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67 results for “Environmental conservation”
An Innovative Scheme to Confront the Trade‐Off Between Water Conservation and Heat Alleviation With Environmental Justice for Urban Sustainability: The Case of Phoenix, Arizona
<p><em><strong>The manuscript for this dataset is accepted by AGU Advances and can be accessed here: <a href="https://doi.org/10.1029/2022AV000816">link</a>. Please cite the literature when using the datasets.</strong></em></p> <p><strong>How to cite this article: Yuanhui Zhu, Soe Myint, Xin Feng, Yubin Li. An Innovative Scheme to Confront the Trade‐Off Between Water Conservation and Heat Alleviation With Environmental Justice for Urban Sustainability: The Case of Phoenix, Arizona. AGU Advances, 4, e2022AV000816. <a href="https://doi.org/10.1029/2022AV000816">https://doi.org/10.1029/2022AV000816</a></strong></p> <p>This study aims to develop a practical and integrated framework to tackle the tradeoff between land surface temperature (LST) reduction and water conservation for heat mitigation and resilience planning in Phoenix, Arizona. We developed a multi-objective framework of spatial optimization for priority areas that considers environmental justice. We employed the priority areas (i.e., residential districts, socio-economically disadvantaged neighborhoods, hotspot regions, and opportunity areas), ECOSTRESS-based LST, actual evapotranspiration (ETa, as a proxy to water use), Landsat-based LST and ETa changes (2000–2020), and the evaporative stress index (ESI). These datasets are used to identify the priority areas in which environmental conditions need to be improved seriously and (2) spatially optimize the placement of new green space (tree %, grass %) in the priority areas to realize the most significant LST reduction and minimum OWU. We provide the results of the new green space configurations with the scenarios for the percentage of new vegetation coverage (including trees and grass) overall increased to 25%, 35%, and 45% within the entire study areas, residential districts, socio-economically disadvantaged neighborhoods, and hotspot regions.</p> <table> <caption>The dataset summarization</caption> <tbody> <tr> <td>Category</td> <td>Dataset</td> <td>Resolution</td> <td>Source/method</td> <td>Time</td> </tr> <tr> <td>Environmental database</td> <td>Summer daytime LST</td> <td>70m</td> <td>ECOSTRESS</td> <td>2019</td> </tr> <tr> <td>Environmental database</td> <td>Summer nighttime LST</td> <td>70m</td> <td>ECOSTRESS</td> <td>2019</td> </tr> <tr> <td>Environmental database</td> <td>Summer ETa</td> <td>70m</td> <td>ECOSTRESS</td> <td>2019</td> </tr> <tr> <td>Environmental database</td> <td>Summer ESI</td> <td>70m</td> <td>ECOSTRESS</td> <td>2019</td> </tr> <tr> <td>Environmental change database</td> <td>Trends of summer LST changes</td> <td>30m</td> <td>Landsat-based Statistical Mono-Window algorithm</td> <td>2000-2020</td> </tr> <tr> <td>Environmental change database</td> <td>Trends of summer ETa changes</td> <td>30m</td> <td>Landsat-based Simplified Surface Energy Balance</td> <td>2000-2020</td> </tr> <tr> <td>The results of new green space configurations</td> <td>The spatial distributions of new green space</td> <td>--</td> <td>Spatial optimization</td> <td>--</td> </tr> </tbody> </table> <p>note: LULC: Land use and land cover; LST: Land Surface Temperature; ETa: Actual Evapotranspiration; ESI: Evaporative Stress Index</p> <p>We provide the different scenarios in shapefile format for spatial distributions of new space configurations. The naming convention for attribute tables in shapefile is :</p> <p>VV_new_perNN_LSTWW</p> <p>where:</p> <ul> <li>VV = New vegetation for tree or grass</li> <li>NN = The scenarios with new vegetation increased to 25%, 35%, or 45% (unit: %)</li> <li>WW = The weight values of land surface temperature range from 0 to 1 (unit: %) when executing spatial optimization for the tradeoff between land surface temperature reduction and outdoor water use conservation with vegetation coverage. The weight of 0 represents that our spatial optimization models only focus on outdoor water use conservation, and the weight of 1 denotes that we only consider land surface temperature reduction. </li> </ul> <p>Example: grass_new_per25_LST65 means -- new vegetation for grass; the scenario is set up by new vegetation increased to 25%; the weight of land surface temperature is 0.65. </p> <p> </p>
Figure 7 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 7. Box plots show the distribution of relative abundances of the associations across the six facies types.
