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300 results for “land change”
Supplementary material for "Strong decline in grasshopper abundance over 20 years without major land-use changes: Is soil drying one of the drivers?»
<p><strong>Abstract</strong></p> <p><span>Strong declines in insect numbers have been described for different taxa and regions. These observations are of great concern such that broad scientific and public attention has been raised. Among other urgencies, the need for long-term insect data has been identified. Here, we present data on grasshopper (Caelifera) abundances recorded between 1992 and 2011 at over 600 sites in north-western Switzerland. While vegetation type, often semi-natural grasslands, had remained largely constant, total grasshopper abundance declined by around 50% (while many other taxa showed much less decline). Numbers in July remained relatively stable until about 2003 but then declined similar to the declines seen in August-October already before. Greatest losses were observed for drier habitats and steeper slopes, suggesting that soil drying might be an important factor for the decline. Second, more nutrient-rich habitats suffered greater losses; possible reasons for this include small-scale vegetation changes in these habitats e.g. due to atmospheric nitrogen deposition, or isolation of sites. Other than abundance, species richness decreased much less, illustrating that important ecological changes may be strongly underestimated when only species lists are available. The strong declines at our sites, which often are in an agri-environmental scheme, is alarming. Apart from being yet another call to fight climate change, our results also point to the urgent need to reduce atmospheric nitrogen deposition and to continue extensive farming, but also to adapt it in preparation of expected effects of climate change, with the aim to favour a divers, ecologically robust insect community.</span></p> <p><span> </span></p>
Data from: Response of net primary production to land use and climate changes in the middle-reaches of the Heihe River basin
Net primary production (NPP) supplies matter, energy, and services to facilitate the sustainable development of human society and ecosystem. The response mechanism of NPP to land use and climate changes is essential for food security and biodiversity conservation but lacks a comprehensive understanding, especially in arid and semi-arid regions. To this end, taking the middle-reaches of the Heihe River basin (MHRB) as an example, we uncovered the NPP responses to land use and climate changes by integrating multi-source data (e.g., MOD17A3 NPP, land use, temperature, and precipitation) and multiple methods. The results showed that: (1) land use intensity (LUI) increasing, and climate warming and wetting promoted NPP. From 2000 to 2014, the LUI, temperature and precipitation of MHRB increased by 1.46, 0.58 °C and 15.76 mm, respectively, resulting in an increase of 14.62 gC/m2 in annual average NPP. (2) The conversion of low-yield cropland to forest and grassland increased NPP. Although the widespread conversion of unused land and grassland to cropland boosted both LUI and NPP, it was not conducive to ecosystem sustainability and stability due to huge water consumption and human-appropriated NPP. Urban sprawl occupied cropland, forest and grassland, and reduced NPP. (3) Increase in temperature and precipitation generally improved NPP. The temperature decreasing less than 1.2 °C also promoted the NPP of hardy vegetation due to the simultaneous precipitation increasing. However, warming-induced water stress compromised the NPP in arid sparse grassland and deserts. Cropland had greater NPP and NPP increase than natural vegetation due to the irrigation, fertilizers and other artificial inputs it received. Decrease in both temperature and precipitation generally reduced NPP, but the NPP in the well-protection or less-disturbance areas still increased slightly.
