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149 results for “species connectivity”
Functional connectivity in a continuously distributed, migratory species as revealed by landscape genomics
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Connecting species’ geographical distributions to environmental variables: range maps versus observed points of occurrence
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Urban versus rural? The effects of residential status on species identification skills and connection to nature
<p>1. Urbanization and urban lifestyles increasingly disconnect people from nature in a process that was termed the 'extinction of experience'. This loss of human-nature interactions can undermine both cognitive (ecological knowledge) and affective (emotional connection to nature) relations to nature, further impacting capabilities to experience, care for, benefit from and act to protect nature. Yet, the extent to which the urban life influences both cognitive and affective relations to nature, remains poorly understood and research is confined to a few countries and cultures.</p> <p>2. We explored how cognitive and affective relations to nature can be related to people's childhood and current place of residency. We expected that urban dwellers, who have less opportunities to experience nature than their rural counterparts, will be less connected to nature and demonstrate lower ecological knowledge than their rural counterparts.</p> <p>3. We conducted four surveys in Israel, in urban and rural settings between 2015 and 2018 (N= 1706) to measure and compare (urban vs. rural) the following variables: (1) species identification skills (correctly identified); (2) familiarity (recognized), as two measures of cognitive relation with nature and (3) nature relatedness, as a measure of emotional connection to nature.</p> <p>4. The ability to identify common plant, bird and butterfly species was poor in general (Av.=3.83 out of 12), and lower for urban dwellers (Av.=2.48) compared to their rural counterparts (Av.=6.56). Differences in correct species identifications between urban and rural dwellers varied with taxa and peaked for butterflies (only 26 respondents managed to identify one species or more). We also identified an important gap between familiarity and species identification skills, especially for urban residents. Finally, people who currently live or used to live in rural areas during their childhood had higher scores of nature relatedness than their urban counterparts.</p> <p>5. Our results highlight that decreased opportunity to interact with nature reduces cognitive and affective relations to nature. Such reductions can affect the overall preferences for human-nature relationships and exacerbate a pervasive negative cycle that modifies relational values such as, care for nature, sense of belonging, place and identity that influence both humans well-being and environmental stewardship. </p>
By animal, water, or wind: can dispersal mode predict genetic connectivity in riverine plant species?
<div class="page"> <div class="section"> <div class="layoutArea"> <div class="column"> <p>Seed dispersal is crucial to gene flow among plant populations. Although the effects of geographic distance and barriers to gene flow are well studied in many systems, it is unclear how seed dispersal mediates gene flow in conjunction with interacting effects of geographic distance and barriers. To test whether distinct seed dispersal modes (i.e. hydrochory, anemochory, and zoochory) have a consistent effect on the level of genetic connectivity (i.e., gene flow) among populations of riverine plant species, we used unlinked single-nucleotide polymorphisms (SNPs) for eight co-distributed plant species sampled across the Rio Branco, a putative biogeographic barrier in the Amazon Basin. We found that animal-dispersed plant species exhibited higher levels of genetic diversity and lack of inbreeding as a result of the stronger genetic connectivity than plant species whose seeds are dispersed by water or wind. Interestingly, our results also indicated that the Rio Branco facilitates gene dispersal for all plant species analyzed, irrespective of their mode of dispersal. Our findings indicate that seed dispersal mode and riverscape features can greatly impact genetic structure, representing reliable predictors of genetic connectivity in riverine plant species. These results may help improve conservation and management policies in Amazonian riparian forests, where degradation and deforestation rates are high.</p> </div> </div> </div> </div>
Data from: Signatures of polygenic adaptation associated with climate across the range of a threatened fish species with high genetic connectivity
Adaptive differences across species' ranges can have important implications for population persistence and conservation management decisions. Despite advances in genomic technologies, detecting adaptive variation in natural populations remains challenging. Key challenges in gene-environment association studies involve distinguishing the effects of drift from those of selection, and identifying subtle signatures of polygenic adaptation. We used paired-end restriction-site associated-DNA sequencing data (6605 biallelic single nucleotide polymorphisms; SNPs) to examine population structure and test for signatures of adaptation across the geographic range of an iconic Australian endemic freshwater fish species, the Murray cod Maccullochella peelii. Two univariate gene-association methods identified 61 genomic regions associated with climate variation. We also tested for subtle signatures of polygenic adaptation using a multivariate method (redundancy analysis; RDA). The RDA analysis suggested that climate (temperature- and precipitation-related variables) and geography had similar magnitudes of effect in shaping the distribution of SNP genotypes across the sampled range of Murray cod. Although there was poor agreement among the candidate SNPs identified by the univariate methods, the top 5% of SNPs contributing to significant RDA axes included 67% of the SNPs identified by univariate methods. We discuss the potential implications of our findings for the management of Murray cod and other species generally, particularly in relation to informing conservation actions such as translocations to improve evolutionary resilience of natural populations. Our results highlight the value of using a combination of different approaches, including polygenic methods, when testing for signatures of adaptation in landscape genomics studies.
