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67 results for “landscape-scale”
Landscape-Scale Forest Dynamics in the Luquillo Experimental Forest in Puerto Rico 1936-1989
This study examined landscape-scale forest dynamics in the Luquillo Experimental Forest (Puerto Rico). The analysis was based on vegetation maps created from aerial photographs taken in 1936 and 1989. For details on methods and results, please see the published paper (Foster, D. R., M. Fluet and E. R. Boose. 1999. Human or natural disturbance: landscape-scale dynamics of the tropical forests of Puerto Rico. Ecological Applications 9: 555-572). The Abstract from the paper is reproduced below. "Increasingly ecologists are recognizing that human disturbance has played an important role in tropical forest history and that many assumptions concerning the relative importance of natural processes warrant re-examination. To assess the historical role of broad-scale human versus natural disturbance on an intensively studied tropical forest we undertook a landscape-level analysis of forest dynamics in the Luquillo Experimental Forest (LEF; 10,871 ha) in eastern Puerto Rico. Using aerial photographs (1936 and 1989), GIS, a model of topographic exposure to hurricane winds, and historical data, we sought to: (1) document historical changes in extent, cover and type of forest vegetation, (2) evaluate the distribution of land-use and hurricane impacts, (3) assess the contributions of these processes in controlling current vegetation patterns, and (4) relate these results to ongoing ecological, conservation and natural resource discussions. "With over 1000 m of relief in the LEF, the broad vegetation zones of Tabonuco (below 600 m a.s.l.), Colorado (600-900 m), Dwarf (above 900 m), and Palm forest are determined by environmental gradients. However, over the past 60-100 years forest extent, cover, and type have been transformed: in 1936, 40% of the LEF was unforested or secondary forest and less than 50% had continuous canopy (more than 80% cover); in 1989, less than 97% was continuous forest. Secondary forest and agricultural lands in 1936 were replaced largely by Tabonuco and Colo
MCR LTER: Coral Reef: Landscape-scale patterns of nutrient enrichment in a coral reef ecosystem: implications for coral to algae phase shifts, Adam et al., Ecol. Appl.
These data and analyses code were generated in support of the manuscript: Adam TC, Burkepile DE, Holbrook SJ, Carpenter RC, Claudet J, Loiseau C, Thiault L, Brooks, AJ, Washburn L, and RJ Schmitt, Ecological Applications We investigated the potential role of anthropogenic nutrient loading in driving recent coral-to-macroalgae phase shifts on reefs in the lagoons surrounding Moorea, French Polynesia. We used nitrogen (N) tissue content and stable isotopes (δ15N) in an abundant macroalga (Turbinaria ornata) together with empirical models of nutrient discharge to describe spatial and temporal patterns of nutrient enrichment in the lagoons. Turbinaria ornata were collected at 190 sites around Moorea in January, May, and August 2016. These sampling periods corresponded with distinct seasonal shifts in rainfall and wave forcing. Our results revealed that patterns of N enrichment were linked to rainfall, wave-driven circulation, and distance from anthropogenic nutrient sources, especially human sewage. In addition to describing high resolution patterns of N enrichment from 2016, we also analyzed core MCR time series on N tissue content in Turbinaria ornata from three habitats (fringing reef, back reef, and reef crest) at the six core MCR LTER sites between 2007 and 2013. These data showed that fringing reefs have been consistently enriched in N relative to back reefs, which are enriched relative to the reef crest. Further, these patterns mirror long-term patterns of nitrate and nitrite concentrations in the water column. We also analyzed core MCR time series on benthic communities and fishes and found that back reef sites that were consistently enriched in N between 2007 and 2013 experienced large increases in macroalgae while macroalgae remained much less abundant at back reef sites with lower N. These phase shifts to macroalgae occurred despite island-wide increases in the density and biomass of herbivorous fishes over the time period. Together, these results indicate th
Virgin Islands National Park: Coral Reef: Population Dynamics: Landscape-scale Variation in Scleractinian Corals
This study provides a landscape-scale context to a decadal-scale analysis of community structure on shallow reefs along 4 km of the south shore of St. John, US Virgin Islands. By focusing on 12-14 sites along ~100 km of the shores of St. John and St. Thomas, surveys conducted in 2011 were used to contrast: (1) a local-scale with a landscape-scale analysis on two islands, (2) reefs around St. John and St. Thomas, and (3) reefs on north and south shores. Reefs were censused using photoquadrats that were analyzed for percentage cover first by functional groups (coral, macraolagae and CTB), and then by coral genus. In general, among-site variation for the coarse-resolution analysis eclipsed shore and island effects, but the fine-resolution analysis revealed strong site-specific differences for multiple coral genera that could be the product of priority effects in community succession. Over the next decade these differences probably will create unique community trajectories at each site.
