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259 results for “landscape scale”
Disentangling direct and indirect drivers of farmland biodiversity at landscape scale
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The effects of land-use history and the contemporary landscape on non-native plant invasion at local and regional scales in the French Broad Watersheds, 2007
Determining what factors explain the distribution of non-native invasive plants that can spread in forest-dominated landscapes could advance understanding of the invasion process and identify forest areas most susceptible to invasion. The researchers conducted roadside surveys to determine the presence and abundance of 15 non-native plant species known to invade forests in western North Carolina, USA. Prior to sampling, the researchers identified 15 non-native invasive plant species that were of concern in the study region. Generalized linear models were used to examine how contemporary and historic land use, landscape context, and topography influenced presence and abundance of the species at local and regional scales.
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.
Data for: Landscape scale variation in the hydrologic niche of California coast redwood
<p>Topoclimatic diversity within forest landscapes can underlie variation in water availability, which may correspond to patterns in habitat suitability of tree species with differing hydrologic niches. However, the trade-off between the collection of data at a fine grain size over large spatial extents has limited comprehensive analyses of landscape scale variation in habitat suitability. We present a fine scale analysis of the roles of topographic gradients in moisture availability, soil water storage, and fog frequency in the spatial pattern of habitat suitability for coast redwood (<i>Sequoia sempervirens</i>), at 10 m resolution across 34,800 hectares and three landscapes spanning approximately one-third of redwood's latitudinal range. A new 10 m resolution presence-absence map derived from airborne imaging spectroscopy was used to characterize current redwood distributions in three landscapes. Access to belowground moisture was assessed through four measures calculated from a high-resolution LiDAR digital elevation model, soil water storage was mapped from the USDA Soil Survey Geographic Database, and fog frequency was calculated from MODIS cloud cover data. Access to belowground moisture and fog predicted variation in suitability as redwood habitat from 22–75% and predicted redwood presence and absence at 10 m resolution with 63–74% accuracy. Across all three landscapes, redwood density consistently decreased with increasing interpolated height above a stream (IHAS), but the role of other predictors varied among the sites. Our results challenge previous assumptions that redwood habitat suitability within much coarser resolutions (800 m x 800 m) can be described by a single value. The elevated habitat suitability of sites close to streams suggests that these sites should be evaluated for their potential to become microrefugia within landscapes that may become climatically unsuitable for redwoods at a regional scale. </p>
Functional groups of wild bees respond differently to faba bean (Vicia faba L.) cultivation at landscape scale
<p><span><b>1.</b> Concerns about insect declines are growing and the provisioning of ecosystem services like pollination may be threatened. To safeguard biodiversity, greening measures were introduced within the reform of the EU's Common Agricultural Policy. One measure commonly applied by farmers is the cultivation of nitrogen fixing crops. Although underlying studies are largely missing, this measure is criticized as providing no significant biodiversity benefit.<b> </b></span></p> <p><span><b>2.</b> Using a landscape-scale approach, we selected 30 paired study landscapes (1km x 1km) in Germany, i.e. 15 study landscapes with faba bean (FB) fields (<i>Vicia faba</i> L.) and 15 without any grain legumes. Flower-visiting wild bees were recorded with transect walks at the field margins of different crops using a stratified sampling approach. We analyzed the effect of FB cultivation and landscape composition on the abundance and species richness of wild bees as well as on the functional composition of the bee communities. </span></p> <p><span><b>3.</b> Bumblebee densities (<i>Bombus</i> spp. Latreille) were more than twice as high in FB compared to control landscapes after the flowering of the beans. Non-<i>Bombus</i> wild bee densities, however, were not affected by FB cultivation, but were enhanced by increasing amounts of semi-natural habitats (SNH). </span></p> <p><span><b>4.