Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
54
datasets available to search
ShareScore release 0.9.0
Dataset results
54 results for “ecosystem type”
Bee species abundance and composition in three ecosystem types at the Sevilleta National Wildlife Refuge, New Mexico, USA
This study was designed to examine community- or population-level fluctuations in bee species at the Sevilleta National Wildlife Refuge, both intra- and inter-annually. From 2002 to 2019, passive funnel traps were used to collect bees at three sites, each representing a different ecosystem type of the southwestern U.S. (Plains grassland, Chihuahuan Desert grassland, and Chihuahuan Desert shrubland). Bees were collected during each month from March through October, and were identified to species by taxonomic experts.
Data set for Global quantitative synthesis of ecosystem functioning across climatic zones and ecosystem types
<p>Dataset used in the publication: " Global quantitative synthesis of ecosystem functioning across climatic zones and ecosystem types". The dataset gathers estimates of ecosystem standing stocks (biomass, organic carbon, detritus), fluxes (GPP, ER, NEP) and process rates (decomposition and carbon uptake rates) for eight broad ecosystem types (forest, grassland, agroecosystem, desert, stream, lake, pelagic and benthic marine ecosystems) in five broad climatic zones (arctic, boreal, arid, temperate, tropical, arid).</p> <p>The scripts to produce the figures and the statistics of the publication are released along with the txt version of the data, which file is uploaded when running the script.</p>
Multiple Element Limitation in Northern Hardwood Ecosystems (MELNHE): Soil Profile Rock Characteristics by Bedrock Type in Bartlett and Hubbard Brook, 2004-2018
Soils in our northeastern forests were formed in parent materials deposited by glaciers. The direction and distance of glacial movement can be used to predict the source of glacial till at “downstream” points on the landscape (Bailey 1992). The goal of this project was to identify the rocks excavated from the soil pits in each of the plots and then to use that data to validate the glacial till model. The minority of rocks in the soil pits matched the bedrock, showing the importance of glacial movement. Additional detail on the MELNHE project, including a data table of site descriptions and a pdf file with the project description and diagram of plot configuration can be found in this data package: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-hbr&identifier=344. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station. Literature cited: Bailey, S.W., 1992. Lithologic composition and rock weathering potential of forested, glacial-till soils (Vol. 662). US Department of Agriculture, Forest Service, Northeastern Forest Experiment Station.
Mapping ecosystem types and land cover types in the Seychelles granitic islands, using Earth Engine and Sentinel-2
<p>We share here maps produced using Earth Engine: https://code.earthengine.google.com/?accept_repo=users/bsenterre/gis</p> <p>The maps include a land cover classification based on Sentinel-2, at 10m resolution, using an Object-Based Image Analysis approach, for the Seychelles granitic islands. Based on the land cover, landform (modeled using TauDEM), altitude and expert knowledge, we then derived a model of ecosystem types, with 3 maps: current distribution, potential distribution and prehuman distribution.</p> <p>A report exists (18th May 2022) that describes in detail the methodology, and it is being used for the preparation of a publication. The maps uploaded here are in raster format (geotif), crs=4326, and are accompanied by QGIS legend files (.qml), so they should load in QGIS with their legend automatically.</p>
New woody plant functional types and parameters for the SAVANNA ecosystem model
<p>New woody plant functional types (PFTs) are defined and parameterised for use in the SAVANNA ecosystem model (Coughenour, 1992, 1993). Supplementary material used in creating the PFTs and parameters are included. Details of the methods are available from the authors on request. The new woody PFTS are defined in terms of growth form, leaf size and defences in relation to large mammal herbivores.</p> <p>1. shrub types are <4 m (Zizka et al., 2014),</p> <p>2. fine-leaf types have bipinnate leaves with leptophyllous- or nanophyllous-sized leaflets (<225 mm2) according to Raunkaier’s leaf size classes (Fuller and Bakke, 1918) given that leaflets of compound leaves are separate morphological units analogous to simple leaves (Milla, 2012; Mo et al., 2022),</p> <p>3. high chemical defence investment (CDI) types have either nitrogen:acid detergent fibre (N:ADF) <0.10 (Wallis et al., 2012) or condensed tannin (CT) >5% (Cooper and Owen-Smith, 1985) when expressed in sorghum tannin or leucocyanidin equivalents as determined by the acid-butanol assay,</p> <p>4. all types, except fine_highcdi and fine_lowcdi, have the square-root of Charles-Dominique et al.'s (2017) "investment in structural defence" (ISD) < 13.</p>
Taxonomy, distribution and classification of ecosystem-types, integrating the recent IUCN function-based typology and local conceptualizations
<p>1. Introduction:</p> <p>This dataset is a work in progress. It compiles data gathered on ecosystem-types and their distribution based on a series of field studies led by the author, in Seychelles and West and Central Africa (Senterre 2014, Senterre & Wagner 2014, Senterre 2016, Senterre et al. 2017, 2019, 2020, 2021a, 2022). The aims of this dataset are:</p> <p>a. To share in an explicit and transparent way data on proposed taxonomies of ecosystems, i.e. conceptualizations of ecosystem-types, including explicit ecosystem names and management of synonymies.</p> <p>b. To develop ecosystem red listing based on transparent and falsifiable distribution raw data, combining distribution modeling (maps) and in situ observation of individual stand occurrences.</p> <p>c. To illustrate in detail how to deal with ecosystem data following the approach described in Senterre et al. (2021b) (i.e. "ecosystemology" approach).</p> <p>d. To integrate the above approach with the newly developed function-based typology of ecosystems (Keith et al. 2022), therefore contributing to bridging the persistent gap between the global and the local scales in ecosystem descriptions and classifications.</p> <p> </p> <p>2. Context and versions:</p> <p>This dataset was initially planned for publication on GBIF (Global Biodiversity Information Facility), as part of a project developed for the review of Key Biodiversity Areas in Seychelles: "Mainstreaming recent species and ecosystem distribution data into Key Biodiversity Areas assessments in Seychelles" (<a href="https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf">https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf</a>).</p> <p>In the first version of the GBIF dataset (<a href="https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf">https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf</a>), we proposed an analysis of the potential 'core' and 'extension' files available in GBIF for a publication of ecosystem-type names (and synonymies) and their corresponding occurrences recorded from field observations. This is an original analysis of taxonomic principles managed entirely at the scale of local observable objects, and their history of identifications or interpretations.</p> <p>Toward the end of the above-mentioned GBIF project, considering the limitations and gaps currently present in GBIF, it was decided to restrict the GBIF dataset to a simple 'metadata' entry and to publish the complete version of this dataset in Zenodo. This allows to include all tables needed, as well as all required fields without having to accommodate them within the limited GBIF structure (see metadata description on GBIF for more details). The fields of the tables published here are described in the GBIF metadata entry and in the ecosystemology paper (Senterre et al. 2021b).</p> <p> </p> <p>3. New development on typology aspects:</p> <p>In addition, considering that the new IUCN global typology of ecosystems is now published (Keith et al. 2022), we have reviewed in detail the possibility of integration of ecosystems conceptualized using our ecosystemology approach within the new IUCN typology. The result of this analysis is being considered for a publication, and this Zenodo dataset would then be published in full (i.e. including all typology aspects) as supplementary materials. In the meantime, I would be happy to discuss any of these aspects with whoever is interested.</p> <p> </p> <p>4. Access to ecosystem data for conservation actors:</p> <p>Finally, the actual data (published here) on ecosystem-types, their names, synonymies, classification, distribution, and red list status are compiled into a format that we designed to be useful to conservation actors in the form of interactive webpages (produced with R as shiny apps). This development is based on very limited resources, and the author is still quite new to R, so any help or feedback on ways to improve the scripts would be very much welcomed.</p> <p>The interactive page is available here (currently filtered to Seychelles' data only, although the dataset contains data beyond the Seychelles): https://shiny.bio.gov.sc/bioeco/</p> <p>The R scripts are available on Github: https://github.com/bsenterre/ecosystemology</p> <p> </p> <p>5. Tables contained in this dataset:</p> <p>a. Ecosystem taxonomy tables:</p> <p>ecoSpecies: Contains the list of all ecosystem-type names with their unique identifier.</p> <p>ecoOccurrences: Contains the list of individual stand occurrences, including ecosystem characters as standardized in Senterre et al. (2021b; i.e. virtual ecosystem specimen).</p> <p>ecoSpeciesProfiles: Contains basic metadata on ecosystem-types, such as their Red List evaluations.</p> <p>ecoIdentifications: Contains all the different interpretations/identifications (referring to the table ecoSpecies or to higher levels of classification, see below) made on the stands observed in the ecoOccurrences table.</p> <p> </p> <p>b. Ecosystem typology tables (TO BE ADDED LATER):</p> <p>IUCNL3: This is just a transcription, as is, of the IUCN global typology version 2.1.</p> <p>IUCNL3BIOCrossover: This table defines and comments correspondences between BIOL2 (the level 2 of the typology used by us) and the IUCN typology L3 (level 3).</p> <p>BIOL2: This is a variation based on the IUCN typology, here our level 2.</p> <p>BIOL3: This is a variation based on the IUCN typology, here our level 3.</p> <p>BIOL4: This is a variation based on the IUCN typology, here our level 4.</p> <p>ecoGenus: This is a general type of stand (thus excluding any regional ecosystem connotation), defined at a local scale and never combined with any geographic connotation (see ecosystemology paper: Senterre et al. 2021b).</p> <p>ecoFamily: This is a generalized version of the ecoGenus (i.e. still excluding any regional, sub-regional or geographic aspect).</p> <p>ecoOrder: This is a further generalized version of the ecoGenus (see also Senterre et al. 2020).</p> <p>lifeZone: This is a basic and incomplete list of life zones as defined following the Holdridge (1967) approach, with some additional elements proposed in Senterre et al. (2021b).</p> <p> </p> <p>6. Literature cited:</p> <p>Holdridge, L. R. 1967. Life zone ecology. Tropical Science Center, San Jose, Costa Rica.</p> <p>Keith, D. A., J. R. Ferrer-Paris, E. Nicholson, M. J. Bishop, B. A. Polidoro, E. Ramirez-Llodra, M. G. Tozer, J. L. Nel, R. Mac Nally, E. J. Gregr, K. E. Watermeyer, F. Essl, D. Faber-Langendoen, J. Franklin, C. E. R. Lehmann, A. Etter, D. J. Roux, J. S. Stark, J. A. Rowland, N. A. Brummitt, U. C. Fernandez-Arcaya, I. M. Suthers, S. K. Wiser, I. Donohue, L. J. Jackson, R. T. Pennington, T. M. Iliffe, V. Gerovasileiou, P. Giller, B. J. Robson, N. Pettorelli, A. Andrade, A. Lindgaard, T. Tahvanainen, A. Terauds, M. A. Chadwick, N. J. Murray, J. Moat, P. Pliscoff, I. Zager, and R. T. Kingsford. 2022. A function-based typology for Earth’s ecosystems. . Nature 610:513–518. doi:10.1038/s41586-022-05318-4.</p> <p>Senterre, B. 2014. Mapping habitat-types within the Hummingbird site at Dugbe (Liberia, West Africa). Consultancy Report, Missouri Botanical Garden. P. 56. https://doi.org/10.13140/RG.2.2.32628.48003.</p> <p>Senterre, B. 2016. Habitat-type ground-truthing and assessment of ecosystem conservation value in the Bel Air Alufer mining site (Guinea, West Africa), with recommendations for improving the draft map of land cover types. Consultancy Report, Missouri Botanical Garden, A study conducted for Alufer Mining Limited. P. 54.</p> <p>Senterre, B., E. Bidault, and T. Stévart. 2019. Identification et évaluation des écosystèmes menacés du Mont Nimba. Rapport de consultance, Missouri Botanical Garden (MBG), Africa and Madagascar Department. P. 106. https://doi.org/10.13140/RG.2.2.13242.93129.</p> <p>Senterre, B., E. Bidault, T. Stévart, and P. P. Lowry II. 2020. Assessment of Key Biodiversity Areas in the Lofa-Gola-Mano & Nimba complexes (West Africa) using ecosystem criteria. Final Report, Missouri Botanical Garden. P. 146. 10.13140/RG.2.2.17934.89924.</p> <p>Senterre, B., E. Bidault, T. Stévart, M. Wagner, and P. Lowry. 2017. Mapping habitat-types in south-east Kouilou (Republic of Congo). Consultancy Report, Missouri Botanical Garden (MBG), Africa and Madagascar Department, St. Louis, Missouri, USA. P. 163.</p> <p>Senterre, B., R. M. Bristol, G. Gendron, and E. Henriette. 2021a. Fine-tuning conservation priorities in Seychelles at the landscape scale, using global KBA guidelines with both species and ecosystem criteria. Consultancy Report, United Nations Development Programme, GOS/UNDP/GEF Programme Coordination Unit, