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FIGURES 11 a–c. Sinopoda empat spec. nov., holotype male from Gua Gereja Hujan. a–c 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)
FIGURES 11 a–c. Sinopoda empat spec. nov., holotype male from Gua Gereja Hujan. a–c left male palp (a prolateral, b ventral, c retrolateral).
FIGURES 17 a–e 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)
FIGURES 17 a–e. Sinopoda inthanon spec. nov., holotype male and paratype female from Doi Inthanon. a–c left male palp (a prolateral, b ventral, c retrolateral); d Epigyne, ventral; e Vulva, dorsal.
FIGURES 5–12 in Megymenum tuberculatum, a new species of Megymenini from Java and a review of distribution of M. brevicorne (Hemiptera: Heteroptera: Dinidoridae)
FIGURES 5–12. Visual comparison of pronotum shape and size of dorsal anterior tubercle in eight species of the genus Megy- menum Guérin-Méneville, 1831. 5—Megymenum tuberculatum Hemala & Kocorek, sp. nov.; 6—M. brevicorne (Fabricius, 1787); 7—M. basale Walker, 1868; 8—M. parallelum Vollenhoven, 1868; 9—M. spinosum (Burmeister, 1834); 10—M. mekon- gum Distant, 1921; 11—M. pratti Distant, 1911; 12—M. gracilicorne Dallas, 1851. (Photo: V. Hemala).
Data from Jenkinson et al. 2020: Biogeographical variation in the distribution, abundance, and interactions among key species on rocky reefs of the northeast Pacific
<p>See Metadata tab for full description of transect survey data.</p>
Data from: Colonial history impacts urban tree species distribution in a tropical city
Urban forests associated with green infrastructure for sustainable outcomes are particularly critical in the Global South, where some of the world's fastest-growing cities are located. However, compared to temperate cities, the drivers of urban tree species distribution in tropical cities remain understudied. In this study, we quantify the spatial distribution and abundance of urban forests in the tropical city of Georgetown, Guyana. British colonialism has shaped this city, including forced movement of peoples under slavery from Africa and indentured servants from the Indian Subcontinent. We studied how this multicultural context has influenced tree species distributions in the capital city of the only Anglophone country in South America. We quantified the abundance of tree species using a stratified sampling design to distribute transects across fifteen neighborhoods that vary in distance to the colonial center of the city and ethnic composition. We recorded a total of 57 unique species, the majority of which (73%) were cultivated for their edible fruits. We identify tree species that likely represent Guyana's unique multicultural heritage by comparing our species list to flora in nine cities in neighboring countries (Venezuela and Brazil) with different colonial histories. This international comparison identified a set of tree species that occurred only in Guyana. Relationships between ethnic composition and colonial history and tree species distribution were weak at the neighborhood scale, where proportion of East Indian residents had little explanatory power and distance to colonial center was correlated with abundance of only some species groups. This apparent discrepancy between neighborhood and national scales may relate to the establishment of Guyanese food as a unifying national identifier across ethnicities. The prominence of edible fruit trees in our study suggests a set of species that could be incorporated into urban planning to strengthen biocultural linkages, foster cultural integration, and promote food security.