Data from: Mean landscape-scale incidence of species in discrete habitats is patch size dependent
<p>Contains data and code for the manuscript 'Mean landscape-scale incidence of species in discrete habitats is patch size dependent'.</p> <p>Raw data consist of 202 published datasets collated from primary and secondary (e.g., government technical reports) sources. These sources summarise metacommunity structure for different taxonomic groups (birds, invertebrates, non-avian vertebrates or plants) in different types of discrete metacommunities including 'true' islands (i.e., inland, continental or oceanic archipelagos), habitat islands (e.g., ponds, wetlands, sky islands) and fragments (e.g., forest/woodland or grass/shrubland habitat remnants). </p> <p>The aim of the study was to test whether the size of a habitat patch influences the mean incidences of species within it, relative to the incidence of all species across the landscape. In other words, whether high-incidence (widespread) or low-incidence (narrow-range) species are found more often than expected in smaller or larger patches. To achieve this, a new standardized effect size metric was developed that quantifies the mean observed incidence of all species present in every patch (the geometric mean of the number of patches in which all species were observed) and compares this with an expectation based on re-sampling the incidences of all species in all patches. Meta-regression of the 202 datasets was used to test the relationship between this metric, the 'mean species landscape-scale incidences per patch' (MSLIP), and the size of habitat patches, and for differences in response among metacommunity types and taxonomic groups. </p>
Number of chamber measurement locations for accurate quantification of landscape-scale greenhouse gas fluxes: Importance of land use, seasonality, and greenhouse gas type
<p>Contains all raw data measured in the Schwingbach Earth Observatory (SEO) from Spring, Summer and Autumn 2020. Data was measured with an on-site LGR laser from the GHG emissions, and with 100cm³ soil cores for the soil characteristics. Details can be found in the corresponding manuscript "Number of chamber measurement locations for accurate quantification of landscape-scale greenhouse gas fluxes: Importance of land use, seasonality, and greenhouse gas type"</p>
Data and R code from: Spatiotemporal risk factors predict landscape-scale survivorship for a northern ungulate
<p>These data and computer code (written in R, https://www.r-project.org) were created to statistically evaluate a suite of spatiotemporal covariates that could potentially explain pronghorn (Antilocapra americana) mortality risk in the Northern Sagebrush Steppe (NSS) ecosystem (50.0757<sup>o</sup> N, −108.7526<sup>o</sup> W). Known-fate data were collected from 170 adult female pronghorn monitored with GPS collars from 2003-2011, which were used to construct a time-to-event (TTE) dataset with a daily timescale and an annual recurrent origin of 11 November. Seasonal risk periods (winter, spring, summer, autumn) were defined by median migration dates of collared pronghorn. We linked this TTE dataset with spatiotemporal covariates that were extracted and collated from pronghorn seasonal activity areas (estimated using 95% minimum convex polygons) to form a final dataset. Specifically, average fence and road densities (km/km2), average snow water equivalent (SWE; kg/m2), and maximum decadal normalized difference vegetation index (NDVI) were considered as predictors. We tested for these main effects of spatiotemporal risk covariates as well as the hypotheses that pronghorn mortality risk from roads or fences could be intensified during severe winter weather (i.e., interactions: SWE*road density and SWE*fence density). We also compare an analogous frequentist implementation to estimate model-averaged risk coefficients. Ultimately, the study aimed to develop the first broad-scale, spatially explicit map of predicted annual pronghorn survivorship based on anthropogenic features and environmental gradients to identify areas for conservation and habitat restoration efforts.</p> <p> </p>
Fig. 1 in Co-occurrence of two sympatric galliform species on a landscape-scale
Fig. 1. Map of Cat Tien NP with five survey transects each in bamboo, mixed deciduous, and mosaic forests, and seven transects in evergreen forest.
