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14 results for “Land degradation”
Photographic record of land degradation and resilience in Dogu'a Tembien after the shock of the Tigray war (northern Ethiopia)
<p><span>Following two years of combat, blockade, and power outage, the Tigray war in northern Ethiopia has had a substantial negative impact on the environment (2020–2022). This photographic dataset, part of a rare study carried out by the same research team before and after a war, compares 26-year legacy data on land degradation, with post-war observations at 56 sites in the Dogu'a Tembien district of Tigray (13°39'N, 39°30'E), at elevations ranging from 1600 to 2800 meters.</span></p> <p><span>With 30 years of environmental research experience in Tigray, we remained as a lone research team after the start of the war and collected ground data at previous research sites during the war. This culminated in international partners returning to the Dogu'a Tembien district in 2023 after they had been absent for four years due to coronavirus restrictions and the Tigray War. We visited 56 previously investigated sites—which have been documented in 45 prior publications—through transect walks, where we mostly made qualitative observations and discussions regarding the processes of land degradation and recovery. This included degradation processes like sheet and rill erosion</span><span>, gully erosion</span><span>, landslides</span><span></span><span>, deforestation</span><span>, as well as the most common rehabilitation approaches, i.e. stone bunds</span><span>, check dams</span><span>, exclosures</span><span>, improved hydrological cycle</span><span>, and integrated catchment management</span><span>. Local farmers and other village residents, along with experts who either reside in or have a good understanding of the research area, participated in the group observations.</span></p>
Summary for policymakers of the assessment report on land degradation and restoration of the Intergovernmental SciencePolicy Platform on Biodiversity and Ecosystem Services: Figure SPM.1
<p>The purpose of Figure SPM.1 is to support the statement that land degradation occurs just about everywhere in the world (i.e. it is ‘pervasive’), takes many forms, and that examples of successful restoration are also widespread. The figure consists of a backdrop map of the world from a multiple land degradation perspective, showing the level of uncertainty between studies, overlaid with dots representing all the places specifically mentioned in the eight chapters of the main Assessment Report on Land Degradation and Restoration, including case studies of both degradation and restoration. Around the map are brief notes regarding the main forms of degradation encountered.</p>
Output data from: From land productivity trends to land degradation assessment in Mozambique: Effects of climate, human activities and stakeholder definitions
<p>This repository includes output data from the following article:</p> <p><strong>Montfort, F., Bégué, A., Leroux, L., Blanc, L., Gond, V., Cambule, A.H., Remane, I.A.D., Grinand, C., 2020. From land productivity trends to land degradation assessment in Mozambique: Effects of climate, human activities and stakeholder definitions. <em>Land Degrad Dev</em>.; 32: 49– 65. <a href="https://doi.org/10.1002/ldr.3704">https://doi.org/10.1002/ldr.3704</a></strong></p> <p>This study aimed at characterizing and mapping the underlying factors (human or climatic) in land productivity changes over the 2000-2016 period, in order to assess land degradation in Mozambique.</p> <p>The methodology is based on remote sensing methodology. Land productivity change were first analyzed using MODIS NDVI time-series (2000–2016), and a two-step framework was then used to understand the main factors of these productivity changes, using climate times series (CHIRPS data for rainfall and CRU data for temperature), Land Use and Land Cover Change (LULCC) maps (Laurel project LULCC map), and ground knowledge.</p> <p>This repository includes raster data of annual land productivity change over the 2000-2016 period, annual land productivity climate factors, potential land productivity decrease factors and potential productivity increase factors. Data are available as GeoTIFF raster files at 250 m resolution in the UTM 37S projection (EPSG: 32737).</p>
A new approach to simulate peat accumulation, degradation and stability in a global land surface scheme (JULES vn5.8_accumulate_soil) for northern and temperate peatlands
<p>This is the data (model output from JULES and observational data) used in the paper "A new approach to simulate peat accumulation, degradation and stability in a global land surface scheme (JULES vn5.8_accumulate_soil) for northern and temperate peatlands" for the resubmitted version after review of the discussion paper in Geoscientific Model Development Discussions (2021) https://doi.org/10.5194/gmd-2021-263. R code is provided that will recreate all of the plots in the paper using the data provided. These data include outputs from the JULES model including developments to represent peat accumulation, and observational data of peat properties (most are taken from other sources: references provided therein).</p>
Rare soil microbial taxa regulate the negative effects of land degradation drivers on soil organic matter decomposition
<p>1. Land degradation drivers, including loss in vegetation and eutrophication, are expected to impact soil biodiversity and functions in drylands world-wide. Soils contain both common and rare microbial taxa that drive multiple soil functions. Yet, little is known about how these microbial taxa influence the impacts of land degradation drivers on ecosystem functions. Obtaining this information is essential to determine whether rare taxa need to be protected, or if protecting only common taxa would be enough to sustain and protect ecosystem functions and services.</p> <p>2. Here, we conducted an experiment to investigate the effects of N-enrichment and vegetation loss (plant removal), which are two major land degradation drivers in semi-arid grasslands, on the diversities of common and rare soil bacterial and fungal taxa and soil function [soil organic matter (SOM) decomposition] in a long-term experiment.</p> <p>3. Six years after N-enrichment and vegetation loss, we found that N-enrichment decreased the alpha diversities of common and rare soil bacteria and rare soil fungi, while vegetation loss only decreased the alpha diversity of rare soil fungi. Both N-enrichment and vegetation loss altered the community composition of common and rare bacteria and fungi, except for the lack of response of common soil fungi to the vegetation loss. Moreover, both structural equation modelling and variation partitioning analyses show that land degradation drivers reduce SOM decomposition, and these were also indirectly associated with changes in the diversity of rare microbial taxa, especially that of bacteria.</p> <p>4.<em> Synthesis and applications</em>. Collectively, this work shows that land degradation can have negative impacts on soil biodiversity and functions, and the rare microbial taxa indirectly regulate the impacts of land degradation on ecosystem functioning. These results indicate that the rare microbial taxa can be used as one of the ecological indicators for identifying land degradation in the semi-arid grasslands. These findings are essential to understand the future impacts of desertification and land degradation on rare microbial taxa–function relationships in global drylands.</p>