Supplementary material 1 from: Datta A, Schweiger O, Kühn I (2020) Origin of climatic data can determine the transferability of species distribution models. NeoBiota 59: 61-76. https://doi.org/10.3897/neobiota.59.36299
Variable selection using cluster analsys based on Spearman's rank corellation and UPGMA method for agglomeration
Data from: Joint effect of phylogenetic relatedness and trait selection on the elevational distribution of Rhododendron species
<p>Congeneric species may coexist at fine spatial scales through niche differentiation, however, the magnitude to which the effects of functional traits and phylogenetic relatedness contribute to their distribution along elevational gradients remains understudied. To test the hypothesis that trait and elevational range overlap can affect local speciesʼ coexistence, we first compared phylogenetic relatedness and trait (including morphological traits and leaf elements) divergence among closely related species of <em>Rhododendron</em> L. on Yulong Mountain, China. We then assessed relationships between the overlap of multiple functional traits and the degree of elevational range overlap among species pairs in a phylogenetic context. We found that phylogeny was a good predictor for most functional traits, where closely related species showed higher trait similarity and occupied different elevational niches at our study site. Species pairs of <em>R</em>. subgen. <em>Hymenanthes</em> (Blume) K. Koch showed low elevational range overlap and some species pairs of <em>R</em>. subgen. <em>Rhododendron</em> showed obvious niche differentiation. Trait divergence is greater for species in <em>R.</em> subgen. <em>Rhododendron</em>, and it plays an important role between species pairs with low elevational range overlap. Trait convergent selection takes place between co-occurring closely related species that have high elevational range overlap, which share more functional trait space due to environmental filtering or ecological adaptation in more extreme habitats. Our results highlight the importance of evolutionary history and trait selection for species coexistence at fine ecological scales along environmental gradients.</p>
Data from: Evaluating presence-only species distribution models with discrimination accuracy is uninformative for many applications
Aim: Species distribution models are used across evolution, ecology, conservation, and epidemiology to make critical decisions and study biological phenomena, often in cases where experimental approaches are intractable. Choices regarding optimal models, methods, and data are typically made based on discrimination accuracy: a model's ability to predict subsets of species occurrence data that were withheld during model construction. However, empirical applications of these models often involve making biological inferences based on continuous estimates of relative habitat suitability as a function of environmental predictor variables. We term the reliability of these biological inferences "functional accuracy." We explore the link between discrimination accuracy and functional accuracy. Methods: Using a simulation approach we investigate whether models that make good predictions of species distributions correctly infer the underlying relationship between environmental predictors and the suitability of habitat. Results: We demonstrate that discrimination accuracy is only informative when models are simple and similar in structure to the true niche, or when data partitioning is geographically structured. However, the utility of discrimination accuracy for selecting models with high functional accuracy was low in all cases. Main conclusions: These results suggest that many empirical studies and decisions are based on criteria that are unrelated to models' usefulness for their intended purpose. We argue that empirical modeling studies need to place significantly more emphasis on biological insight into the plausibility of models, and that the current approach of maximizing discrimination accuracy at the expense of other considerations is detrimental to both the empirical and methodological literature in this active field. Finally, we argue that future development of the field must include an increased emphasis on simulation; methodological studies based on ability to predict withheld occurrence data may be largely uninformative about best practices for applications where interpretation of models relies on estimating ecological processes, and will unduly penalize more biologically informative modeling approaches.
Fig. 17-18 in Notes on taxonomy and distribution of Cryptophagus jakowlewi R , 1888 (Coleoptera: Cryptophagidae) with remarks on further species
Fig. 17-18: (17) Cryptophagus freyi BRUCE, 1941, holotype, (18) Cryptophagus archangelicus J.R. SAHLBERG. 1929, Siberia. Fig. 19-20: Habitus of (19) Cryptophagus quadridentatus MANNER- HEİM, 1843, (20) Cryptophagus dentaus (HERBST, 1793).
Supplementary material 1 from: Huang J, Guo Z, Tang S, Ren W, Chu G, Wang L, Zhao L, Yu R, Xu Y, Ding Y, Zang R (2020) Floristic composition and plant diversity in distribution areas of native species congeneric with Betula halophila in Xinjiang, northwest China. Nature Conservation 42: 1-17. https://doi.org/10.3897/natureconservation.42.54735
Figure S1. The correlation between environmental variables in distribution areas of five congeneric species with Betula halophila
Regionally divergent drivers of historical diversification in the late Quaternary in a widely distributed generalist species, the common pheasant Phasianus colchicus
