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7,849 results for “Conservancy”
Mapping multiscale breeding bird species distributions across the United States and evaluating their conservation applications
<p>Species distribution models are vital to management decisions that require understanding habitat use patterns, particularly for species of conservation concern. However, the production of distribution maps for individual species is often hampered by data scarcity, and existing species maps are rarely spatially validated due to limited occurrence data. Furthermore, community-level maps based on stacked species distribution models lack important community assemblage information (e.g., competitive exclusion) relevant to conservation. Thus, multispecies, guild, or community models are often used in conservation practice instead. To address these limitations, we aimed to generate fine-scale, spatially-continuous, nationwide maps for species represented in the North American Breeding Bird Survey (BBS) between 1992-2019. We generated ensemble models for each species at three spatial resolutions – 0.5, 2.5, and 5 km – across the conterminous United States. We also compared species richness patterns from stacked single-species models with those of 19 functional guilds developed using the same data to assess the similarity between predictions. We successfully modeled 192 bird species at 5-km resolution, 160 species at 2.5-km resolution, and 80 species at 0.5-km resolution. However, the species we could model represent only 28-56% of species found in the conterminous US BBS surveys across resolutions owing to data limitations. We found stacked maps and guild maps generally had high correlations across resolutions (median = 84%), but spatial agreement varied regionally by resolution and was most pronounced between the East and West at the 5-km resolution. The spatial differences between our stacked maps and guild maps illustrate the importance of spatial validation in conservation planning. Overall, our species maps are useful for single-species conservation and can support fine-scale decision-making across the United States, and can also support community-level conservation when used in tandem with guild maps. However, there are still data scarcity issues for many species of conservation concern when using the BBS for single-species models.</p>
Robust evidence for bats as reservoir hosts is lacking in most African virus studies – a review and call to optimize sampling and conserve bats
<p><span>Africa experiences frequent emerging disease outbreaks among humans, with bats often proposed as zoonotic pathogen hosts. We comprehensively reviewed virus-bat findings from papers published between 1978 and 2020 to evaluate the evidence that African bats are reservoirs and/or bridging hosts for viruses that cause human disease. We present data from 162 papers (of 1322) with original findings on (1) numbers and species of bats sampled across bat families and the continent, (2) how bats were selected for study inclusion, (3) if bats were terminally sampled, (4) what types of ecological data, if any, were recorded, and (5) which viruses were detected and with what methodology. We propose a scheme for evaluating presumed virus-host relationships by evidence type and quality, using the contrasting available evidence for </span><em>Orthoebolavirus</em> (formerly <em>Ebolavirus</em>) versus <em>Orthomarburgvirus</em> (formerly <em>Marburgvirus</em>) as an example. We review the wording in abstracts and discussions of all 162 papers, identifying key framing terms, how these refer to findings, and how they might contribute to people's beliefs about bats. We discuss the impact of scientific research communication on public perception and emphasize the need for strategies that minimize human-bat conflict and support bat conservation. Finally, we make recommendations for best practices that will improve virological study metadata.</p>
Fig. 2 in Bird Diversity Differs Between Industrial Tree Plantations On Borneo: Implications For Conservation Planning
Fig. 2. Species accumulation curves for (A) Sabah Softwoods and (B) Sarawak Planted Forest Project.
Fig. 2 in Natural-Licks Use By Orangutans And Conservation Of Their Habitats In Bornean Tropical Production Forest
Fig. 2. Two pairs of females with infants drink the seepage water at a natural-lick.
Fig. 6 in Natural-Licks Use By Orangutans And Conservation Of Their Habitats In Bornean Tropical Production Forest
Fig. 6. Visitation time of each orangutan class to the naturallicks.
Fig. 4 in Natural-Licks Use By Orangutans And Conservation Of Their Habitats In Bornean Tropical Production Forest
Fig. 4. Visiting proportion of each orangutan class: flanged male, female with infant, and others.