</b> After the beans` blooming had ceased, FB landscapes had a higher proportion of wild bees collecting pollen from Fabaceae than control landscapes. The community weighted means for bee size, measured as intertegular distance, were not affected by FB cultivation, but we found smaller species and species with shorter tongues with an increasing percentage of SNH. </span></p> <p><span><b>5.</b> <i>Synthesis and applications</i>. The cultivation of faba bean (<i>V. faba </i>L.<i>)</i> strongly increased bumblebee densities throughout the season. This indicates that also on-field greening measures can support biodiversity. Nevertheless, since only functional groups adapted to faba bean benefit, measures to promote semi-natural habitats in agricultural landscapes need to be implemented. We conclude that the combination of on- and off-field measures is essential to maintain farmland biodiversity and the Common Agricultural Policy should furthermore promote both.</span></p>
Data from: Epidemic and endemic pathogen dynamics correspond to distinct host population microbiomes at a landscape scale
Infectious diseases have serious impacts on human and wildlife populations, but the effects of a disease can vary, even among individuals or populations of the same host species. Identifying the reasons for this variation is key to understanding disease dynamics and mitigating infectious disease impacts, but disentangling cause and correlation during natural outbreaks is extremely challenging. This study aims to understand associations between symbiotic bacterial communities and an infectious disease, and examines multiple host populations before or after pathogen invasion to infer likely causal links. The results show that symbiotic bacteria are linked to fundamentally different outcomes of pathogen infection: host–pathogen coexistence (endemic infection) or host population extirpation (epidemic infection). Diversity and composition of skin-associated bacteria differed between populations of the frog, Rana sierrae, that coexist with or were extirpated by the fungal pathogen, Batrachochytrium dendrobatidis (Bd). Data from multiple populations sampled before or after pathogen invasion were used to infer cause and effect in the relationship between the fungal pathogen and symbiotic bacteria. Among host populations, variation in the composition of the skin microbiome was most strongly predicted by pathogen infection severity, even in analyses where the outcome of infection did not vary. This result suggests that pathogen infection shapes variation in the skin microbiome across host populations that coexist with or are driven to extirpation by the pathogen. By contrast, microbiome richness was largely unaffected by pathogen infection intensity, but was strongly predicted by geographical region of the host population, indicating the importance of environmental or host genetic factors in shaping microbiome richness. Thus, while both richness and composition of the microbiome differed between endemic and epidemic host populations, the underlying causes are most likely different: pathogen infection appears to shape microbiome composition, while microbiome richness was less sensitive to pathogen-induced disturbance. Because higher richness was correlated with host persistence in the presence of Bd, and richness appeared relatively stable to Bd infection, microbiome richness may contribute to disease resistance, although the latter remains to be directly tested.
Data from: Associations with landscape and local-scale wetland habitat conditions vary among migratory shorebird species during stopovers
<p>Wetlands provide many ecosystem services and functions, including critical stopover habitat for numberous migratory shorbirds species. We conducted shorebird surveys at >14,000 wetlands and associated observed abundance with wetland variables for 16 species. We found that the scale at which observed abundance was associated with wetland extent varied among speceis, and that for most species abundance was positively associated with higher wetland density, presence of shallow water, more usable area, and limited vegetation. There was considerable variation in the strength and sometimes direction of responses. Our study helps inform optimal habitat requirementes for shorebirds.</p>
Pairing Remote Sensing and Clustering in Landscape Hydrology for Large-Scale Changes Identification. Applications to the Subarctic Watershed of the George River (Nunavik, Canada). Dataset and Code.
<p>For remote and vast northern watersheds, hydrological data are often sparse and incomplete. Landscape hydrology provides useful approaches for the indirect assessment of the hydrological characteristics of watersheds through analysis of landscape properties. In this study, we used unsupervised Geographic Object-Based Image Analysis (GeOBIA) paired with the Fuzzy C-Means (FCM) clustering algorithm to produce seven high-resolution territorial classifications of key remotely sensed hydro-geomorphic metrics for the 1985-2019 time-period, each spanning five years. Our study site is the George River watershed (GRW), a 42,000 km<sup>2</sup> watershed located in Nunavik, northern Quebec (Canada). The subwatersheds within the GRW, used as the objects of the GeOBIA, were classified as a function of their hydrological similarities. Classification results for the period 2015-2019 showed that the GRW is composed of two main types of subwatersheds distributed along a latitudinal gradient, which indicates broad-scale differences in hydrological regimes and water balances across the GRW. Six classifications were computed for the period 1985-2014 to investigate past changes in hydrological regime. The seven-classification time series showed a homogenization of subwatershed types associated to increases in vegetation productivity and in water content<br> in soil and vegetation, mostly concentrated in the northern half of the GRW, which were the major changes occurring in the land cover metrics of the GRW. An increase in vegetation productivity likely contributed to an augmentation in evapotranspiration and may be a primary driver of fundamental shifts in the GRW water balance, potentially explaining a measured decline of about 1 % (∼ 0.16 km<sup>3</sup>y<sup>−1</sup>) in the George River’s discharge since the mid-1970s. Permafrost degradation over the study period also likely affected the hydrological regime and water balance of the GRW. However, the shifts in permafrost extent and active layer thickness remain difficult to detect using remote sensing based approaches, particularly in areas of discontinuous and sporadic permafrost.</p>
Data from: Scale-dependence of landscape heterogeneity effects on plant invasions
<p><span>Invasive alien species are amongst the most concerning threats to native biodiversity worldwide, and the level of landscape heterogeneity is considered to affect spatial patterns of their occurrence and spread. However, as previous studies on these associations report contrasting results, the role of landscape heterogeneity on its susceptibility to invasions remains poorly understood. Landscape heterogeneity is usually described by two measures: configuration and composition. Both measures may differently affect invasive species and these impacts may be additionally scale-dependent. Nevertheless, their relative contribution to invasion patterns is poorly known. We investigated the effect of two landscape heterogeneity components: configuration (edge density) and composition (number and evenness of land-cover types) measured at different spatial scales (from within 0.25 km to 5 km of the studied localities) on the local abundance of one of the most invasive alien plant species in Europe, the North American goldenrods (<em>Solidago canadensis</em> and <em>S. gigantea</em>). Using publicly available geospatial environmental data and a novel method based on remote analysis of Google Street View images, we collected and analyzed large dataset on goldenrod occurrence along 1347 roadside transects in agricultural landscapes of Poland. Both the compositional and configurational heterogeneity were positively associated with the local abundance of goldenrods, however the effect size of these relationships was dependent on spatial scale. While abundance-heterogeneity associations were most pronounced at the largest spatial scale for compositional heterogeneity, the pattern was the opposite for configurational heterogeneity. Landscape heterogeneity is a clear correlate of plant invasion potential, with occurrences of invasive plants generally higher in more heterogeneous landscapes. However, scale-dependence of this association means that researchers and practitioners may miss the association if only concentrating on a single spatial scale. While increasing heterogeneity of rural landscapes is widely introduced as a way to promote farmland biodiversity, we show that it may also support invasive plants and thus conflict with original goals of biodiversity-oriented strategies. Therefore, we suggest implementing regular management and eradication schemes in most heterogeneous landscapes. Finally, we demonstrate how remote analysis of plant invasions using existing imagery can advance our understanding of invasion biology.</span></p>
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.