Data from: Fecal biomarkers in soils record landscape-scale wild herbivore abundance
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Data from: Mean landscape-scale incidence of species in discrete habitats is patch size dependent
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Wild pollinators and honeybees respond differently to landscape-scale organic farming and increase sunflower yields
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Integrating presence-only and detection/non-detection data to estimate distributions and expected abundance of difficult-to-monitor species on a landscape-scale
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Data and R code from: Spatiotemporal risk factors predict landscape-scale survivorship for a northern ungulate
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Pino Gate Prairie Dog Study: Landscape-scale Vegetation Plot Data from the Sevilleta National Wildlife Refuge, New Mexico (1999-2002)
Prairie dogs (Cynomys spp.) and banner-tailed kangaroo rats (Dipodomys spectabilis) are considered keystone species of grassland ecosystems, and co-occur in the arid grasslands of the southwestern United States and in Mexico. Their keystone status is attributed primarily to the effects of their burrowing and foraging behavior, but they differ ecologically in several important respects. We studied the comparative functional roles of these species where they co-occur at the Sevilleta National Wildlife Refuge, New Mexico, focusing on their impacts on grassland vegetation. We found that vegetation cover, structure, and species richness varied across a gradient extending out from the mound centers, and these patterns differed between prairie dog and kangaroo rat mounds. Certain species and functional groups of plants associated differentially with mounds and landscape patches occupied by prairie dogs and banner-tailed kangaroo rats. Where both species co-occurred locally there was greater soil disturbance, more organic material from their feces, and higher activity of other animals. The overall effect of these rodents was to create a mosaic of different patches across the landscape such that their combined activities increased andscape heterogeneity and plant species richness. Our results demonstrate complementary effects of two co-occurring keystone species on their associated biotic communities.
Pino Gate Prairie Dog Study: Landscape-scale Ground-Dwelling Arthropod Plot Data from the Sevilleta National Wildlife Refuge, New Mexico (2000-2001)
Keystone species have large impacts on community and ecosystem properties, and create important ecological interactions with other species. Prairie dogs (Cynomys spp.), and banner-tailed kangaroo rats (Dipodomys spectabilis) are considered keystone species of grassland ecosystems, and create a mosaic of unique habitats on the landscape. These habitats are known to attract a number of animal species, but little is known about how they affect arthropod communities. Our research evaluated the keystone roles of prairie dogs and kangaroo rats on arthropods at the Sevilleta National Wildlife Refuge in central New Mexico, USA. We evaluated the impacts of these rodents on ground-dwelling arthropod and grasshopper communities in areas where prairie dogs and kangaroo rats co-occurred compared to areas where each rodent species occurred alone. Our results demonstrate that prairie dogs and kangaroo rats have keystone-level impacts on these arthropod communities. Their burrow systems provided important habitats for multiple trophic and taxonomic groups of arthropods, and increased overall arthropod abundance and species richness on the landscape. Many arthropods also were attracted to the aboveground habitats around the mounds and across the landscapes where the rodents occurred. Detritivores, predators, ants, grasshoppers, and rare rodent burrow inhabitants showed the strongest responses to prairie dog and kangaroo rat activity. The impacts of prairie dogs and kangaroo rats were unique, and the habitats they created supported different assemblages of arthropods. Where both rodent species occurred together on the landscape, there was great habitat heterogeneity and increased arthropod diversity.