Fig. 3 in Natural-Licks Use By Orangutans And Conservation Of Their Habitats In Bornean Tropical Production Forest
Fig. 3. Proportion of visitation frequency of top 3 species among the natural-licks.
Fig. 5 in Natural-Licks Use By Orangutans And Conservation Of Their Habitats In Bornean Tropical Production Forest
Fig. 5. Duration of the visit of each orangutan class to the naturallicks.
Figure 4 in Conservation gaps identification through patterns of species richness established from species niche models of mammals in a sector of Chaco Seco ecoregion
Figure 4. Response graphs of habitat suitability (ordinate axis) according to the explanatory variables that intervened in the adjustment of the model for brown brocket deer (A, B, C). The temperature is expressed in degrees Celsius.Source of bioclimatic variables (bio), site https://www.worldclim.org/data/bioclim.html.
Figure 1 in Bird checklist and contributions to conservation of the Atlantic forest-cerrado ecotone in Três Lagoas municipality, Brazil
Figure 1. Três Lagoas Municipality map, Atlantic forest-cerrado ecotone and survey and localities (1-31).
Figure 8 in Conservation gaps identification through patterns of species richness established from species niche models of mammals in a sector of Chaco Seco ecoregion
Figure 8. Species richness maps obtained using three algorithms, (A) "fuzzy union″, (B) "species richness″ and (C) "total beta″.
Figure 7 in Conservation gaps identification through patterns of species richness established from species niche models of mammals in a sector of Chaco Seco ecoregion
Figure 7. Response graphs of habitat suitability (ordinate axis) according to the explanatory variables that intervened in theadjustment of themodel for collared peccary (A,B, C).Temperature is expressed in degrees Celsius and altitude in meters.Source of bioclimatic variables (bio), site https://www.worldclim.org/data/bioclim.html.
The umbrella value of caribou management strategies for biodiversity conservation in boreal forests under global change
<p><span>Single-species conservation management is often proposed to preserve biodiversity in human-disturbed landscapes. How global change will impact the umbrella value of single-species management strategies remains an open question of critical conservation importance. We assessed the effectiveness of threatened boreal caribou as an umbrella for bird and beetle conservation under global change. We combined mechanistic, spatially explicit models of forest dynamics and predator-prey interactions to forecast the impact of management strategies on the survival of boreal caribou in boreal forest. We then used predictive models of species occupancy to characterize concurrent impacts on bird and beetle diversity. Landscapes were simulated based on three scenarios of climate change and four of forest management. We found that strategies that best mitigate human impact on boreal caribou were an effective umbrella for maintaining bird and beetle assemblages. While we detected a stronger effect of land-use change compared to climate change, the umbrella value of management strategies for caribou habitat conservation were still impacted by the severity of climate change. Our results showed an interplay among changes in forest attributes, boreal caribou mortality, as well as bird and beetle species assemblages. The conservation status of some species mandates the development of recovery strategies, highlighting the importance of our study which shows that single-species conservation can have important umbrella benefits despite global change.</span></p>
Environmental Conservation & Buddhism Perspective
<p>During the Sabai Webinar Series 2, hosted by the Shwetaungthagathu Reform Initiative Centre (SRIc), Burmese Young Experts, including Mr. Tin Shine Aung, Sustainability Specialist, Mr. Kaung Ko Ko Sint, EHS Engineer, and Mr. Aung Kaung Htet, Professional Educator, engaged in a discussion on Environmental Conservation and the Buddhist Perspective.</p><p> </p><p>They highlighted the alignment of minimalism with Buddha's teachings and underscored its significance in the daily lives of followers of Buddha.</p><p> </p><p>This Sabai Webinar Series was conducted under the Edu4SD project.</p>