Data from: Ecosystem multifunctionality is promoted by organic farming and hedgerows at the local scale but not at the landscape scale
<p><span>This dataset gathers information used for the paper Couthouis et al. "Ecosystem multifunctionality is promoted by organic farming and hedgerows at the local scale but not at the landscape scale", part of the BIOMHE project (2019-2022) funded by the Fondation de France. It contains data about (i) species richness and abundances used for calculating ecological performance, (ii) crop yield used for calculating agronomic performance, (iii) labour and semi-net margin used for calculating socio-economic performance. Combined, these information allows for the calculation of ecosystem multifunctionaliy indices.</span></p>
Feeding habits influence species habitat associations at the landscape scale in a diverse clade of Neotropical fishes
<p><strong>Aim.</strong> A primary goal of community ecology is to understand the mechanisms that drive species' spatial distribution and habitat associations. Species' geographic distribution can be influenced by the distribution of their prey partly because consumers' behavior is oriented to optimal energy use during foraging. We analyzed how differences in dietary preferences influence the spatial distribution and habitat associations of species at the landscape scale. We hypothesized that differences in feeding guilds will lead to divergent habitat association patterns among species.</p> <p><strong>Location.</strong> Amazon River drainage basin. </p> <p><strong>Taxon.</strong> Characiform fishes in the family Serrasalmidae (piranhas and pacus). </p> <p><strong>Methods.</strong> We used diet data to classify species into feeding guilds (frugivores, herbivores, piscivores, fin and scale feeders, and planktivores). We used three proxies of habitat association derived from satellite products: floodplain extent, landscape heterogeneity, and flood duration, in three distance buffers. We implemented Phylogenetic Generalized Least Squares models to evaluate the relationship between habitat association and feeding guilds.</p> <p><strong>Results.</strong> Frugivores, piscivores, and fin and scale feeders presented similar patterns of habitat associations, with frugivores occupying wider areas of floodplain and greater landscape heterogeneity. Herbivores and planktivores were associated with smaller floodplain extents and lower landscape heterogeneity. All feeding guilds were associated with similar levels of flood duration.</p> <p><strong>Main conclusions.</strong> Differences in resource distribution (assessed through feeding guilds) can influence habitat association. Considering the hydrological variability (i.e., floodplain extent) and landscape heterogeneity that characterize floodplains, the patterns of habitat association vary with the spatial scale considered. This work highlights the importance of understanding species habitat associations by fish as well as food resource dynamics and floodplain dependence. This realization is critical for assessing the impact of anthropogenic activities on freshwater ecosystems.</p>
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>
Data from: Individual Movement - Sequence Analysis Method (IM-SAM): characterising spatio-temporal patterns of animal trajectories across scales and landscapes
<p>Dataset included in Zenodo supports the analyses performed in "<em>Individual Movement - Sequence Analysis Methods (IM-SAM) characterising spatio-temporal patterns of animal trajectories across scales and landscapes.</em>"</p> <p>The dataset includes one RDS file, that can be easily loaded into R using the readRDS function. The RDS file consists out of a list including two objects per animal:</p> <ul> <li>Object 1 contains a data frame with the real and simulated sequences for an animal. e.g., ls[[1]][[1]] </li> <li>Object 2 contains the home range in raster format of an animal. e.g., ls[[1]][[2]]</li> </ul> <p>The data frames in object 1 contain real habitat use sequences and corresponding simulated habitat use sequences generated in the home range of the specific individual (900 simulated sequences: 6 habitat selection rules x 3 selection coefficients x 50 repetitions). Open and closed habitats are respectively encoded by 0 and 1. The first 96 columns of each row in a data frame represent a 16-day habitat use sequence, with a fixed 4-hour relocation interval (0, 4, 8, 12, 16 and 20h). Column names are named as follows: Day_1_0h, Day_1_4h,..., Day_16_20h. In the next columns we provide the selection coefficients (columns 97-99), the habitat selection rules (or pattern, columns 100-102) and the number of missing values (mvs, columns, 103-104) for each of the real and simulated sequences. Note that simulated sequences have no missing values (i.e. values are always 0.00) and for real sequences there is no selection coefficient or habitat selection rule (i.e. values are always xxx).</p> <p>Rownames of simulated sequences are composed out of the habitat selection rule (c, o, a24, a33, a42 and u), the selection coefficient (5, 10, 50) and the replicate (1 to 50), separated by dashes. For example, the first simulated sequence in the first data frame (ls[[1]][[1]][1,]) is described as a24_10_1. The rownames of real sequences instead are composed out of the individuals' identifier, the biweekly period (1 to 23) and the year. For example, the first real sequence in the first data frame (ls[[1]][[1]][901,]) is described as 1_5_2006.</p> <p><br> </p>