Defining and quantifying effective connectivity of landscapes for species' movements
<p>Demonstration of the workflow and supplementary information on the randomized shortest paths framework for "Defining and quantifying effective connectivity of landscapes for species' movements" by Van Moorter B, Kivimäki I, Panzacchi M, Saerens M. (2021) in Ecography 44(6):1–15. </p> <p>Ecosystem functioning depends on multiple successful interactions, many supported by individual movements. The degree to which the landscape allows these interactions to take place has been referred to as 'effective connectivity' (EC). Many of the cumulative impacts of anthropogenic activities on ecosystem functioning arise from changes in EC. Therefore, a coherent framework to quantify EC is urgently needed. Recent theoretical developments propose that studying EC requires the simultaneous consideration of spatial, environmental and species intrinsic characteristics (SEI framework).</p> <p>In the paper we further expand the SEI framework by integrating advances in geographic information science, ecological niche modelling, movement ecology, island biogeography and network sciences to develop a comprehensive three-step methodological approach for quantifying EC. First, using niche modelling and movement ecology, we quantify the species movement probabilities with respect to local environmental conditions. Second, we quantify ecological distances between non-adjacent locations by integrating species movement responses to the local environment with the spatial configuration of the landscape using the expected cost obtained from the randomized shortest paths (RSP) framework. This expected cost generalizes the two most frequently used ecological distance metrics, i.e. least-cost distance and resistance distance. Moreover the 'absorbing random walk' properties of RSP allow the integration of new developments in connectivity research, i.e. spatial absorbing Markov chains, to account for movement-related mortality. Third, drawing from island biogeography and metapopulation ecology, we scale ecological distances by relevant species- and area-specific parameters to estimate EC for the ecological process of interest, e.g. migration, dispersal or gene flow.</p> <p>The integrative and highly interdisciplinary approach we propose can lead to increasingly more realistic measures of EC at different organizational levels. Moreover efficient computation allows its application to large-scale high-resolution landscapes for theoretical studies, conservation planning and sustainable management of real landscapes.</p>
Supplementary material 2 from: Wei Z-Y, Gu Y-F, Xia Z-Q, Chen L-J, Wang T, Zhang S-Z, Zhao G-H, Chen J-B, Cao J-G, Yan Y-H (2021) Dipteris shenzhenensis, a new species of Dipteridaceae connected with broad wings from Shenzhen, southern China. PhytoKeys 186: 111-120. https://doi.org/10.3897/phytokeys.186.73739
Table S2. Specimen information used for morphological comparison
Figure 3 from: Wei Z-Y, Gu Y-F, Xia Z-Q, Chen L-J, Wang T, Zhang S-Z, Zhao G-H, Chen J-B, Cao J-G, Yan Y-H (2021) Dipteris shenzhenensis, a new species of Dipteridaceae connected with broad wings from Shenzhen, southern China. PhytoKeys 186: 111-120. https://doi.org/10.3897/phytokeys.186.73739
Figure 3 Dipteris shenzhenensis Y.H.Yan & Z.Y.Wei A habit B details of a lamina showing the venation and the distribution of sori C rhizome scale showing the profile and length (drawn by Zuo-Ying Wei & Li-Jun Chen, based on the type material at SZG).