<p>Aim: Pleistocene climate and associated environmental changes have influenced phylogeographic patterns of many species. These not only depend on a species' life history but also vary regionally. Consequently, populations of widespread species that occur in several biomes might display different evolutionary trajectories. We aimed to identify regional drivers of diversification in the common pheasant, a widely distributed ecological generalist. <br> <br> Study location Asia<br> <br> Taxon common pheasant Phasianus colchicus<br> <br> Methods Using a comprehensive geographic sampling of 204 individuals from the species' entire range genotyped at seven nuclear and two mitochondrial loci, we reconstructed spatio-temporal diversification and demographic history of the common pheasant. We applied Bayesian phylogenetic inference to describe phylogeographic structure, generated a species tree, and inferred demographic history within and migration between lineages. Moreover, to establish a taxonomic framework, we conducted a species delimitation analysis.<br> Results The common pheasant diversified during the late Pleistocene into eight distinct lineages. It originated at the edge of the Qinghai-Tibetan plateau and spread to East and Central Asia. Only the widely distributed lowland lineage of East Asia displayed recent range expansion. Greater phylogeographic structure was identified elsewhere, with lineages showing no sign of recent demographic changes. One lineage in south-central China is the result of long-term isolation within a climatically stable but topographically complex region. In lineages from arid Central Asia and China, range expansions were impeded by repeated population fragmentation during dry glacial periods and by recent aridification. <br> <br> Main conclusions <br> Spatio-temporal phylogeographic frameworks of widespread taxa such as the common pheasant provide valuable opportunities to identify divergent drivers of regional diversification. Our results suggest that diversification and population histories in the eight distinct evolutionary lineages were shaped by regionally variable effects of past climate and associated environmental changes. The evolutionary history of the common pheasant is best reflected by its being split into three species.</p>
Integrating univariate niche dynamics in species distribution models: a step forward for marine research on biological invasions
<p>Aim The development of approaches to predict the distribution and potential expansion of invasive species is still an open challenge. Here our goal is to improve the modelling procedure for marine invaders by coupling Species Distribution Models (SDMs) with an analysis of their univariate niche dynamics. In particular, we tested for the first time whether choosing model predictors among the stable niche dimensions was effective in improving predictions of invasive species expansion.<br> Location Mediterranean Sea<br> Taxon Dusky spinefoot, Siganus luridus.<br> Methods We analysed the univariate niche dynamics for S. luridus across its native and invaded ranges, by applying a standardized framework that allowed the identification of cases of niche stability or shift. We compared inter-range transferability of SDMs fitted with different combinations of labile or stable predictors. Finally, we evaluated interactions in SDM settings (calibration area, model technique and predictors set) on models' predictive ability, using independent data from the most recent phase of invasion.<br> Results We detected a pattern of niche stability for several variables, especially salinity and bathymetry, which positively influenced model inter-ranges transferability: when the models calibrated in the native range include only stable niche axes, predictive ability is improved. We also identified a shift toward lower surface temperatures in the introduced range, which were almost never experienced by the species before invasion. The model calibrated within the combined ranges was the most ecologically congruent. Also, models calibrated in the invaded range allowed a correct prediction of range expansion, with the predicted suitable areas only slightly underestimated.<br> Main conclusions We provide the first evidence that using conserved predictors in SDMs improves inter-range projections of expanding invasive species. Variable selection, calibration area and modelling technique all matter when modelling invasive species, with important interaction effects. We provide guidelines on how to improve SDMs applications in biological invasion research.</p>
Avian point-counts from Rhode Island and Connecticut used to test species distribution models
<p>Spatial-biases are a common feature of presence-absence data from citizen scientists. Spatial thinning can mitigate errors in species distribution models (SDMs) that use these data. When detections or non-detections are rare, however, SDMs may suffer from class imbalance or low sample size of the minority (i.e. rarer) class. Poor predictions can result, the severity of which may vary by modeling technique. To explore the consequences of spatial bias and class imbalance in presence-absence data, we used eBird citizen science data for 102 bird species from the northeastern USA to compare spatial thinning, class balancing, and majority-only thinning (i.e., retaining all samples of the minority class). We created SDMs using two parametric or semi-parametric techniques (generalized linear models and generalized additive models) and two machine-learning techniques (random forest and boosted regression trees). We tested the predictive abilities of these SDMs using an independent and systematically collected reference dataset with a combination of discrimination (area under the receiver operator characteristic curve; true skill statistic; area under the precision-recall curve) and calibration (Brier score; Cohen's kappa) metrics. We found large variation in SDM performance depending on thinning and balancing decisions. Across all species, there was no single best approach, with the optimal choice of thinning and/or balancing depending on modeling technique, performance metric, and the baseline sample prevalence of species in the data. Spatially thinning all the data was often a poor approach, especially for species with baseline sample prevalence < 0.1. For most of these rare species, balancing classes improved model discrimination between presence and absence classes, but hindered model calibration. Baseline sample prevalence, sample size, modeling approach, and the intended application of SDM output – whether discrimination or calibration – should guide decisions about how to thin or balance data, given the considerable influence of these methodological choices on SDM performance. For prognostic applications requiring good model calibration (vis-à-vis discrimination), the match between sample prevalence and true species prevalence may be the overriding feature and warrants further investigation.</p>
Adaptive trait syndromes along multiple economic spectra define cold and warm adapted ecotypes in a widely distributed foundation tree species