Figure 3 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 3. Sampling locations of three expeditions in 2015–2017. The first (September–October 2015) and second expeditions (July 2016) were searching for living Pontocaspian molluscs in particular. The third expedition consisted of six transects sampled by GeoEcoMar in 2017 in search of any living mollusc. In the legend w/wo means with or without.
Figure 1 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 1. Location of study area along the Romanian Black Sea coast with core locations indicated by black stars. (a) Danube Delta and RSL (modified after Vespremeanu-Stroe et al., 2017). (b) RSL bathymetry with location of study cores (modified after Dimitriu et al., 2008). Two current marine outlets are indicated by white arrows; a third outlet (Gura Portiţa) was closed in the 1970s and is indicated by a dashed white arrow.
Figure 6 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 6. Overview of the 20 most abundant mollusc species grouped according to the results of Kendall's W coefficient of concordance (for k = 4). (a) Valvata piscinalis (RGM.1309841, Core C7, depth 6 cm). (b) Dreissena polymorpha (RGM.1309827, C7 – 6 cm). (c) Dreissena bugensis (RGM.1309846, C5 – 18 cm). (d) Adacna fragilis (RGM.1309835, C2 – 18 cm). (e) Monodacna colorata s.l. (RGM.1309823, C7 – 14 cm). (f) Rissoa membranacea (RGM.1309830, C3 – 48 cm). (g) Hypanis plicata (RGM.1309845, C9 – 3 cm). (h) Clathrocaspia knipowitschii (RGM.1309843, C11 – 102 cm). (i) Mytilaster minimus (RGM.1309838, C3 – 24 cm). (j) Ecrobia maritima (RGM.1309831, C3 – 48 cm). (k) Cerastoderma glaucum (RGM.1309844, C13 – 24 cm). (l) Abra segmentum (RGM.1309821, C1 – 48 cm). (m) Parthenia interstincta (RGM.1309832, C3 – 48 cm). (n) Lentidium mediterraneum (RGM.1309837, C4 – 12 cm). (o) Retusa truncatula (RGM.1309828, C2 – 42 cm). (p) Gyraulus crista (RGM.1309840, C5 – 54 cm). (q) Potamopyrgus antipodarum (RGM.1309836, C2 – 18 cm). (r) Lithoglyphus naticoides (RGM.1309842, C5 – 18 cm). (s) Theodoxus fluviatilis (RGM.1309826, C11 – 66 cm). (t) T. fluviatilis (RGM.1309824, C11 – 78 cm). (u) Theodoxus danubialis (RGM.1309839, C3 – 24 cm). (v) T. danubialis (RGM.1309834, C2 – 30 cm). Scale bars are 1 mm.
Figure 2 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 2. Overview of core data. From left to right each core: core photograph, lithology, facies, fauna relative abundance per species group based on origin, evolution and estimated palaeosalinities.
Figure 5 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 5. NMDS ordination plot of species compositions across samples grouped into lake regions (stress = 0.173). Optimum salinity and grain size were fitted as two-dimensional smooth surfaces to illustrate the associations with species composition. Species are marked with numbers: 1 – Planorbis planorbis, 2 – Clathrocaspia knipowitschii, 3 – Potamopyrgus antipodarum, 4 – Theodoxus danubialis, 5 – Planorbarius corneus, 6 – Abra segmentum, 7 – Rissoa membranacea, 8 – Valvata macrostoma, 9 – Hypanis plicata, 10 – Mytilaster minimus, 11 – Ecrobia maritima, 12 – Parthenia interstincta, 13 – Cerastoderma glaucum and 14 – Lentidium mediterraneum.
