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94 results for “vegetation dynamics”
Data and code for "Topography and climate drive recent shifts in vegetation productivity dynamics"
<p>This zip file includes data and code for manuscript "<span><span>Topography and climate drive recent shifts in vegetation productivity dynamics</span></span>".</p>
Data for "Modeling the short-term fire effects on vegetation dynamics and surface energy in southern Africa"
<p>This is the data used for "Modeling the short-term fire effects on vegetation dynamics and surface energy in southern Africa using the improved SSiB4/TRIFFID-Fire model". The data includes two folders: fireon and fireoff representing the scenarios with the fire model turned on and off. Each folder includes 14 years of data from 2000-2013.</p>
Data and Code for the manuscript "Confounding effects of leaf angle dynamics on vegetation indices - implications for monitoring vegetation from space"
<p>This repository includes the data and code to reproduce the results for the study "<em>Confounding effects of leaf angle dynamics on vegetation indices - implications for monitoring vegetation from space</em>". The study shows that leaf angle dynamics systematically confound widely applied vegetation indices. Moreover, it is demonstrated that these effects are not random but tightly linked to abiotic environmental conditions. These findings demonstrate both challenges and opportunities for using VIs for vegetation monitoring.</p>
Spring vegetation dynamics drive sex-specific migration propensity and fine-scale green-up tracking in Alpine ibex
<p># Data and srcipts used to perform analyses presented in the manuscript: "Spring vegetation dynamics drive sex-specific migration propensity and fine-scale green-up tracking in Alpine ibex"</p>
Data for 'Post-disturbance recovery drives 21st century vegetation shifts in the Boreal forest in a dynamic vegetation model'
<p>This is the database containing all the LPJ-GUESS output data used in the paper. For LPJ-GUESS model code, refer to https://zenodo.org/record/8065737. For data processing refer to https://github.com/lucialayr/borealRecovery </p> <p> </p> <p>If you are interested in the raw data, please contact me. </p>
Data from: Dispersal versus environmental filtering in a dynamic system: drivers of vegetation patterns and diversity along stream riparian gradients
1. Both environmental filtering and dispersal filtering are known to influence plant species distribution patterns and biodiversity. Particularly in dynamic habitats, however, it remains unclear whether environmental filtering (stimulated by stressful conditions) or dispersal filtering (during re-colonization events) dominates in community assembly, or how they interact. Such a fundamental understanding of community assembly is critical to the design of biodiversity conservation and restoration strategies. 2. Stream riparian zones are species-rich dynamic habitats. They are characterized by steep hydrological gradients likely to promote environmental filtering, and by spatiotemporal variation in the arrival of propagules likely to promote dispersal filtering. We quantified the contributions of both filters by monitoring natural seed arrival (dispersal filter) and experimentally assessing germination, seedling survival and growth of 17 riparian plant species (environmental filter) along riparian gradients of three lowland streams that were excavated to bare substrate for restoration. Subsequently, we related spatial patterns in each process to species distribution and diversity patterns after 1 and 2 years of succession. 3. Patterns in initial seed arrival were very clearly reflected in species distribution patterns in the developing vegetation and were more significant than environmental filtering. However, environmental filtering intensified towards the wet end of the riparian gradient, particularly through effects of flooding on survival and growth, which strongly affected community diversity and generated a gradient in the vegetation. Strikingly, patterns in seed arrival foreshadowed the gradient that developed in the vegetation; seeds of species with adult optima at wetter conditions dominated seed arrival at low elevations along the riparian gradient while seeds of species with drier optima arrived higher up. Despite previous assertions suggesting a dominance of environmental filtering, our results demonstrate that nonrandom dispersal may be an important driver of early successional riparian vegetation zonation and biodiversity patterns as well. 4. Synthesis: Our results demonstrate (and quantify) the strong roles of both environmental and dispersal filtering in determining plant community assemblies in early successional dynamic habitats. Furthermore, we demonstrate that dispersal filtering can already initiate vegetation gradients, a mechanism that may have been overlooked along many environmental gradients where interspecific interactions are (temporarily) reduced.
