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opencc-by-4.0Dec 2020View details →

Convergent geographic patterns between grizzly bear population genetic structure and Indigenous language groups in coastal British Columbia

Microsatellite loci calls, sex, and mean centre detection per individual (GrizzlyMicroLociMeanXY.csv) and code associated with the paper: "Convergent geographic patterns between grizzly bear population genetic structure and Indigenous language groups in coastal British Columbia". All code is from published R packages or GitHub repositories not created by the author. Code used is best described in these alternate resources.

opencc-by-4.0Dec 2021View details →

Table S1. Geographical localization of Pinus pseudostrobus Lindley. specimens used in the study and concordance of morphological identification with real-time PCR-HRM assay for Pinus pseudostrobus varieties pseudostrobus, apulcensis, oaxacana and coatepecensis, based on the cluster pattern.

File encloses geographical location of collected Pinus pseudostrobus samples in México, as well as haplotype grouping obtaines from HRM analysis

opencc-by-4.0Nov 2013View details →

Fig. 2. – Species prediction for a grid cell. A in Geographical patterns of woody plants' functional traits in Burkina Faso

Fig. 2. – Species prediction for a grid cell. A. Average of maximal plant size; B. Percentage of spinescent species; C. Percentage of species containing latex; D. Percentage of species with compound leaves.

opencc-by-4.0Nov 2013View details →

Fig. 1. – Study area. A in Geographical patterns of woody plants' functional traits in Burkina Faso

Fig. 1. – Study area. A. Species richness of the 129 woody plants, distribution records and position of Burkina Faso within Africa; B. Names of landscape elements and cities mentioned in the results.

opencc-zeroMay 2022View details →

Geographical variation in the trait-based assembly patterns of multitrophic invertebrate communities

It has been argued that the mechanisms structuring ecological communities may be more generalizable when based on traits than on species identities. If so, patterns in the assembly of community-level traits along environmental gradients should be similar in different places in the world. Alternatively, geographic change in the species pool and regional variation in climate might result in site-specific relationships between community traits and local environments. These competing hypotheses are particularly untested for animal communities. Here we test the geographic constancy of trait-based assembly patterns using a widespread multi-trophic community: aquatic macroinvertebrates within bromeliads. We used data on 615 invertebrate taxa from 1656 bromeliads in 26 field sites from Mexico to Argentina. We summarized invertebrate traits with four orthogonal axes, and used these trait axes to examine trait convergence and divergence assembly patterns along three environmental gradients: detrital biomass and water volume in bromeliads, and canopy cover over bromeliads. We found no overall signal of trait-based assembly patterns along any of the environmental gradients. However, individual sites did show trait convergence along detrital and water gradients, and we built predictive models to explore these site differences. Sites that showed trait convergence along detrital gradients were all north of the Northern Andes. This geographic pattern may be related to phylogeographic differences in bromeliad morphology. Bromeliads with low detritus were dominated by detritivorous collectors and filter feeders, where those with high detritus had more sclerotized and predatory invertebrates. Sites that showed the strongest trait convergence along gradients in bromeliad water were in regions with seasonal precipitation. In such sites, bromeliads with low water were dominated by soft-bodied, benthic invertebrates with simple life cycles. In less seasonal sites, traits associated with short-term desiccation resistance, such as hard exoskeletons, were more important. In summary, we show that there are strong geographic effects on the trait-based assembly patterns of this invertebrate community, driven by the biogeography of their foundational plant species as well as by regional climate. We suggest that inclusion of biogeography and climate in trait-based community ecology could help make it a truly general theory. (excerpted from Srivastava, DS et al. 2022. Geographical variation in the trait-based assembly patterns of multitrophic invertebrate communities. Functional Ecology)

opencc-zeroJun 2022View details →

Broad-scale patterns of geographic avoidance between species emerge in the absence of fine-scale mechanisms of coexistence

Aim: The need to forecast range shifts under future climate change has motivated an increasing interest in better understanding the role of biotic interactions in driving diversity patterns. The contribution of biotic interactions to shaping broad-scale species distributions is however, still debated, partly due to the difficulty of detecting their effects. We aim to test whether spatial exclusion between potentially competing species can be detected at the species range scale, and whether this pattern relates to fine-scale mechanisms of coexistence. Location: Western Palearctic Time period: Anthropocene Taxa: bats (Chiroptera) Methods: We develop and evaluate a measure of geographic avoidance that uses outputs of species distribution models to quantify geographic exclusion patterns expected if interspecific competition affects broad-scale distributions. We apply the measure to 10 Palearctic bat species belonging to four morphologically similar cryptic groups in which competition is likely to occur. We compare outputs to null models based on pairs of virtual species and to expectations based on ecological similarity and fine-scale coexistence mechanisms. We project changes in range suitability under climate change taking into account effects of geographic avoidance. Results: Values of geographic avoidance were above null expectations for two cryptic species pairs, suggesting that interspecific competition could have contributed to shaping their broad-scale distributions. These two pairs showed highest levels of ecological similarity and no trophic or habitat partitioning. Considering the role of competition modified predictions of future range suitability. Conclusions: Our results support the role of interspecific competition in limiting the geographic ranges of morphologically similar species in the absence of fine-scale mechanisms of coexistence. This study highlights the importance of incorporating biotic interactions into predictive models of range shifts under climate change, and the need for further integration of community ecology with species distribution models to understand the role of competition in ecology and biogeography.