Code and Data: WRF v.3.9 sensitivity to land surface model and horizontal resolution changes over North America
<p>Data and code used to obtain results published in Garcia-Garcia et al 2021: WRF v.3.9 sensitivity to land surface model and horizontal resolution changes over North America. Submited to<em> Geosci. Model Dev</em>.</p>
Preserving wintering frugivorous birds in agro‐ecosystems under land use change: Lessons from intensive and super-intensive olive orchards
<p>Fleshy-fruit production is becoming more intensive worldwide, but how this affects frugivorous birds is poorly known. In the Mediterranean region, intensive and super-intensive olive orchards are fast expanding, potentially affecting millions of wintering songbirds. Here we test the idea that intensification may benefit frugivorous birds, at least locally, due to increased fruit availability, while negatively affecting the wider wintering bird community due to intensive management, structural simplification and landscape homogenisation. We estimated olive abundance and surveyed birds in early, mid- and late winter, at traditional, intensive, and super-intensive orchards in southern Portugal. We used Hierarchical Modelling of Species Communities to relate species richness, prevalence and abundance to management intensity, winter period, olive availability and landscape context, and evaluated the role of frugivory on observed responses. Olive availability was much higher throughout the winter in more intensive than in traditional orchards, both in trees and on the ground. Frugivorous bird abundance was higher in more intensive orchards, and the most abundant frugivorous species (blackcap, song thrush, robin) were positively affected by olive availability and/or increasing landscape cover by olive orchards, while intensification level had relatively minor effects after accounting for other variables. Non-frugivorous richness and abundance were higher in traditional orchards, and many non-frugivorous species were less prevalent in more intensive orchards or negatively affected by landscapes dominated by olive cultivation. Synthesis and applications. While negatively affecting the wider bird community, our results suggest that olive farming intensification can contribute to sustain large numbers of frugivorous birds in the Mediterranean region. As frugivorous birds are not seen as damaging by olive farmers, there is an opportunity to promote their conservation in intensive and super-intensive orchards, which requires management to increase habitat heterogeneity, and to reduce risks such as mortality associated with mechanical harvest and contamination with pesticide residues. Overall, we recommend that efforts to manage farmland biodiversity should consider the impacts and conservation opportunities of fruit crop intensification.</p>
Preserving the woody plant tree of life in China under future climate and land-cover changes
<p><span>The tree of life (TOL) is severely threatened by climate and land-cover changes. Preserving the TOL is urgent, but has not been included in the post-2020 global biodiversity framework. Protected areas (PAs) are fundamental for biological conservation. However, we know little about the effectiveness of existing PAs in preserving the TOL of plants and how to prioritize PA expansion for better TOL preservation under future climate and land-cover changes. Here, using high-resolution distribution maps of 8732 woody species in China and phylogeny-based Zonation, we find that current PAs perform poorly in preserving the TOL </span><span>both at the present and in the 2070s</span><span>. The geographical coverage of TOL branches by current PAs is ca. 9%, and < 3% of the identified priority areas for preserving the TOL are currently protected. Interestingly, the geographical coverage of TOL branches by PAs will be improved from 9% to 52–79% by the identified priority areas for PA expansion. Human pressures in the identified priority areas are high, leading to high costs for future PA expansion. We thus suggest that besides nature reserves and national parks, other effective area-based conservation measures should be considered. Our study argues for the inclusion of preserving the TOL in the post-2020 conservation framework and provides references for decision-makers </span><span>to preserve the Earth's evolutionary history.</span></p>
Quantitative Assessment of the Impact of Future Land Use Changes on Flood Risk Using Remote Sensing, Machine Learning, and a Hydraulic Model
<p> </p> <p>The RF Machine learning code </p> <p>Topological, geomorphology, geology, metrological information of the Tajan watershed.</p> <p>Land use land cover images of the Tajan watershed</p> <p>River, transportation roads, villages map </p> <p>Global damage function datasets.</p>
Data for "Energy Surplus and Atmosphere – Land-Surface "Tug of War" Induced by Climate Change Control Future Evapotranspiration"
<p>USGS gauges used in manuscript "<strong>Energy Surplus and An Atmosphere-Land-Surface “Tug of War” Control Future Evapotranspiration"</strong>. USGS_CTL15_Gage.mat contains the USGS gauge ID, and one can use retrieve_daily_streamflow.m to download the corresponding streamflow time series. </p>
SyntheWorld: A Large-Scale Synthetic Dataset for Land Cover Mapping and Building Change Detection