Data from: Conservation genetics of Notelaea lloydii (Oleaceae) in south-eastern Queensland, Australia
<p>Habitat fragmentation can increase the chance of population bottlenecks and inbreeding, and may ultimately lead to reduced fitness and local extinction. <em>Notelaea lloydii</em> is a native olive species endemic to Australia and listed as vulnerable due to its restricted distribution. A recent molecular systematics study has revealed there might be some geographic structuring among the <em>N. lloydii</em> populations. Therefore, we undertook a genome wide Single Nucleotide Polymorphism (SNP) analysis to determine levels and patterns of genetic diversity, inbreeding and gene flow within and among <em>N. lloydii</em> populations in south-eastern Queensland (SE-QLD). Furthermore, as the reproductive phase of a plant's life history has a profound influence on genetic diversity, life history reproductive traits were also studied. Our SNP analysis revealed low genetic diversity, inbreeding and significant genetic structuring even among proximate populations. Results of a flower and fruit bagging experiment in two consecutive seasons revealed that <em>N. lloydii </em>produced many flowers but only a few fruits survived to maturity. There were no differences in bagged and un-bagged flowering and fruiting rates and therefore, we conclude that the high fruit abortion rate was probably due to inbreeding depression and/or suboptimal conditions, rather than pollinator availability and insect attack. Overall, results of this study indicate that the populations of <em>N. lloydii</em> are small, inbred and genetically isolated and represent unique management units that require local conservation management due to ongoing threats associated with urbanisation.</p>
Conservative News Media and Criminal Justice: Evidence from Exposure to Fox News Channel
<p>Conservative News Media and Criminal Justice: Evidence from Exposure to Fox News Channel" (Elliott Ash and Michael Poyker), <i>Economic Journal</i>, 2023</p>
Conservation Ethnographies
<p>This dataset comprises PhD theses, jounral articles, books and reports that are about organsational ethnographies conducted with and on conservation organisations.</p><p>Ethnography based conservation organisation literature csv. contains 211 studies which were found through a systematic scoping study as part of research that is published in Methods Ecology and Evoloution. The dataset contains articles, books, journals and reports which are related to ethnography and conservation organisations and institutions.</p><p>The Methodology orientated studies, comprises 26 entries and are the shortlisted studies that met our inclusion criteria as per the published article in Methods Ecology and Evoloution.</p>
Data and code from Lamb et al., "Evaluating conservation units using network analysis: a sea duck case study"
<p>This file consists of data and code used to construct network models for scoters in North America and is associated with the manuscript "<strong>Evaluating conservation units using network analysis: a sea duck case study</strong>" published in Frontiers in Ecology and the Environment. </p><p> </p><p><strong>Continental scoter network mapping </strong>is the R script used to run analyses.</p><p> </p><p><strong>duck_nodes</strong> is the main datafile. Columns are organized as follows:</p><p>id - unique identifier</p><p>species - species from which the centroid was obtained (BLSC = black scoter, SUSC = surf scoter, WWSC = white-winged scoter)</p><p>stage - period of the annual cycle to which the centroid belongs (W = winter, B = breeding, S = spring staging, M = fall staging and molt, WM = winter migration, BM = breeding migration, MM = molt migration, SM = spring migration)</p><p>site - position of centroid within season (i.e., W1 = first site occupied during winter, W2 = second site occupied, etc.)</p><p>cycle - number of annual cycles following transmitter attachment (1 = first cycle after attachment, 2 = second cycle after attachment, etc.)