Data from: Projected land use changes will cause water quality degradation at drinking water intakes across a regional watershed
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Rare soil microbial taxa regulate the negative effects of land degradation drivers on soil organic matter decomposition
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Data from: Legume life history interacts with land use degradation of rhizobia: Implications for restoration success
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Plant diversity enhances rehabilitation of degraded lands by spurring plant-soil feedbacks
<p>Despite a rich history of theoretical and empirical work showing that increasing biodiversity results in higher ecosystem function, this research has not made a commensurate impact on the reclamation of degraded lands, where enhancing ecosystem function is of primary importance. 2. In this study, we manipulated plant diversity on heavily degraded mine lands and showed that increasing plant diversity greatly enhanced the reclamation of these lands. We found that high diversity assemblages were often associated with more biomass, higher stability and less toxic foliage than low diversity treatments, although the monocultures of Miscanthus sinensis (the most productive species) performed equally well as some of the polycultures. 3. Our results showed that species composition and richness explained most of the total variation in biomass yield of the experimental plots, indicating that both the selection and complementarity effects influenced the positive diversity effects observed in this study. 4. M. sinensis and legumes (as a functional group) were found to be the main contributors to the selection effect. The plots with M. sinensis tended to harbor fewer soil fungal pathogens than those without it and a similar pattern was observed for the legumes, indicating a poorly known plant-soil fungal pathogen feedback for these plants. This kind of feedback appeared to play an important role also in shaping the positive plant species richness-ecosystem function relationships recorded in the degraded mine land. More importantly, we provide the first evidence that the observed plant-soil fungal pathogen feedbacks were likely mediated by chitinolytic bacteria that release anti-fungal enzymes. Cellulose-degrading bacteria that aid in plant decomposition and nutrient cycling also attained higher abundances in plots with higher plant diversity, suggesting the contribution of another kind of plant-soil feedback to the positive diversity effects. 5. Synthesis and applications. Our findings reveal that high diverse plant assemblages are better able to spur plant-soil feedbacks and that increasing plant diversity is an important strategy to enhance land reclamation efficiency. Meanwhile, our results also indicate that some plants such as M. sinensis and legumes should be preferentially used to establish diverse plant communities for rapid reclamation of degraded lands.</p>
Plant diversity enhances rehabilitation of degraded lands by spurring plant-soil feedbacks
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Land degradation and development
<p>All figures of the manuscript which submitted to Land degradation and development.</p>
Data from: Effects of forest degradation on Amazonian ferns in a land-bridge island system as revealed by non-specialist inventories
<p>Background: Tropical deforestation and degradation worldwide have rapidly outpaced biodiversity field sampling. No study to date has assessed the effects of insular habitats induced by hydroelectric dams on Amazonian understorey plants. Fern community responses to anthropogenic effects on tropical forest islands can be efficiently revealed through simple and cheap, yet informative protocols that can be applied by non-specialists. </p> <p>Aims: This study seeks to both understand the drivers of fern and lycophyte assemblages on forest islands and investigate the relative costs and effectiveness of a simplified sampling protocol that can be implemented by non-specialists and has potential to be used to crowdsource ecological field data acquisition.</p> <p>Methods: Fern and lycophytes species were sampled by a non-specialist in 17 quarter-hectare plots on 10 forest islands at the lake of Balbina Hydroelectric Dam, central Amazonia. Sampling was carried out opportunistically during a field expedition planned to conduct tree inventory on permanent plots. We used a set of locally measured or GIS-derived predictors for each of the surveyed sites. We used Principal Coordinates Analysis and Generalized Linear Mixed Models (GLMMs) to further assess the influence of predictors on patterns of fern species richness and composition.</p> <p>Results: A total of 286 photographed individual ferns or lycophytes represented 23 taxa. The average number of taxa per plot was 6.1 on islands and 14.3 in the mainland. The insular species pool was a subset of the mainland pool of fern species. Richness was positively related to island size and negatively related to isolation and fire severity. Area, isolation and fire severity significantly explained variation in community composition. The relative cost of the non-specialist picture-based fern protocol was very modest (in our case, only 4% of the total expedition budget), even compared to the typically low cost of alternative orthodox field campaigns.</p> <p>Conclusion: Fern community structure in this forest archipelago was primarily driven by island size, isolation and fire disturbance. We show that a simple sampling protocol carried out by a non-specialist can lead to inexpensive and highly reliable ecological data. This opens an avenue for crowdsourcing ecological fern data collections using a citizen science approach.</p>
Data from: Effects of forest degradation on Amazonian ferns in a land-bridge island system as revealed by non-specialist inventories
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Training Data - Effects of seasonality and classifier on the accuracy of grazing resource and land degradation maps in a savanna ecosystem
<p>This csv file contains training data (class and coordinates (latitude and longitude)) used in the classification models presented in the paper - Effects of seasonality and classifier on the accuracy of grazing resource and land degradation maps in a savanna ecosystem</p>
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Allen Brain Atlas
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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.