Pino Gate Prairie Dog Study: Landscape-scale Grasshopper Plot Data from the Sevilleta National Wildlife Refuge, New Mexico (2000-2002)
Keystone species have large impacts on community and ecosystem properties, and create important ecological interactions with other species. Prairie dogs (Cynomys spp.) and banner-tailed kangaroo rats (Dipodomys spectabilis) are considered keystone species of grassland ecosystems, and create a mosaic of unique habitats on the landscape. These habitats are known to attract a number of animal species, but little is known about how they affect arthropod communities. Our research evaluated the keystone roles of prairie dogs and kangaroo rats on arthropods at the Sevilleta National Wildlife Refuge in central New Mexico, USA. We evaluated the impacts of these rodents on ground-dwelling arthropod and grasshopper communities in areas where prairie dogs and kangaroo rats co-occurred compared to areas where each rodent species occurred alone. Our results demonstrate that prairie dogs and kangaroo rats have keystone-level impacts on these arthropod communities. Their burrow systems provided important habitats for multiple trophic and taxonomic groups of arthropods, and increased overall arthropod abundance and species richness on the landscape. any arthropods also were attracted to the aboveground habitats around the mounds and across the landscapes where the rodents occurred. Detritivores, predators, ants, grasshoppers, and rare rodent burrow inhabitants showed the strongest responses to prairie dog and kangaroo rat activity. The impacts of prairie dogs and kangaroo rats were unique, and the habitats they created supported different assemblages of arthropods. Where both rodent species occurred together on the landscape, there was greater habitat heterogeneity and increased arthropod diversity.
Improving landscape-scale productivity estimates by integrating trait-based models and remotely-sensed foliar-trait and canopy-structural data
Assessing the impacts of anthropogenic degradation and climate change on global carbon cycling is hindered by a lack of clear, flexible, and easy-to-use productivity models along with scarce trait and productivity data for parameterizing and testing those models. We provide a simple solution: a mechanistic framework (RS-CFM) that combines remotely-sensed foliar-trait and canopy-structural data with trait-based metabolic theory to efficiently map productivity at large spatial scales. We test this framework by quantifying net primary productivity (NPP) at high-resolution (0.01-ha) in hyper-diverse Peruvian tropical forests (30,040 hectares) along a 3,322-m elevation gradient. Our analysis captures hotspots and elevational shifts in productivity more accurately and in greater detail than alternative empirical- and process-based models that use plant functional types. This result exposes how high-resolution, location-specific variation in traits and light competition drive variability in productivity, opening up possibilities to fully harness remote sensing data and reliably scale up from traits to map global productivity in a more direct, efficient, and cost-effective manner.
