contrasts to test trait-mediated diversification while accommodating phylogenetic uncertainty in relationships among all salamander families. Using a neontological data set, we find several species-level traits to be variable, heritable, and associated with differential success (i.e., higher diversification rates) at higher taxonomic categories. Specifically, the macroecological trait of small geographic-range size is strongly correlated with a higher rate of net diversification. We further consider the role that plasticity in life-history traits appears to fulfill in macroevolutionary processes of lineage divergence and durability. We find that pedotypy—wherein some, but not all, organisms of a species mature in the gilled form without metamorphosing—is also associated with higher net diversification rate than is the absence of developmental plasticity. Often dismissed as an insignificant process in evolution, we provide direct evidence for the role of species selection in lineage diversification of salamanders.

opennotspecifiedDec 2015View details →

FIGURES 19–21 in Astrotischeria neotropicana sp. nov. — a leaf-miner on Sida, Malvaceae, currently with the broadest distribution range in the Neotropics (Lepidoptera, Tischeriidae)

FIGURES 19–21. Male genitalia of Astrotischeria neotropicana sp. nov., paratype, slide no. AD718.

FIGURE 13 in Parrotfishes (Teleostei: Labridae: Scarini) of the Socotra Archipelago: Diversity and distributional biogeography, including a range extension of Scarus zufar Randall & Hoover, 1995

FIGURE 13. Scarus tricolor, terminal male, Roosh, Socotra Island, 14 m depth.

FIGURE 12 in Parrotfishes (Teleostei: Labridae: Scarini) of the Socotra Archipelago: Diversity and distributional biogeography, including a range extension of Scarus zufar Randall & Hoover, 1995

FIGURE 12. Scarus scaber, initial phase, Samha Island, Socotra Archipelago, 10 m depth.

FIGURE 2 in Parrotfishes (Teleostei: Labridae: Scarini) of the Socotra Archipelago: Diversity and distributional biogeography, including a range extension of Scarus zufar Randall & Hoover, 1995

FIGURE 2. Chlorurus sordidus, terminal male, Samha Island, Socotra Archipelago, 10 m depth.

FIGURE 1 in Parrotfishes (Teleostei: Labridae: Scarini) of the Socotra Archipelago: Diversity and distributional biogeography, including a range extension of Scarus zufar Randall & Hoover, 1995

FIGURE 1. Overview map of the Socotra Archipelago, with key marine locations.

FIGURE 10 in Parrotfishes (Teleostei: Labridae: Scarini) of the Socotra Archipelago: Diversity and distributional biogeography, including a range extension of Scarus zufar Randall & Hoover, 1995

FIGURE 10. Scarus niger, terminal male, Qariah, Socotra Island, 4 m depth.

restrictedcc-by-4.0Mar 2024View details →

Data from: Distribution models predict climate-related range alteration or extinction of eleven threatened tropical rainforest trees in the Western Ghats