Figure 8 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 8. Snapshot reconstructions of the evolution of the RSL and their mollusc biota. The names of major sand barriers are indicated in yellow, while those of deltaic lobes are in black. The names in parentheses and italic font are currently inactive lobes. Pie charts indicate the relative abundance of the three associations in the time interval of ±50 years of the indicated snapshot: blue – Association I (freshwater); green – Association II (Pontocaspian), orange – Association III (marine), grey – rest of the group. Water colours indicate a salinity gradient: blue is Black Sea influence (18 psu); green is river influence (0 psu). Note the freshening of the system and according changes in species associations with the decreasing influence of mesohaline waters from the Black Sea.
Figure 4 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 4. Spatiotemporal salinity variations in the RSL. For each sample, the salinity was calculated by weighted averaging of the species' optimum salinities. Salinity categories adapted from Strydom et al. (2003). Snapshots referred to in the Discussion are indicated with letters A–F.
Data from: An adaptive biomolecular condensation response is conserved across environmentally divergent species
<p>Cells must sense and respond to sudden maladaptive environmental changes—stresses—to survive and thrive. Across eukaryotes, stresses such as heat shock trigger conserved responses: growth arrest, a specific transcriptional response, and biomolecular condensation of protein and mRNA into structures known as stress granules under severe stress. The composition, formation mechanism, adaptive significance, and even evolutionary conservation of these condensed structures remain enigmatic. Here we provide an unprecedented view into stress-triggered condensation, its evolutionary conservation and tuning, and its integration into other well-studied aspects of the stress response. Using three morphologically near-identical budding yeast species adapted to different thermal environments and diverged by up to 100 million years, we show that proteome-scale biomolecular condensation is tuned to species-specific thermal niches, closely tracking corresponding growth and transcriptional responses. In each species, poly(A)-binding protein—a core marker of stress granules—condenses in isolation at species-specific temperatures, with conserved molecular features and conformational changes modulating condensation. From the ecological to the molecular scale, our results reveal previously unappreciated levels of evolutionary selection in the eukaryotic stress response, while establishing a rich, tractable system for further inquiry.</p>
Environmental DNA metabarcoding reveals and unpacks a biodiversity conservation paradox in Mediterranean marine reserves
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Data from: An adaptive biomolecular condensation response is conserved across environmentally divergent species
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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>
Assessing the conservation priority of freshwater lake sites based on taxonomic, functional and environmental uniqueness
<p><strong>Aim: </strong>We propose a novel approach that considers taxonomic uniqueness, functional uniqueness and environmental uniqueness, and show how it can be used in guiding conservation planning. We illustrate the approach using data for lake biota and environment.</p> <p><strong>Location: </strong>Lake Puruvesi, Finland.</p> <p><strong>Methods: </strong>We sampled macrophytes and macroinvertebrates from the same 18 littoral sites. By adapting the original 'ecological uniqueness' approach, we used distance‒based methods to calculate measures of taxonomic (LCBD‒t), functional (LCBD‒f) and environmental (LCEH) uniqueness for each site. We also considered the numbers and locations of the sites needed to protect up to 70% of total variation in taxonomic, functional or environmental features in the studied part of the lake.</p> <p><strong>Results: </strong>Relationships between taxonomic (LCBD‒t), functional (LCBD‒f) and environmental (LCEH) uniqueness were generally weak, and only the relationship between macrophyte LCBD‒t and LCBD‒f was statistically significant. Overall, however, if the whole biotic dataset was considered, macroinvertebrate LCBD‒f values showed a consistent positive relationship with macrophyte LCBD‒f. Depending on the measure of site uniqueness, between one third to one half of the sites could help protect up to 70% of the ecological uniqueness of the studied part of Lake Puruvesi.</p> <p><strong>Main conclusions: </strong>Although the dataset examined originated from a large lake system, the approach we proposed here can be applied in different ecosystems and at various spatial scales. An important consideration is that a set of sites has been sampled using the same methods, resulting in species and environmental matrices that can be analysed using the methodological approach proposed here. This framework can be easily applied to grid‒based data, sets of islands, or sets of forest fragments. We suggest that the approach based on taxonomic, functional and environmental uniqueness will be a useful tool in guiding nature conservation and ecosystem management, especially if associated with meta‒system ideas or network thinking.</p>