Landscape-scale drivers of liana load across a Southeast Asian forest canopy differ to the Neotropics
<p><span>Lianas (woody vines) are a key component of tropical forests, known to reduce forest carbon storage and sequestration and to be increasing in abundance. Analysing how and why lianas are distributed in forest canopies at landscape scales will help us determine the mechanisms driving changes in lianas over time. This will improve our understanding of liana ecology and projections of tropical forest carbon storage now and into the future. Despite competing hypotheses on the mechanisms driving spatial patterning of lianas, few studies have integrated multiple tree-level biotic and abiotic factors in an analytical framework. None have done so in the Palaeotropics, which are biogeographically and evolutionarily distinct from the Neotropics, where most research on lianas has been conducted.</span></p> <p><span>We used an unoccupied aerial system (UAS; drone) to assess liana load in 50-ha of Palaeotropical forest canopy in Southeast Asia. We obtained data on hypothesised drivers of liana spatial distribution in the forest canopy, including disturbance, tree characteristics, soil chemistry, and topography, from the UAS, from airborne LiDAR, and from ground surveys. We integrated these in a comprehensive analytical framework to extract variables at an individual-tree level and evaluated the relative strengths of the hypothesised drivers and their ability to predict liana distributions through boosted regression tree (BRT) modeling.</span></p> <p><span>Tree height and distance to canopy gaps were the two most important predictors of liana load, with relative contribution values in BRT models of 34.60% 45.39% and 7.93% - 10.19%, respectively. Our results suggest that taller trees were less often and less heavily infested by lianas than shorter trees, opposite to Neotropical findings. Lianas also occurred more often, and to a greater extent, in tree crowns close to canopy gaps and to neighbouring trees with lianas in their crown</span><span>. </span></p> <p><span><strong>Synthesis</strong>: Despite their known importance and prevalence in tropical forests, lianas are not well understood, particularly in the Palaeotropics. Examining 2,428 trees across 50-ha of Palaeotropical forest canopy in Southeast Asia, we find support for the hypothesis that canopy gaps promote liana infestation. Our finding that liana presence and load declined with tree height, opposite to well-established Neotropical findings, suggests a fundamental difference between Neotropical and Southeast Asian forests. Considering that most liana literature has focused on the Neotropics, this highlights the need for additional studies in other biogeographic regions to clarify potential differences and enable us to better understand liana impacts on tropical forest ecology, carbon storage and sequestration.</span></p>
Landscape-scale conservation mitigates the biodiversity loss of grassland birds
<p>The decline of biodiversity from anthropogenic landscape modification is among the most pressing conservation problems world-wide. In North America, long-term population declines have elevated the recovery of the grassland avifauna to among the highest conservation priorities. Because the vast majority of grasslands of the Great Plains are privately owned, the recovery of these ecosystems and bird populations within them depend on landscape-scale conservation strategies that integrate social, economic, and biodiversity objectives. The Conservation Reserve Program (CRP) is a voluntary program for private agricultural producers administered by the United States Department of Agriculture that provides financial incentives to take cropland out of production and restore perennial grassland. We investigated spatial patterns of grassland availability and restoration to inform landscape-scale conservation for a comprehensive community of grassland birds in the Great Plains. The research objectives were to 1) determine how apparent habitat loss has affected spatial patterns of grassland bird biodiversity, 2) evaluate the effectiveness of CRP for offsetting the biodiversity declines of grassland birds and 3) develop spatially explicit predictions to estimate the biodiversity benefit of adding CRP to landscapes impacted by habitat loss. We used the Integrated Monitoring in Bird Conservation Regions program to evaluate hypotheses for the effects of habitat loss and restoration on both the occupancy and species richness of grassland specialists within a continuum modelling framework. We found the odds of community occupancy declined by 37% for every 1 Standard Deviation (SD) decrease in grassland availability [log<i><sub>e</sub></i>(km<sup>2</sup>)] and increased by 20% for every 1 SD increase in CRP land cover [log<i><sub>e</sub></i>(km<sup>2</sup>)]. There was 17% turnover in species composition between intact grasslands and CRP landscapes, suggesting grasslands restored by CRP retained considerable, but incomplete representation of biodiversity in agricultural landscapes. Spatially explicit predictions indicated absolute conservation outcomes were greatest at high latitudes in regions with high biodiversity, whereas the relative outcomes were greater at low latitudes in highly modified landscapes. By evaluating community-wide responses to landscape modification and CRP restoration at bioregional scales, our study fills key information gaps for developing collaborative strategies, and balancing conservation of avian biodiversity and social well-being in agricultural production landscapes of the Great Plains.</p>
