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221 results for “landscape use”
Data from: Decreasing predation rates and shifting predator compositions along a land-use gradient in Madagascar’s vanilla landscapes
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Data from: Surface-water dynamics and land use influence landscape connectivity across a major dryland region
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A systematic review of global road ecology camera trap studies that monitored animals’ use of wildlife crossings in road-fragmented landscapes
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Land use impacts on parasitic infection: A cross-sectional epidemiological study on the role of irrigated agriculture in schistosome infection in a dammed landscape
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Data from: Predicting contemporary range-wide genomic variation using climatic, phylogeographic and morphological knowledge in an ancient, unglaciated landscape
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Spatial reconstruction of the early hepatic transcriptomic landscape after an acetaminophen overdose using single-cell RNA sequencing
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Marginal imprint of human land use upon fire history in a mire-dominated boreal landscape of the Veps Highland, North-West Russia
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Wealth, water and wildlife: landscape aridity intensifies the urban Luxury Effect - data used in meta-analysis
<p>The available Excel file contains all data used in the meta-analysis to analyse the Luxury Effect (i.e. the relationship between urban biodiversity and socioeconomic status) and its moderators (wealth status, species provenance and precipitation). Each column in the data set (tab ‘Data’) is defined as follows:</p> <p><strong>Location</strong>: Location (e.g. city) where a given study took place. If more than one geographical location was considered, they are detailed in the column 'Sample'</p> <p><strong>Sample: </strong>Any separate samples based either on location or temporal sampling period (e.g. geographical location, habitat types, different years) considered in a given paper. If the column is blank, only one location or period was considered.</p> <p><strong>Biodiversity measure: </strong>Defined into either diversity or abundance measures as defined in the text.</p> <p><strong>Response variable: </strong>The precise response variable analysed in the paper.</p> <p><strong>Socioeconomic variable: </strong>The socioeconomic variable analysed in the paper.</p> <p><strong>Provenance: </strong>Native or exotic species, where specified. 'All' refers both to papers where it was explicitly stated that both native and exotic species were considered, and those where no information was given, but we assumed that native and exotic species had been considered.</p> <p><strong>Development status: </strong>Countries with developed economies ('Rich') and countries with developing economies 'Poor') as defined in the text.</p> <p><strong>Gradient length: </strong>Studies including only urbanized areas ('Short') and those also including rural sampling locations ('Long').</p> <p><strong>Precipitation: </strong>in mm.</p> <p><strong>Pearson's r: </strong>Standardized values used in the meta-analysis.</p> <p> </p> <p>Note the above information is also available in the Excel file in the ‘Notes’ tab. </p> <p> </p>
Data from: An environmental impact assessment of different management regimes in eucalypt plantations in southern China using Landscape Function Analysis
<p>There are global concerns regarding the detrimental environmental impacts of industrial forest plantations developed over the past 30 years. To address this concern, the Landscape Function Analysis methodology was used to rapidly assess indices of soil stability, water infiltration, and nutrient cycling within eucalypt plantations at different growth stages and under different management regimes in Guangxi Province, China. Results showed that these plantations under both regimes were approaching an ecologically functional state by the time of harvest. However, within the plantation management that included the burning of post-harvest biomass residues, indices of water infiltration, and nutrient cycling were significantly lower than within the plantation that retained post-harvest residues. Indicators of rain splash protection, perennial vegetation cover, and litter accumulation were all lower in the plantation that practiced residue burning and pre-planting cultivation. Retention of post-harvest residues improves landscape functionality at the time of re-planting. Our results indicate that burning and extensive cultivation prior to re-planting should be minimized.</p>
Data from: Climate change and landscape-use patterns influence recent past distribution of giant pandas
<p>Climate change is one of the most pervasive threats to biodiversity globally, yet the influence of climate relative to other drivers of species depletion and range contraction remain difficult to disentangle. Here, we examine climatic and non-climatic correlates of giant panda (<i>Ailuropoda melanoleuca</i>) distribution using a large-scale 30-year dataset to evaluate whether a changing climate has already influenced panda distribution. We document several climatic patterns, including increasing temperatures, and alterations to seasonal temperature and precipitation. We found that while climatic factors were the most influential predictors of panda distribution, their importance diminished over time, while landscape variables have become relatively more influential. We conclude that the panda's distribution has been influenced by changing climate, but conservation intervention to manage habitat is working to increasingly offset these negative consequences.</p>
Data from:Identification of landscape features influencing gene flow: how useful are habitat selection models?