Identifying the environmental drivers of corridors and predicting connectivity between seasonal ranges in multiple populations of Alpine ibex (Capra ibex) as tools for conserving migration
<p># GPS locations of Alpine ibex</p> <p>This dataset contains migratory tracks of Alpine ibex identified using the application Migration Mapper (https://migrationinitiative.org/content/migration-mapper) and used in the work <strong>Identifying the environmental drivers of corridors and predicting connectivity between seasonal ranges in multiple populations of Alpine ibex (<em>Capra ibex</em>) as tools for conserving migration</strong></p> <p># Dataset structure</p> <p>Each row of the dataset represents a GPS location with its coordinates contained in the x (longitude) and y(latitude) columns. Coordinates are given in wgs84 (epsg 4326).<br> The column t1_ informs on the date and time the location was recorded.<br> The id and pop columns provide information about the identity of the animal and the population to which it belongs.</p> <p> </p>
Supplementary material: for Using anticipation to unveil drivers of local livelihoods in Transfrontier Conservation Areas: a call for more environmental justice
<ol> <li> <span>Calling on the concept of environmental justice in its </span><span>distributive, procedural, and recognition</span><span> dimensions, </span><span>w</span><span>e implemented a collaborative scenario-building approach to explore sustainable livelihood pathways in four sites belonging to two Transfrontier Conservation Areas (TFCAs) in southern Africa. </span> </li> <li><span>Grounded on participation and transdisciplinarity, as a foundation for decolonised anticipatory action research, we aimed at stimulating knowledge exchange and providing insights on the future of local livelihoods by engaging experts living within these TFCAs. </span></li> <li><span>Our results show that wildlife and wildlife-related activities are not seen as the primary drivers of local livelihoods, despite the focus and investments of dominant stakeholders in these sectors. Instead, local governance and land use regulations emerged as key drivers in the four study sites. The state of natural resources, including water, and appropriate farming systems also appeared critical to sustain future livelihoods in TFCAs, together with the recognition of indigenous culture, knowledge, and value systems.</span></li> <li><span>Nature conservation, especially in Africa, is rooted in its colonial past and struggles to free or decolonise itself from the habits of this past despite decades of reconsideration. To date, the enduring coloniality of conservation prevents local citizens from truly participating in the planning and designing of the TFCAs they live in, leaving room for limited benefits to local citizens and often limiting indigenous people's capacity to conserve. </span></li> <li> <span>A practical way forward is to consider environmental justice as a cement between the two pillars of the TFCA concept, i.e.</span><span>nature conservation and socioeconomic development of local or neighbouring communities,</span><span> as part of a more broad and urgent need to rethink the relationships between people in, and with, the rest of nature.</span> </li> </ol>
Data from: Environmental DNA metabarcoding elucidates freshwater mussel diversity and occupancy to facilitate improved management and conservation
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Supplementary material: for Using anticipation to unveil drivers of local livelihoods in Transfrontier Conservation Areas: a call for more environmental justice
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Data and code from: Public participation in tropical conservation and environmental management research: Towards a locally grounded and reflexive practice
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Environmental DNA metabarcoding reveals and unpacks a biodiversity conservation paradox in Mediterranean marine reserves
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OpenNeuro
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