Two decades of annual landscape-scale tree growth and dynamics in old-growth tropical rainforest in the CARBONO Project, La Selva Biological Station, 1997-2018
<p>Here we present the complete data series from a 21-yr study of the annual growth and dynamics of trees, palms and lianas in the old-growth tropical rainforest at the La Selva Biological Station in Costa Rica. These observations were part of the CARBONO Project, a multidisciplinary team study of forest carbon cycling. The project was designed to assess forest processes at the landscape scale by sampling with replication across the within-landscape edaphic heterogeneity typical of tropical forests. Through more than two decades, forest growth and dynamics were assessed annually. The annual time-step used in the CARBONO Project effectively captured forest responses to major disturbances and to interannual and climatic variation. Annual measurements also enhanced the accuracy and long-term consistency of the data. To our knowledge, the resulting records are unique for tropical forests, where the dominant approach to studying the dynamics of a given forest has been to use a single plot and multi-year inter-census intervals. To date these CARBONO Project data have revealed: multi-decadal forest stability in spite of the short-term changes in forest structure resulting from major natural disturbances (e.g., the 1997-1998 Strong El Niño, and the extreme windstorm of May 2018); the dynamics and importance of large trees; and the responses of a major component of ecosystem productivity, aboveground wood production, to interannual and long-term climatic and atmospheric change. These data have also contributed to many remote-sensing studies.</p> <p>The data set consists of annual observations through the period 1997–2018 of the floristics, survival, recruitment, and growth of all woody stems (diameter <u>></u> 10 cm) in a landscape-scale plot network. At completion of the study, the data spanned 6705 individuals and 21 years. The data set is complete and has been through extensive internal checks for quality assurance. Detailed data documentation and an emphasis on measurement repeatability were prioritized through the study. The metadata include an extensive README file describing the data files and the methods, a document detailing the data management and qa/qc, and the scanned original field data-sheets for the 22 annual censuses.</p> <p>We gratefully acknowledge the careful long-term field work and data entry and checking by paraforesters Leonel Campos Otoya and William Miranda Conejo. Logistical support and the long-term protection of the La Selva reserve were provided by the Organization for Tropical Studies. The Ministerio de Ambiente y Energía of Costa Rica granted permits to carry out this study through the years of the study (most recently: Resolución No. 037-2018-ACCVC-PI).</p>
Landscape-scale dynamics of a threatened species respond to local-scale conservation management
<p><span>Landscape-scale approaches are increasingly advocated for species conservation but ensuring landscape level persistence by enlarging the size of patches or increasing their physical connectivity is often impractical. Here, we test how such barriers can be overcome by management of habitat at the local (site-based) level, using a rare butterfly as an exemplar. We used four surveys of the entire UK distribution of the Lulworth Skipper (<em>Thymelicus</em> <em>acteon</em>) over 40 years to test how local habitat influences population density and colonization / extinction dynamics, and parameterized, validated and applied a metapopulation model to simulate effects of varying local habitat quality on regional persistence. We found the total number of populations in four distribution snapshots between 1978 and 2017 varied between 59–84, and from 1997 to 2017, 34% of local populations showed turnover (colonization or extinction). Population density was closely linked to vegetation characteristics indicative of management, namely height and food plant frequency, both of which changed through time. Simulating effects of habitat quality on metapopulation dynamics 40 years into the future suggests coordinated changes to two key components of quality (vegetation height and food plant frequency) would increase patch occupancy above the range observed in the past 40 years (50–80%). In contrast, deterioration of either component below threshold levels leads to metapopulation retraction to core sub-networks of patches, or eventual extirpation. Our results indicate that changes to habitat quality can overcome constraints imposed by habitat patch area and spatial location on relative rates of colonization and local extinction, demonstrating the sensitivity of regional dynamics to targeted in situ management. Local habitat management therefore plays a key role in landscape-scale conservation. Monitoring of population density, and the monitoring and management of local (site-level) habitat quality, therefore represent effective and important components of conservation strategies in fragmented landscapes.</span></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.