</p><p>sex - sex of individual (M = male, F = female)</p><p>age - age of individual (HY = hatch year, SY = second year, TY = third year, ASY = after second year, ATY = after third year, AHY = after hatch year</p><p>capture_reg - general area where individual was captured</p><p>capture_subreg - specific region within capture region where individual was captured</p><p>lon - longitude of centroid</p><p>lat - latitude of centroid</p><p>duration - number of days spent at centroid</p><p>start - date of arrival at centroid</p><p>end - date of departure from centroid</p><p>jstart - Julian date of arrival at centroid</p><p>jend - Julian date of departure from centroid</p><p>season - season of annual cycle in which centroid occurred (W = winter, F = fall, B = breeding, S = spring)</p><p>year - calendar year in which centroid began</p><p>to - node in which centroid is grouped</p><p>from - node in which previous centroid is grouped (i.e., node in which indiviual was located before moving to present node)</p><p>to_sea - season of annual cycle in which centroid occurred</p><p>from_sea - season of annual cycle in which previous centroid occurred</p><p>type - movement type to centroid; the first letter represents the season (coded as in "season" column), and the second represents the nature of the movement (WD = dispersal within a season, M = migration among seasons)</p><p>type2 - same as "type", but with dispersal movements coded by the stage in which they occur (W = winter, B = breeding, SM = spring migration, WM = winter migration)</p><p>ew - capture location in eastern (east; Atlantic and Great Lakes) or western (west; Pacific) North America</p><p>count_ind_sp - total number of tracked individuals of the species represented by centroid</p><p>wt - base centroid weight (all centroids equal, deployments excluded)</p><p>wt_sp - species-adjusted centroid weight: for centroid <i>x</i> in species <i>s</i>, weight<i>x</i> = (<i>N </i>centroids) × (1 / (<i>n </i>centroids in <i>s</i>))</p><p>wt_dur - duration-adjusted centroid weight: for centroid <i>x</i>, weight<i>x</i> = (days at centroid location) × 365-1</p><p>wt_ind - individual-adjusted centroid weight: for centroid <i>x</i> in individual<i> j</i>, weight<i>x</i> = 1 / (<i>n </i>centroids in <i>j</i>)</p><p>wt_ind_sp - individual and species adjusted centroid weight: for centroid <i>x</i>, individual <i>j</i>, and species <i>s</i>, weight<i>x</i> = (<i>N </i>centroids / (<i>N </i>species * <i>n</i> individuals in <i>s</i>)) × (1 / (<i>n </i>centroids in <i>j</i>))</p><p>wt_cap - capture location adjusted centroid weight: for centroid <i>x</i> and capture location <i>c, </i>weight<i>x </i>= (<i>N </i>centroids / <i>N</i> capture locations) / <i>n</i> centroids in <i>c</i></p><p>wt_ew - east-west adjusted centroid weight: for for centroid <i>x</i> and region <i>r, </i>weight<i>x </i>= (<i>N </i>centroids / <i>N</i> regions) / <i>n</i> centroids in <i>r</i></p><p>wt_spew - species and east-west adjusted centroid weight: for centroid <i>x</i> species <i>s</i>, and region <i>r, </i>weight<i>x </i>= (<i>N </i>centroids / (<i>N</i> species × <i>N</i> regions)) / <i>n </i>centroids for species <i>s</i> in region <i>r</i></p><p>wt_indspew - individual, species, and east-west adjusted centroid weight: for centroid <i>x,</i> individual<i> j, </i>species <i>s</i>, and region <i>r, </i>weight<i>x </i>= <i>N </i>centroids / (<i>N</i> species × <i>N</i> regions × <i>n</i> centroids for individual <i>j </i>× <i>n</i> individuals for species <i>s</i> in region <i>r</i>)</p><p>wt_spewcap - species, east-west, and capture location adjusted centroid weight: for centroid <i>x,</i> species <i>s</i>, capture location <i>c, </i>and region <i>r, </i>weight<i>x </i>= <i>N </i>centroids / (<i>N</i> species × <i>N</i> regions × <i>n</i> centroids for species <i>s</i> in capture location <i>c </i>× <i>n</i> capture locations for species <i>s</i> in region <i>r</i>)</p>
Fig. 9 in Hornets (Vespidae: Vespinae) of Singapore: ecology, identification, and national conservation assessment
Fig. 9. Singaporean distribution of Vespa analis.
Fig. 2 in Hornets (Vespidae: Vespinae) of Singapore: ecology, identification, and national conservation assessment
Fig. 2. Singaporean distribution of Provespa anomala.
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Allen Brain Atlas
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OpenNeuro
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