opencc-zeroOct 2022View details →

Data from: Biodiversity patterns diverge along geographic temperature gradients

Models applying space-for-time substitution, including those projecting ecological responses to climate change, generally assume an elevational and latitudinal equivalence that is rarely tested. However, a mismatch may lead to different capacities for providing climatic refuge to dispersing species. We compiled community data on zooplankton, ectothermic animals that form the consumer basis of most aquatic food webs, from over 1,200 mountain lakes and ponds across western North America to assess biodiversity along geographic temperature gradients spanning nearly 3,750 metres of elevation and 30 degrees latitude. Species richness, phylogenetic relationships, and functional diversity all showed contrasting responses across gradients, with richness metrics plateauing at low elevations but exhibiting intermediate latitudinal maxima. The nonmonotonic/hump-shaped diversity trends with latitude emerged from geographic interactions, including weaker latitudinal relationships at higher elevations (i.e. in alpine lakes) linked to different underlying drivers. Here, divergent patterns of phylogenetic and functional trait dispersion indicate shifting roles of environmental filters and limiting similarity in the assembly of communities with increasing elevation and latitude. We further tested whether gradients showed common responses to warmer temperatures and found that mean annual (but not seasonal) temperatures predicted elevational richness patterns but failed to capture consistent trends with latitude, meaning that predictions of how climate change will influence diversity also differ between gradients. Contrasting responses to elevation- and latitude-driven warming suggest different limits on climatic refugia and likely greater barriers to northward range expansion.

opencc-zeroJun 2024View details →

Data from: Functional and phylogenetic dimensions of tree biodiversity reveal unique geographic patterns

Aim: Quantify tree functional and phylogenetic richness and divergence at the global scale, and explore the drivers underpinning these biogeographic patterns. Location: Global Time Period: Present Major taxa studied: Trees Methods: Using global tree occurrence data, we outlined species' observed ranges using individual alpha hulls to obtain per-pixel tree species composition. Using eight traits from a recent tree-trait database and a vascular-plant phylogeny we computed and mapped four pixel level biodiversity indices, including two metrics related to richness: phylogenetic richness and functional richness and two related to divergence: mean pairwise phylogenetic distance and Rao's quadratic entropy. To account for the effect of species richness, we also calculated standardized effect sizes accounting for richness for each pixel. We then explored the relations between richness and divergence and the latitudinal patterns of divergence both globally and across biomes. Finally, we used a random forest modeling approach to test for drivers of the different dimensions of diversity in trees. Results: In contrast to the latitudinal gradient in species richness, functional and phylogenetic divergence both peak in mid-latitude systems, exhibiting the highest values in temperate ecosystems and lowest values in boreal and tropical forests. This result holds for functional divergence when removing gymnosperms but the peak flattens for phylogenetic divergence. Phylogenetic richness is consistently lower than expected given the number of species, whereas functional richness has higher-than-expected values at mid-latitudes, mimicking functional divergence patterns. When considering the drivers of these diversity patterns, temperature and historical speciation rates consistently emerge as the strongest forces driving divergence, with negligible effects of human influence, soils or historical climate stability. Main Conclusions: Collectively, these results reveal unique similarities and disparities across biomes that are not apparent in any single dimension of biodiversity, highlighting the importance of considering multiple aspects of biodiversity in the management of natural ecosystems.

opencc-by-4.0Dec 2003View details →

Figure 1 in Geographic and depth distributional patterns of western Atlantic Porcellanidae (Crustacea: Decapoda: Anomura), with an updated list of species

Figure 1. Comparison of the tropical porcellanid faunas from different regions of the western Atlantic. Large, simple circles indicate total number of species in Florida and Brazil regions; small, simple circles indicate species shared by regions; double circle indicates species in Caribbean-West Indian region; rectangle indicates species in southern Caribbean; oval indicates species in the Antilles.

Figures 14–17 in The geographic pattern of distribution of the genus Rhopalurus Thorell, 1876 in the Guayana-Amazon region (Scorpiones: Buthidae)

Figures 14–17: Rhopalurus pintoi kourouensis ssp. n. 14. Carapace. 15. Metasoma and telson, lateral aspect. 16–17. Metasoma and telson, dorsal and ventral aspects.