Data from: A landscape approach for optimizing the cost-effectiveness of large-scale forest restoration
<p>This is a complete dataset for achieving results of the manuscript "<strong>A landscape approach for optimizing the cost-effectiveness of large-scale forest restoration</strong>". </p> <p> </p> <p><strong>Abstract: </strong></p> <ol> <li>Achieving global targets for forest restoration will require cost-effective strategies to return agricultural land to forest, while minimizing implementation costs and negative outcomes for agricultural production.</li> <li>We present a landscape approach for optimizing the cost-effectiveness of large-scale forest restoration. Across three different landscapes within Brazil's Atlantic Forest biodiversity hotspot, we modelled landscape scenarios based on spatially-explicit data on the probability of natural regeneration, restoration costs, land opportunity costs, and forest restoration outcomes for increasing carbon stocking and landscape connectivity<em>.</em> We compare benefits of our cost-reduction approach to the legally mandated riparian restoration and randomly distributed approaches.</li> <li>Compared with riparian prioritization and considering both implementation and opportunity costs, our cost-reduction scenario produced the greatest savings (20.9%) in mechanized agricultural landscapes.</li> <li>When only considering implementation costs, our cost-reduction scenario led to the highest savings (38.4%) in the landscape with highest forest cover where natural regeneration potential is highest and enables cost-effective carbon stocking and connectivity.</li> </ol> <p><em>Synthesis and applications.</em> We present a guide for forest restoration planning that maximizes specific outcomes with minimal costs and reduction of agricultural production. Furthermore, we show how policies could encourage prioritization of low-cost restoration via natural regeneration, increasing cost-effectiveness. While our study focuses on Brazil’s Atlantic Forest, the approach can be parameterized for other regions.</p> <p><strong>Resumo:</strong></p> <ol> <li>Atingir metas globais para a restauração florestal exigirá estratégias economicamente viáveis para transformar terras agrícolas em floresta, minimizando custos de implementação e os resultados negativos para a produção agrícola.</li> <li>Apresentamos uma abordagem de paisagem para otimizar a relação custo-eficácia da restauração florestal em larga escala. Em três diferentes paisagens, no Bioma da Mata Atlântica, modelamos cenários baseados em dados espacialmente explícitos sobre a probabilidade de regeneração natural, custos de restauração, custos de oportunidade da terra e resultados de restauração florestal com o objetivo de aumentar o estoque de carbono e a conectividade da paisagem. Por fim, comparamos os benefícios da nossa abordagem de redução de custos com a tradicional abordagem de restauração da paisagem em zonas ripárias (áreas de preservação permanente) e abordagens de espacialidade aleatoriamente distribuídas.</li> <li>Comparado com a priorização ripária e considerando os custos de implementação e de oportunidade, nosso cenário de redução de custos produziu as maiores economias (20,9%) em paisagens agrícolas mecanizadas.</li> <li>Ao considerar apenas os custos de implementação, nosso cenário de redução de custos levou à maior economia (38,4%) na paisagem com maior cobertura florestal, onde o potencial de regeneração natural é maior e permite uma melhor relação de custo-oportunidade no estoque de carbono e na conectividade da paisagem.</li> </ol> <p><em>Síntese e aplicações.</em> Apresentamos aqui um guia para o planejamento de restauração florestal que maximiza resultados específicos com redução de custos e mínima influência na produção agrícola. Além disso, mostramos como políticas públicas poderiam incentivar a priorização da restauração de baixo custo via regeneração natural, aumentando a relação custo-benefício. Enquanto nosso estudo se concentra na Mata Atlântica do Brasil, a abordagem pode ser parametrizada para outras regiões.</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>
ScienceDex guides
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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.