This dataset contains information related to species occurence data and species distribution modeling (SDM) analysisr of eleven threatened tree species. Occurrences are compiled from extensive field surveys in the Anamalai Hills along with data from the Global Biodiversity Information Facility (GBIF.org) and earlier work done within the southern Western Ghats, India. References: Page, N. V., & Shanker, K. (2020). Climatic stability drives latitudinal trends in range size and richness of woody plants in the Western Ghats, India. PLOS ONE, 15(7), e0235733. https://doi.org/10.1371/journal.pone.0235733 GBIF.org (2022) GBIF Occurrence Download, 2 August 2022. DOI:10.15468/dl.gnvuxj AUTHOR #1 1. Name: A.P. Madhavan 2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India 3. Email address: madhavan@ncf-india.org 4. ORCID: https://orcid.org/0009-0009-2754-8256 AUTHOR #2 1. Name: Kshama Bhat 2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India 3. Email address: kshama@ncf-india.org 4. ORCID: ORCID: https://orcid.org/0000-0002-6190-2687 AUTHOR #3 1. Name: Srinivasan Kasinathan 2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India 3. Email address: srini@ncf-india.org 4. ORCID: https://orcid.org/0000-0001-7323-6653 AUTHOR #4 1. Name: Divya Mudappa  2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India 3. Email address: divya@ncf-india.org  4. ORCID: https://orcid.org/0000-0001-9708-4826 AUTHOR #5 1. Name: Navendu Page 2. Work Address: Wildlife Institute of India, Post Box No. 18, Chandrabani, Dehradun, Uttarakhand 248001, India 3. Email address: navendu.page@gmail.com 4. ORCID: ORCID: https://orcid.org/0000-0002-9413-7571 AUTHOR #6 1. Name: T. R. Shankar Raman  2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India 3. Email address: trsr@ncf-india.org  4. ORCID: https://orcid.org/0000-0002-1347-3953 Keywords: tropical rainforest, climate change, tree distributions, species distribution models, range shifts, Western Ghats Geographic Coverage: 1. Location/Study Area: Southern Western Ghats Montane Rain Forests, Southern Western Ghats Moist Deciduous Forests, India 2. GPS coordinates: SWG (73.95° – 80.33° E, 8.06° – 13.11°N)  Temporal coverage Starts: 2020-08-01 Ends: 2024-03-28 Besides this README.txt file, the dataset includes three comma-delimited text files (csv); two R scripts, and 1 kml file of surveyed trails. CSV files with the data in columns as explained below: 1) Focal_Tree_Dat.csv Comp: Number identifier FT_ID: Unique tree no for each individual Focal_tree: Scientific name of species Date: Date of occurrence observation Place: Area/locality description Trail: Unique trail ID Waypoint: Waypoint number      Time: Time in hh:mm format     Location: Specific description of occurrence locality     Latitude: Latitude in decimal degrees N  Longitude: Longitude in decimal degrees E  Elevation: Elevation in metres     Slope: Cateory of slope  ID_Notes: Notes on identification Phenophase: Phenophase expression at the time of observation                              GBH: Girth at breast height in centimetres (comma separated list of numbers in case of multi-stemmed trees)      Tree_ht: Tree height in metres Canopy_ht: Maximimum height of the surrounding canopy in metres Substrate: Soil substrate composition Invasives: Name of invasive species (if present)     Stature: Vegetation strata position  Relatively: Stature of focal individual relative to other surrounding individuals  Deadwood: Description of deadwood on the tree     Damage: Description of damage on the bole  Shape: Description of tree canopy shape Closure: Canopy closure at focal tree     Seedlings: Number of conspecific seedlings present in 5 m radius of focal tree     Saplings: Number of conspecific saplings present in 5 m radius of focal tree Trees:    Number of conspecific trees present in 5 m radius of focal tree Remarks: Remarks  2) Ffspecies.csv Source: Source of occurrence     ID: State/location of occurrence Region: Biogeographic region of occurrence  decimalLatitude: Latitude in decimal degrees N decimalLongitude: Longitude in decimal degrees E species: Scientific name of species 4) ft_surveys.csv Date: Date of survey of sample trail Prot_type: Category indicating whether protected area or fragment     Place: Area/locality description Route_description: Specific landmark description of trail Trail: Unique trail ID     Trail_distance: Tracked distance of trail in km     Corrected_trail_distance: Corrected distance of trail in km Track_filename_kml: File name of gps track Sample_collected: Name of species if sample collected     Observers: Name of observers      Remarks: Remarks ANALYSES SCRIPTS flexsdm_script.R Script containing the analysis of all maxent distribution modeling and associated analysis Franklinia_density.Rmd Script of density and abundance related analysis

opencc-zeroNov 2021View details →

Geographic range estimates and environmental requirements for the harpy eagle derived from spatial models of current and past distribution

Understanding species-environment relationships is key to defining the spatial structure of species distributions and develop effective conservation plans. However, for many species this baseline information does not exist. With reliable presence data, spatial models that predict geographical ranges and identify environmental processes regulating distribution are a cost-effective and rapid method to achieve this. Yet these spatial models are lacking for many rare and threatened species, particularly in tropical regions. The harpy eagle (Harpia harpyja) is a Neotropical forest raptor of conservation concern with a continental distribution across lowland tropical forests in Central and South America.Currently the harpy eagle faces threats from habitat loss and persecution and is categorised as Near-Threatened by the International Union for the Conservation of Nature (IUCN). Within a point process modelling (PPM) framework, we use presence-only occurrences with climatic and topographical predictors to estimate current and past distributions and define environmental requirements using Ecological Niche Factor Analysis. The current PPM prediction had high calibration accuracy (Continuous Boyce Index = 0.838) and was robust to null expectations (pROC ratio = 1.407). Three predictors contributed 96 % to the PPM prediction, with Climatic Moisture Index the most important (72.1 %), followed by minimum temperature of the warmest month (15.6 %) and Terrain Roughness Index (8.3 %). Assessing distribution in environmental space confirmed the same predictors explaining distribution, along with precipitation in the wettest month. Our reclassified binary model estimated a current range size 11 % smaller than the current IUCN range polygon. Paleoclimatic projections combined with the current model predicted stable climatic refugia in the central Amazon, Guyana, eastern Colombia, and Panama. We propose a data-driven geographical range to complement the current IUCN range estimate, and that despite its continental distribution this tropical forest raptor is highly specialized to specific environmental requirements.