Figures 10–13 in The geographic pattern of distribution of the genus Rhopalurus Thorell, 1876 in the Guayana-Amazon region (Scorpiones: Buthidae)

Figures 10–13: Rhopalurus pintoi kourouensis ssp. n. 10. Chela, dorso-external aspect, showing trichobothria and very intense setation. 11. Chela, idem, represented without setation. 12–13. Patella and femur, dorsal aspect. Again an important setation can be observed.

Figures 5–9 in The geographic pattern of distribution of the genus Rhopalurus Thorell, 1876 in the Guayana-Amazon region (Scorpiones: Buthidae)

Figures 5–9: Rhopalurus crassicauda paruensis ssp. n., male holotype. 5–7. Chela, dorso-external, ventral and internal aspects, showing trichobothria. 8–9. Tarsi of leg IV, lateral and ventral aspects, showing setation.

Figure 4 in The geographic pattern of distribution of the genus Rhopalurus Thorell, 1876 in the Guayana-Amazon region (Scorpiones: Buthidae)

Figure 4: Present distribution of savannah formations in South America (after Sarmiento, 1984). Arrows indicated distinct savannah fragments inhabited by Rhopalurus species. 1. Llanos of the Magdalena (R. caribensis); 2. Llanos of Orinoco (R. laticauda); 3. Savannahs of the Rio Branco-Rupununi (R. pintoi & R. crassicauda); 4. Campos de Paru (R. crassicauda paruensis ssp. n.); 5. Coastal savannahs of the Guayanas (R. pintoi kourouensis ssp. n.).

Figure 1 in The geographic pattern of distribution of the genus Rhopalurus Thorell, 1876 in the Guayana-Amazon region (Scorpiones: Buthidae)

Figure 1: Presumed dispersal tracks of Rhopalurus spp., between 18,000 and 13,000 years BP. A and B illustrate possible corridors between North-South and East-West savannah formations which coalesced during past dry periods (base map after Ab'Saber, 1977).

Fig. 5 in Geographical color pattern of Argia apicalis (Odonata: Coenagrionidae) in the absence of molecular variation

Fig. 5. Identifying characters of Argia apicalis in the southeast: (A) humeral stripe wide extending at least three-quarters of the pterothorax length; (B) middorsal line slightly wider than in northwestern A. apicalis; and (C) paler caudal appendage (whiter) than in individuals from the north.

Fig. 2 in Geographical color pattern of Argia apicalis (Odonata: Coenagrionidae) in the absence of molecular variation

Fig. 2. (A) Distribution map of specimens examined (this accounts for about 59% of the reported distribution of Argia apicalis). Dark gray states with black dots represent collected specimen localities, and light gray states with no dots represent areas where no specimens were collected. (B) Distribution of color morphs of A. apicalis in Florida; dark gray represents counties with typical A. apicalis, light gray represents counties with atypical A. apicalis, and the striped area represents the county in which both typical and atypical A. apicalis morphs are present.

Fig. 4 in Geographical color pattern of Argia apicalis (Odonata: Coenagrionidae) in the absence of molecular variation

Fig. 4. Variation in width and extension of humeral stripes in the northwest region of the distribution: (A) Dallas County, Texas; (B) Fairfax County, Virginia; (C) Hunterdon County,New Jersey;(D) Iowa; (E) Missouri County,Oregon; (F) Washington Parish,Louisiana; (G) Holmes County, Florida;(H) Wharton County, Texas; and (I) Washington D.C.

Fig. 1. The 4 in Geographical color pattern of Argia apicalis (Odonata: Coenagrionidae) in the absence of molecular variation

Fig. 1. The 4 defining characters of Argia apicalis; (A) a pearlaceous blue pterothorax and a hairline humeral stripe; (B) a thin dorsal stripe; (C) males have a distinctive pointed and tooth-like cercus; (D) and their distribution east of the Rocky Mountains (shaded areas on map are the recorded distribution of A. apicalis).

Fig. 3 in Geographical color pattern of Argia apicalis (Odonata: Coenagrionidae) in the absence of molecular variation

Fig. 3. Geographical color variation: individuals from the (A) northwestern range of the distribution have a typical (= narrow) humeral stripe, whereas individuals from the (B) southeastern part of the range have an atypical (= wide) humeral stripe.

Fig. 6 in Geographical color pattern of Argia apicalis (Odonata: Coenagrionidae) in the absence of molecular variation

Fig. 6. Variation of humeral stripes in the southeast region of the distribution: (A) Clay County, Florida; (B) Columbia County; Florida; (C) Wakulla County, Florida; and (D) Suwannee County, Florida.