Understanding how dispersal patterns are influenced by landscape heterogeneity is critical for modelling species connectivity. Resource selection function (RSF) models are increasingly used in landscape genetics approaches. However, because the ecological factors that drive habitat selection may be different from those influencing dispersal and gene flow, it is important to consider their explicit assumptions. We calculated pairwise genetic distances among 301 Alaskan Dall's sheep (Ovis dalli dalli) using an intensive sampling effort and 15 microsatellite loci. We used multiple regression of distance matrices to assess the correlation of pairwise genetic distance and landscape resistance derived from an RSF, and combinations of landscape features hypothesized to influence dispersal. Dall's sheep gene flow was positively correlated with steep slopes, moderate peak normalized difference vegetation indices (NDVI), and open land cover. Whereas RSF covariates were significant in predicting genetic distance, the RSF model itself was not significantly correlated with Dall's sheep gene flow, suggesting that certain habitat features important seasonally (rugged terrain, mid-range elevation) were not influential to breeding dispersal. This work underscores that consideration of both habitat selection and landscape genetics models in developing conservation strategies will ensure resources are managed to meet both the immediate survival needs of a species and allow for long-term genetic connectivity.
Data from: Mechanistic insights into landscape genetic structure of two tropical amphibians using field-derived resistance surfaces
Conversion of forests to agriculture often fragments distributions of forest species and can disrupt gene flow. We examined effects of prevalent land uses on genetic connectivity of two amphibian species in northeastern Costa Rica. We incorporated data from field surveys and experiments to develop resistance surfaces that represent local mechanisms hypothesized to modify dispersal success of amphibians, such as habitat-specific predation and desiccation risk. Because time lags can exist between forest conversion and genetic responses, we evaluated landscape effects using land-cover data from different time periods. Populations of both species were structured at similar spatial scales but exhibited differing responses to landscape features. Litter frog population differentiation was significantly related to landscape resistances estimated from abundance and experiment data. Model support was highest for experiment-derived surfaces that represented responses to microclimate variation. Litter frog genetic variation was best explained by contemporary landscape configuration, indicating rapid population response to land-use change. Poison frog genetic structure was strongly associated with geographic isolation, which explained up to 45% of genetic variation, and long-standing barriers, such as rivers and mountains. However, there was also partial support for abundance and microclimate response derived resistances. Differences in species responses to landscape features may be explained by overriding effects of population size on patterns of differentiation for poison frogs, but not litter frogs. In addition, pastures are likely semi-permeable to poison frog gene flow because the species is known to use pastures when remnant vegetation is present, but litter frogs do not. Ongoing reforestation efforts will likely increase connectivity in the region by increasing tree cover and reducing area of pastures.
Data from: Using simulations to evaluate Mantel-based methods for assessing landscape resistance to gene flow
Mantel-based tests have been the primary analytical methods for understanding how landscape features influence observed spatial genetic structure. Simulation studies examining Mantel-based approaches have highlighted major challenges associated with the use of such tests and fueled debate on when the Mantel test is appropriate for landscape genetics studies. We aim to provide some clarity in this debate using spatially explicit, individual-based, genetic simulations to examine the effects of the following on the performance of Mantel-based methods: (1) landscape configuration, (2) spatial genetic nonequilibrium, (3) nonlinear relationships between genetic and cost distances, and (4) correlation among cost distances derived from competing resistance models. Under most conditions, Mantel-based methods performed poorly. Causal modeling identified the true model only 22% of the time. Using relative support and simple Mantel r values boosted performance to approximately 50%. Across all methods, performance increased when landscapes were more fragmented, spatial genetic equilibrium was reached, and the relationship between cost distance and genetic distance was linearized. Performance depended on cost distance correlations among resistance models rather than cell-wise resistance correlations. Given these results, we suggest that the use of Mantel tests with linearized relationships is appropriate for discriminating among resistance models that have cost distance correlations <0.85 with each other for causal modeling, or <0.95 for relative support or simple Mantel r. Because most alternative parameterizations of resistance for the same landscape variable will result in highly correlated cost distances, the use of Mantel test-based methods to fine-tune resistance values will often not be effective.
Data from: Prioritizing land management efforts at a landscape scale: a case study using prescribed fire in Wisconsin
One challenge in the effort to conserve biodiversity is identifying where to prioritize resources for active land management. Cost-benefit analyses have been used successfully as a conservation tool to identify sites that provide the greatest conservation benefit per unit cost. Our goal was to apply cost-benefit analysis to the question of how to prioritize land management efforts, in our case the application of prescribed fire to natural landscapes in Wisconsin, USA. We quantified and mapped frequently burned communities, and prioritized management units based on a suite of indices that captured ecological benefits, management effort, and the feasibility of successful long-term management actions. Data for these indices came from LANDFIRE, Wisconsin's Wildlife Action Plan, and a nationwide Wildland Urban Interface assessment. We found that the majority of frequently burned vegetation types occurred in the southern portion of the state. However, the highest-priority areas for applying prescribed fire occurred in the central, northwest, and northeast portion of the state where frequently burned vegetation patches were larger and where identified areas of high biological importance area occurred. Although our focus was on the use of prescribed fire in Wisconsin, our methods can be adapted to prioritize other land management activities. Such prioritization is necessary to achieve the greatest possible benefits from limited funding for land management actions, and our results show that it is feasible at scales that are relevant for land management decisions.