<p><strong>Paper Accept by WACV 2024</strong></p> <p>[paper, supp] [<a href="https://arxiv.org/abs/2309.01907">arXiv</a>]</p> <p><strong>Overview</strong></p> <p>Synthetic datasets, recognized for their cost effectiveness, play a pivotal role in advancing computer vision tasks and techniques. However, when it comes to remote sensing image processing, the creation of synthetic datasets becomes challenging due to the demand for larger-scale and more diverse 3D models. This complexity is compounded by the difficulties associated with real remote sensing datasets, including limited data acquisition and high annotation costs, which amplifies the need for high-quality synthetic alternatives. To address this, we present SyntheWorld, a synthetic dataset unparalleled in quality, diversity, and scale. It includes 40,000 images with submeter-level pixels and fine-grained land cover annotations of eight categories, and it also provides 40,000 pairs of bitemporal image pairs with building change annotations for building change detection task. We conduct experiments on multiple benchmark remote sensing datasets to verify the effectiveness of SyntheWorld and to investigate the conditions under which our synthetic data yield advantages.</p> <pre><strong>Description</strong> ------------ This dataset has been designed for land cover mapping and building change detection tasks. File Structure and Content: --------------------------- 1. **1024.zip**: - Contains images of size 1024x1024 with a GSD (Ground Sampling Distance) of 0.6-1m. - `images` and `ss_mask` folders: Used for the land cover mapping task. - `images` folder: Post-event images for building change detection. - `small-pre-images`: Images with a minor off-nadir angle difference compared to post-event images. - `big-pre-images`: Images with a large off-nadir angle difference compared to post-event images. - `cd_mask`: Ground truth for the building change detection task. 2. **512-1.zip**, **512-2.zip**, **512-3.zip**: - Contains images of size 512x512 with a GSD of 0.3-0.6m. - `images` and `ss_mask` folders: Used for the land cover mapping task. - `images` folder: Post-event images for building change detection. - `pre-event` folder: Images for the pre-event phase. - `cd-mask`: Ground truth for building change detection. Land Cover Mapping Class Grep Map: ---------------------------------- class_grey = { "Bareland": 1, "Rangeland": 2, "Developed Space": 3, "Road": 4, "Tree": 5, "Water": 6, "Agriculture land": 7, "Building": 8, }</pre> <p><strong>Reference</strong></p> <p>@misc{song2023syntheworld,<br> title={SyntheWorld: A Large-Scale Synthetic Dataset for Land Cover Mapping and Building Change Detection}, <br> author={Jian Song and Hongruixuan Chen and Naoto Yokoya},<br> year={2023},<br> eprint={2309.01907},<br> archivePrefix={arXiv},<br> primaryClass={cs.CV}<br> }</p> <p> </p>
Data for: The kinetic Ising model encapsulates essential dynamics of land pattern change
<p>A land pattern change represents a globally significant trend with implications for the environment, climate, and societal well-being. While various methods have been developed to predict land change, our understanding of the underlying change processes remains inadequate. To address this issue, we investigate the suitability of the 2D kinetic Ising model (IM), an idealized model from statistical mechanics, for simulating land change dynamics. We test the IM on a variety of patterns, each with different focus land type. Specifically, we investigate four sites characterized by distinct patterns, presumably driven by different physical processes. Each site is observed on eight occasions between 2001 and 2019. Given the observed pattern at the time $t_i$ we find two parameters of the IM such that the model-evolved land pattern at $t_{i+1}$ resembles the observed land pattern at that time. The data supports simulating seven such transitions per site.</p> <p>Our findings indicate that the IM produces approximate matches to the observed patterns in terms of layout, composition, texture, and patch size distributions. Notably, the IM simulations even achieve a high degree of cell-scale pattern accuracy in two of the sites. Nevertheless, the IM has certain limitations, including its inability to model linear features, account for the formation of new large patches, and handle pattern shifts.</p>
Large carnivore expansion in Europe is associated with human population density and land cover changes
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Data from: Contrasting impacts of land use change on phylogenetic and functional diversity of tropical forest birds
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Data from: Understanding patterns of land-cover change in the Brazilian Cerrado from 2000 to 2015
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Data from: Contemporary land change alters fish communities in a San Francisco Bay drainage, California, U.S.A.
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Data from: Land colonisation by fish is associated with predictable changes in life history
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Data from: Present conditions may mediate the legacy effect of past land-use changes on species richness and composition of above- and below-ground assemblages
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Data from: Wildfire activity and land use drove 20th-century changes in forest cover in the Colorado front range
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Data from: On the inconsistency of pollinator species traits for predicting either response to land-use change or functional contribution
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Data from: Response of net primary production to land use and climate changes in the middle-reaches of the Heihe River basin
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Data from: Annual temperature variation influences the vulnerability of montane bird communities to land-use change
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Preserving wintering frugivorous birds in agro‐ecosystems under land use change: Lessons from intensive and super-intensive olive orchards
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.