Data from: Developing state and transition models of floodplain vegetation dynamics as a tool for conservation decision-making: a case study of the Macquarie Marshes Ramsar wetland
1. Floodplain vegetation states (communities) exhibit spatiotemporal dynamics in vegetation structure and composition, which reflect unique hydrological and connectivity patterns. Shifts in inundation regimes can drive succession and establish new stable states, determined by the magnitude and duration of the hydrological perturbation. 2. We aimed to develop a modelling approach that is able to capture ecosystem dynamics, identify and quantify the main drivers of change, and provide a tool for conservation decision-making. We developed state and transition models for floodplain vegetation states based on surveys in 1991 and 2008 in the Macquarie Marshes (Australia), a Ramsar wetland of international importance. We used a Bayesian logistic regression approach to model state and transitions between vegetation states and investigated how flood frequency, distance to stream and fire frequency were associated with vegetation dynamics during this period. 3. During 1991–2008, significant transitions have occurred towards drier states. Semi-permanent wetland vegetation had the lowest persistence probability (ppsis = 0·456) and a significant threshold response of transitioning to terrestrial vegetation (ptran = 0·505). Transition to drier states was driven by lower inundation probabilities followed by increased fire probability, and distance to nearest stream. 4. Using developed models, we predicted persistence probabilities of vegetation states under an unregulated (i.e. no dams or diversions) and regulated water availability system. Under a regulated system, semi-permanent wetland vegetation had an average persistence of ppsis = 0. 67 and 0·08 in the northern and southern sections of the nature reserve, respectively. Under an unregulated system, the predicted persistence of semi-permanent wetland vegetation was considerably higher: ppsis = 0·87 and 0·38, respectively. 5. Synthesis and applications. Developing quantitative models of state transitions significantly improved our understanding of ecosystem dynamics, identifying sensitive indicators for monitoring and thus supporting conservation decision-making. This helps managers understand potential trajectories of change in ecosystems in response to management options. For example, increasing environmental flows in the Macquarie Marshes is predicted to shift the community towards more of a wetland than the terrestrial state, resulting from river regulation. State and transition models identified how key ecological assets respond to drivers of change, particularly where these can be managed. This is critical for ensuring that all ecosystem components are managed and that these do not shift into undesirable states.
Simulation results for "Modeling the joint effects of vegetation characteristics and soil properties on ecosystem dynamics in a Panama tropical forest"
<p>This dataset is the ELM-FATES simulation outputs for the paper entitled "Modeling the joint effects of vegetation characteristics and soil properties on ecosystem dynamics in a Panama tropical forest". </p>
Effects of habitat types on the dynamic changes of allocation in carbon and nitrogen storage of vegetation-soil system in sandy grasslands
<p>The progressive restoration of degraded vegetation in semiarid and arid desertified areas undoubtedly formed different habitat types. The most plants regulate their growth by fixing carbon with their energy deriving from photosynthesis, carbon (C) and nitrogen (N) play the crucial role in regulating plant growth, community structure and function in the vegetation restoration progress. However, it is still unclear how habitat types affect the dynamic changes of allocation in C and N storage of vegetation-soil system in sandy grasslands. Here, we investigated plant community characteristics and soil properties across three successional stages of habitat types: semi-fixed dunes (SFD), fixed dunes (FD) and grasslands (G) in 2011, 2013 and 2015. We also examined the C and N concentrations of vegetation-soil system, and estimated their C and N storage. The C and N storage of vegetation system, soil and vegetation-soil system remarkably increased from SFD to G. The litter C and N storage in SFD, N storage of vegetation system in SFD and N storage of soil and vegetation-soil system in FD increased from 2011 to 2015, while aboveground plant C and N storage of FD were higher in 2011 than in 2013 and 2015. Most of C and N were sequestered in soil in the vegetation restoration progress. These results suggest that the dynamic changes of allocation in C and N storage in vegetation-soil systems varied with habitat types. Our study highlights that SFD has higher N sequestration rate in vegetation, while FD has the considerably N sequestration rate in the soil.</p>
Tidal channel formation in a rapidly invaded micro-tidal marsh: the role of dynamic vegetation pattern and concurrent channel deepening
<p>The channel formation during the spartina alterniflora invasion influenced by vegetation pattern dynamic and concurrent channel deepening.</p>
The Vegetation Dynamics in Response to Cooling Events from the Medieval Warm Period to the Little Ice Age in Southeast China
<p>Full palynological dataset from three-peats (Wangdongyang peat bog: WDY, 27°40′48″N、119°38′15″E, elevation: 1303 m; Xiyaohu peat bog: XYH15, 28°44′N, 115°40′E, elevation: 735m and XYH14 is close to XYH15; Yuhuashan peat bog: YHS2, 27°50′29″N, 115°38′54.98″E, elevation: 882 m) in the southeast of China.</p> <p>The dataset contains raw counts for pollen and ferns.</p>
Data from: Complex biotic interactions drive long-term vegetation dynamics in a subarctic ecosystem
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Data from: Coupled range dynamics of brood parasites and their hosts responding to climate and vegetation changes
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Effects of habitat types on the dynamic changes of allocation in carbon and nitrogen storage of vegetation-soil system in sandy grasslands
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Data from: Developing state and transition models of floodplain vegetation dynamics as a tool for conservation decision-making: a case study of the Macquarie Marshes Ramsar wetland
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Data from: Middle Jurassic vegetation dynamics based on quantitative analysis of spore/pollen assemblages from the Ravenscar Group, North Yorkshire, UK
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Data from: Dispersal versus environmental filtering in a dynamic system: drivers of vegetation patterns and diversity along stream riparian gradients
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Data from: Functional extinction of a desert rodent: implications for seed fate and vegetation dynamics
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Data from: Diversification dynamics of vegetation during the Cenozoic in the Neotropics: A palynological perspective from Colombia
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Data from: Nitrogen deposition alters plant–fungal relationships: linking belowground dynamics to aboveground vegetation change
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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.