Data from: Host use dynamics in a heterogeneous fitness landscape generates oscillations in host range and diversification
Colonization of novel hosts is thought to play an important role in parasite diversification, yet little consensus has been achieved about the macroevolutionary consequences of changes in host use. Here we offer a mechanistic basis for the origins of parasite diversity by simulating lineages evolved in silico. We describe an individual-based model in which (i) parasites undergo sexual reproduction limited by genetic proximity, (ii) hosts are uniformly distributed along a one-dimensional resource gradient, and (iii) host use is determined by the interaction between the phenotype of the parasite and a heterogeneous fitness landscape. We found two main effects of host use on the evolution of a parasite lineage. First, the colonization of a novel host allowed parasites to explore new areas of the resource space, increasing phenotypic and genotypic variation. Second, hosts produced heterogeneity in the parasite fitness landscape, which led to reproductive isolation and therefore, speciation. As a validation of the model, we analyzed empirical data from Nymphalidae butterflies and their host plants. We then assessed the number of hosts used by parasite lineages and the diversity of resources they encompass. In both simulated and empirical systems, host diversity emerged as the main predictor of parasite species richness.
Data from: Current approaches using genetic distances produce poor estimates of landscape resistance to interindividual dispersal
Landscape resistance reflects how difficult it is for genes to move across an area with particular attributes (e.g., land cover, slope). An increasingly popular approach to estimate resistance uses Mantel and partial Mantel tests or causal modeling to relate observed genetic distances to effective distances under alternative sets of resistance parameters. Relatively few alternative sets of resistance parameters are tested, leading to relatively poor coverage of the parameter space. Although this approach does not explicitly model key stochastic processes of gene flow, including mating, dispersal, drift, and inheritance, bias and precision of the resulting resistance parameters have not been assessed. We formally describe the most commonly used model as a set of equations and provide a formal approach for estimating resistance parameters. Our optimization finds the maximum Mantel r when an optimum exists, and identifies the same resistance values as current approaches when the alternatives evaluated are near the optimum. Unfortunately, even where an optimum existed, estimates from the most commonly used model were imprecise and were typically much smaller than the simulated true resistance to dispersal. Causal modeling using Mantel significance tests also typically failed to support the true resistance to dispersal values. For a large range of scenarios, current approaches using a simple correlational model between genetic and effective distances do not yield accurate estimates of resistance to dispersal. We suggest that analysts consider the processes important to gene flow for their study species, model those processes explicitly, and evaluate the quality of estimates resulting from their model.
PEDAGOGICAL REQUIREMENTS OF TEACHING STUDENTS TO USE LANDSCAPE COMPOSITION IN PAINTING
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Exploring Conformational Landscapes and Binding Mechanisms of Convergent Evolition for the SARS-CoV-2 Spike Omicron Variant Complexes with the ACE2 Receptor Using AlphaFold2-Based Structural Ensembles and Molecular Dynamics Simulations
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Supplementary Materials for "Landscape-aware Automated Algorithm Configuration using Multi-Output Mixed Regression and Classification"
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Data from: Seasonal progression and differences in major floral resource use by bees and hoverflies in a diverse horticultural and agricultural landscape revealed by DNA metabarcoding
<p>Gardens are important habitats for pollinators, providing floral resources and nesting sites. There are high levels of public support for growing 'pollinator-friendly' plants but whilst plant recommendation lists are available, they are usually inconsistent, poorly supported by scientific research and target a narrow group of pollinators. In order to supply the most appropriate resources, there is a clear need to understand foraging preferences, for a range of pollinators, across the season within horticultural landscapes.</p> <p>Using an innovative DNA metabarcoding approach, we investigated foraging preferences of four groups of pollinators in a large and diverse, horticultural, and agricultural landscape, across the flowering season and over two years, significantly improving on the spatial and temporal scale that can be achieved using observational studies.</p> <p>Bumblebees, honeybees, non-corbiculate bees, and hoverflies visited 191 plant taxa. Overall floral resources were shared between the different types of pollinators, but significant differences were seen between the plants used most abundantly by bees (Hymenoptera) and hoverflies (Diptera).</p> <p>Floral resource use by pollinators is strongly associated with seasonal changes in flowering plants, with pollinators relying on dominant plants found within each season, with preferences consistent across both years.</p> <p>The plants identified were categorised according to their native status to investigate the value of native and non-native plants. The majority of floral resources used were of native and near-native origin, but the proportion of horticultural and naturalised plants increased during late summer and autumn.</p> <p><em>Synthesis and applications: </em>We recommend that plant lists should distinguish between bees and hoverflies and provide evidence-based floral recommendations throughout the year that include native as well as non-native plants for use in the UK and Northern Europe. Specific management recommendations include reducing mowing to encourage plants such as dandelion <em>Taraxacum officinale</em>, buttercups <em>Ranunculus spp.</em>, and reducing scrub management to encourage bramble <em>Rubus fruticosus</em>.</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.