<p>1. The coordination of traits from individual organs to whole plants is under strong selection because of environmental constraints on resource acquisition and use. However, the tight coordination of traits may provide underlying mechanisms of how locally adapted plant populations can become maladapted because of climate change. 2. To better understand local adaptation in intraspecific trait coordination, we studied trait variability in the widely distributed foundation tree species, Populus fremontii using a common garden near the mid-elevational point of this species distribution. We examined 28 traits encompassing four spectra: phenology, leaf economic spectrum (LES), whole-tree architecture (Corner's Rule), and wood economic spectrum (WES). 3. Based on adaptive syndrome theory, we hypothesized that trait expression would be coordinated among and within trait spectra, reflecting local adaptation to either exposure to freeze-thaw conditions in genotypes sourced from high-elevation populations or exposure to extreme thermal stress in genotypes sourced from low-elevation populations. 4. High-elevation genotypes expressed traits within the phenology and WES that limit frost exposure and tissue damage. Specifically, genotypes sourced from high elevations had later mean budburst, earlier mean budset, higher wood densities, higher bark fractions, and smaller xylem vessels than their low-elevation counterparts. Conversely, genotypes sourced from low elevations expressed traits within the LES that prioritized hydraulic efficiency and canopy thermal regulation to cope with extreme heat exposure, including 40% smaller leaf areas, 67% higher stomatal densities, and 34% higher mean theoretical maximum stomatal conductance. Low-elevation genotypes also expressed a lower stomatal control over leaf water potentials that subsequently dropped to pressures that could induce hydraulic failure. 5. Synthesis. Our results suggest that P. fremontii expresses a high degree of coordination across multiple trait spectra to adapt to local climate constraints on photosynthetic gas exchange, growth, and survival. These results, therefore, increase our mechanistic understanding of local adaptation and the potential effects of climate change that in turn, improves our capacity to identify genotypes that are best suited for future restoration efforts.</p>
Data from: Modelling species distributions limited by geographic barriers: a case study with African and American primates
<p><strong>Aim:</strong> The boundaries of species distributions are often shaped by natural barriers such as mountains and rivers, but species distribution models usually fail to include these constraints. We tested several approaches that include barriers as explanatory variables in species distribution models.</p> <p><strong>Location:</strong> Africa and South America.</p> <p><strong>Time period:</strong> Current</p> <p><strong>Major taxa studied:</strong> Primates</p> <p><strong>Methods:</strong> We modelled the ranges of pairs of species separated by a river taking into account three explanatory components: the environment (ecosystems, topo-hydrography, climate, human pressure), the spatial structure shaped by history and population dynamics (using a trend-surface approach), and rivers as naturals barriers to dispersal (using a binary cis-trans variable that describes both sides of the river). To assess how the addition of a spatial structure and the barrier could improve distribution models, we used a nested approach by comparing models based on: a) the environment; b) the environment and the spatial structure; and c) the environment, the spatial structure and the river. These models were constructed using the favourability functions.</p> <p><strong>Results:</strong> There was a decreased occurrence of high-favourability values in the opposite side of the rivers in models that included the spatial structure of distributions, compared to models based on environment alone. This decrease was more marked when the description of the spatial structure was made more flexible. However, model performance was significantly improved by the inclusion of cis-trans variables that identified areas on the opposite side as totally unfavourable.</p> <p><strong>Main conclusions:</strong> The performance of distribution models can improve by the use of approaches that describe barriers. Although adding the location of geographic units in relation to a river appears to be the most accurate way to define the presence of a barrier, defining this variable may be challenging. A suitable alternative is to analyse the spatial structure of distributions using a flexible approach.</p>
Drought sensitivity of Empetrum nigrum shrub growth at the species' southern lowland distribution range margin
<p>The ongoing warming of the Earth's atmosphere is projected to cause a northward shift of species' distributions, as they track their climatic optimum. In the rapidly warming Arctic, this has already led to an increase of shrubs in tundra ecosystems. While this northern expansion of woody biomass has been studied relatively extensively over the last decade, little research has been devoted to shrub growth responses at the southern margins of Northern Hemisphere shrubs.</p> <p>Here, we studied shoot length growth, its responses to climate over the period 2010-2017, and differences in leaf C and N content of the evergreen dwarf shrub <i>Empetrum nigrum</i>, as well as the vegetation composition and soil parameters at four sites located along a gradient of increasing dune age on the island Spiekeroog, northern Germany. The sites are located in the tri-national UNESCO world heritage site, the Wadden Sea. <i>E. nigrum</i> has a predominantly circum-arctic-boreal distribution and its southern distribution mbargin in European lowlands runs through northern Germany, where it is retreating northwards.</p> <p>We found a negative response to autumn (surface) temperatures and previous summer surface temperatures and/or a positive response to summer precipitation of <i>E. nigrum</i> growth, except at the oldest dune with the strongest <i>E. nigrum</i> dominance. Growth rates and plant species diversity declined with dune age. Our results suggest that <i>E. nigrum</i> growth is drought sensitive at its European southern range margin. We hypothesize that this sensitivity may form the basis for its northward retreat, which is supported by recent observations of <i>E. nigrum</i> dieback in Germany after the extreme drought in 2018 and model projections.</p>
Combining Satellite Remote Sensing and Climate Data in Species Distribution Models to Improve the Conservation of Iberian White Oaks (Quercus L.)
<p>The Iberian Peninsula hosts a high diversity of oak species, being a hot-spot for the conservation of European White Oaks (Quercus) due to their environmental heterogeneity and its critical role as a phylogeographic refugium. Identifying and ranking the drivers that shape the distribution of White Oaks in Iberia requires that environmental variables operating at distinct scales are considered. These include climate, but also ecosystem functioning attributes (EFAs) related to energy–matter exchanges that characterize land cover types under various environmental settings, at finer scales. Here, we used satellite-based EFAs and climate variables in species distribution models (SDMs) to assess how variables related to ecosystem functioning improve our understanding of current distributions and the identification of suitable areas for White Oak species in Iberia. We developed consensus ensemble SDMs targeting a set of thirteen oaks, including both narrow endemic and widespread taxa. Models combining EFAs and climate variables obtained a higher performance and predictive ability (true-skill statistic (TSS): 0.88, sensitivity: 99.6, specificity: 96.3), in comparison to the climate-only models (TSS: 0.86, sens.: 96.1, spec.: 90.3) and EFA-only models (TSS: 0.73, sens.: 91.2, spec.: 82.1). Overall, narrow endemic species obtained higher predictive performance using combined models (TSS: 0.96, sens.: 99.6, spec.: 96.3) in comparison to widespread oaks (TSS: 0.80, sens.: 92.6, spec.: 87.7). The Iberian White Oaks show a high dependence on precipitation and the inter-quartile range of Normalized Difference Water Index (NDWI) (i.e., seasonal water availability) which appears to be the most important EFA variable. Spatial projections of climate–EFA combined models contribute to identify the major diversity hotspots for White Oaks in Iberia, holding higher values of cumulative habitat suitability and species richness. We discuss the implications of these findings for guiding the long-term conservation of IberianWhite Oaks and provide spatially explicit geospatial information about each oak species (or set of species) relevant for developing biogeographic conservation frameworks.</p>
FIGURE 3. Leptagrion dispar. a in Description of the larva of Leptagrion dispar Selys, 1876 (Odonata: Coenagrionidae) with notes on distribution and ecology of the specie
FIGURE 3. Leptagrion dispar. a—Last larval instar, dorsal view; b—Head and thorax—dorsal view; c—Prementum—dorsal view; d—Labial palp, dorsal view; e—Right mandible, inner view; f—Left mandible, inner view; g—Gonapophysis and cercus of the male, ventral view; h—lamellas—dorsal view; i—Median caudal lamella—dorsal view; j—Lateral caudal lamella, lateral view. Scales: Fig. a = 5 mm, Figs. b–d = 1 mm, Figs. e–f = 0,5 mm, Figs. g–j = 1 mm.
Supplementary material 1 from: Bustamante RO, Alves L, Goncalves E, Duarte M, Herrera I (2020) A classification system for predicting invasiveness using climatic niche traits and global distribution models: application to alien plant species in Chile. NeoBiota 63: 127-146. https://doi.org/10.3897/neobiota.63.50049
Table S1. Exotic species located in Quadrant 1 (see Figure 3) and impacts on biodiversity, agriculture and cattle raisng
FIGURE 9 in DNA barcodes, morphology and geographic distribution confirm a new butterfly species in the genus Rhamma (Lepidoptera: Lycaenidae)
FIGURE 9. Neighbor Joining identification tree. Rhamma eleonorae sp. nov sequences are denoted as: Rhamma sp 1 BMC16124 and 22302. Note the placement of Rhamma arria from Llanos de Cuiva. The distances were computed using the Kimura 2-parameter method (Kimura 1980) and are in the units of the number of base substitutions per site. The analysis involved 42 nucleotide sequences. All positions containing gaps and missing data were eliminated. There were a total of 577 positions in the final dataset. Analyses were conducted in MEGA7 (Kumar et al. 2016).
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.