Figure 2 from: Wei Z-Y, Gu Y-F, Xia Z-Q, Chen L-J, Wang T, Zhang S-Z, Zhao G-H, Chen J-B, Cao J-G, Yan Y-H (2021) Dipteris shenzhenensis, a new species of Dipteridaceae connected with broad wings from Shenzhen, southern China. PhytoKeys 186: 111-120. https://doi.org/10.3897/phytokeys.186.73739
Figure 2 Morphological features of Dipteris shenzhenensis Y.H.Yan & Z.Y.Wei (A–E) and D. chinensis (F–J). A fan-shaped frond of D. shenzhenensisB the frond base with broad wing of D. shenzhenensisC rhizome of D. shenzhenensisD spore of D. shenzhenensisE rhizome scale of D. shenzhenensisF fan-shaped frond of D. chinensisG the frond base without wing of D. chinensisH rhizome of D. chinensisI spore of D. chinensisJ rhizome scale of D. chinensis.
Figure 4 from: Wei Z-Y, Gu Y-F, Xia Z-Q, Chen L-J, Wang T, Zhang S-Z, Zhao G-H, Chen J-B, Cao J-G, Yan Y-H (2021) Dipteris shenzhenensis, a new species of Dipteridaceae connected with broad wings from Shenzhen, southern China. PhytoKeys 186: 111-120. https://doi.org/10.3897/phytokeys.186.73739
Figure 4 The phylogenetic tree inferred by the Bayesian inference with posterior probabilities above the branches.
Supplementary material 1 from: Wei Z-Y, Gu Y-F, Xia Z-Q, Chen L-J, Wang T, Zhang S-Z, Zhao G-H, Chen J-B, Cao J-G, Yan Y-H (2021) Dipteris shenzhenensis, a new species of Dipteridaceae connected with broad wings from Shenzhen, southern China. PhytoKeys 186: 111-120. https://doi.org/10.3897/phytokeys.186.73739
Table S1. List of species and GenBank accession numbers used in the present study
Figure 1 from: Wei Z-Y, Gu Y-F, Xia Z-Q, Chen L-J, Wang T, Zhang S-Z, Zhao G-H, Chen J-B, Cao J-G, Yan Y-H (2021) Dipteris shenzhenensis, a new species of Dipteridaceae connected with broad wings from Shenzhen, southern China. PhytoKeys 186: 111-120. https://doi.org/10.3897/phytokeys.186.73739
Figure 1 Boxplot (median and interquartile values) for the length of lobes (left), the width of lobes (center), and the number of lobes of each half of the fan-shaped fronds (right) amongst Dipteris conjugata, D. shenzhenensis and D. chinensis. Significant differences between species are represented with * (P < 0.05), ** (P < 0.001), and *** (P < 0.0001).
FIGURE 2 in Taxonomic description of a new species of Leucoagaricus and utilization of the Pantone Connect app in classification research
FIGURE 2. Basidiomata of Leucoagaricus brunneorube (HKAS128146, holotype!). Bars=1 cm.
FIGURE 4 in Three decades to connect the sexes: Calatola microcarpa (Icacinaceae), a new species from the Southwestern Amazon
FIGURE 4. Distribution map of Calatola microcarpa Duno & J. Janovec (●).
FIGURE 1 in Three decades to connect the sexes: Calatola microcarpa (Icacinaceae), a new species from the Southwestern Amazon
FIGURE 1. Type specimen of Calatola microcarpa Duno & J. Janovec (R. Vásquez 12300, CICY).
By animal, water, or wind: can dispersal mode predict genetic connectivity in riverine plant species?
Open the record for dataset details and reuse information.
Data from: Signatures of polygenic adaptation associated with climate across the range of a threatened fish species with high genetic connectivity
Open the record for dataset details and reuse information.
Urban versus rural? The effects of residential status on species identification skills and connection to nature
Open the record for dataset details and reuse information.
Defining and quantifying effective connectivity of landscapes for species' movements
Open the record for dataset details and reuse information.
FIGURE 7 in A new species of Stenampyx Karsch, 1890 from East Africa (Orthoptera: Tettigoniidae, Pseudophyllinae, Phyllomimini)- evidence of a former connection of West-Central and East African forests
FIGURE 7. Morphological details of male Stenampyx viridiflavum n. sp. A. Apex, dorsal view B. Subgenital plate C. Stridulatory file.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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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.