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ShareScore release 0.9.0
Dataset results
30 results for “Tropical forest recovery”
Data from: Linking coordinated hydraulic traits to drought and recovery responses in a tropical montane cloud forest
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Data from: Long-term recovery of the functional community assembly and carbon pools in an African tropical forest succession
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Data from: Rules of thumb for predicting tropical forest recovery
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Data from: Tropical forest restoration enriches vascular epiphyte recovery
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Data from: Litterfall and nutrient dynamics shift in tropical forest restoration sites after a decade of recovery
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Associations between socio-environmental factors and landscape-scale biodiversity recovery in naturally regenerating tropical and subtropical forests
<p class="western"><span><span>Natural regeneration is key for large-scale forest restoration, yet it may lead to different biodiversity outcomes depending on socio-environmental context. We combined the results of a global meta-analysis to quantify how biodiversity recovery in naturally regenerating forests deviates from biodiversity values in reference old-growth forests, with structural equation modeling, to identify direct and indirect associations between socioeconomic, biophysical and ecological factors and deviation in biodiversity recovery at a landscape scale. Low deviation within a landscape means higher chances of multiple sites in naturally regenerating forests successfully recovering biodiversity compared to reference forests. Deviation in biodiversity recovery was directly negatively associated with the percentage of cropland, forest cover, and positively associated with the percentage of urban areas in the surrounding landscape. These three factors mediated the indirect associations with rural population size, recent gross deforestation, time since natural regeneration started, mean annual temperature, mean annual water deficit, road density, land opportunity cost, percentage cover of strictly protected forest areas, and human population variation in the surrounding landscape. We suggest that natural forest restoration should be prioritized in landscapes with both low socioeconomic pressures on land use conversion to pasturelands and urban areas, and high percentage of forest cover.</span></span></p>
Data from: Tropical forest restoration: fast resilience of plant biomass contrasts with slow recovery of stable soil C stocks
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Associations between socio-environmental factors and landscape-scale biodiversity recovery in naturally regenerating tropical and subtropical forests
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Data from: Testing applied nucleation as a strategy to facilitate tropical forest recovery
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Recovery of seedling community attributes during passive restoration of a tropical moist forest in Uganda
<p><strong>Aim: </strong>There has been a debate about the effectiveness of passive restoration for recovering tropical forests, but few studies quantify the success of passive restoration. The aim of this study was to better understand tropical forest succession under a passive restoration scenario. We compared floristic and functional attributes of seedlings in a passively-restored and an old-growth forest, and assessed the effect of restoration age and distance from the old-growth forest on seedling attributes.</p> <p><strong>Location:</strong> Kibale National Park, western Uganda</p> <p><strong>Methods:</strong> We measured seedlings in a passively-restored and an old‐growth forest in 2011, 2014 and 2017. We determined species diversity, structure and composition and searched the literature for functional traits. We used generalized linear mixed-effects models to compare seedling attributes between the restored and old-growth forest and determine the influence of restoration age and distance from the old-growth forest.</p> <p><strong>Results:</strong> Seedling species abundance, evenness, basal area and height were similar between the restored and old-growth forest. Wood density and abundance of seedlings of different dispersal modes, habitat types, fruit size categories, and regeneration strategies were also similar between the restored and old-growth forest. However, richness, diversity and composition of seedlings were different. We found a positive effect of restoration age on species abundance and abundance of non-zoochorous, medium-fruited, forest-dependent, non-pioneer light demander and shade-tolerant species, and a negative effect on evenness, wood density, abundance of pioneers and compositional dissimilarity. Basal area of seedlings and the abundance of zoochorous and forest-dependent species declined while compositional dissimilarity increased with distance from the old-growth forest.</p> <p><strong>Conclusions:</strong> Our results provide empirical evidence on the potential of passive restoration to recover the structure and functionality of tropical forests in a relatively short period of time. We demonstrate that the effect of restoration age and distance from the old-growth forest is not straightforward and depends on the attributes measured.</p>
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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.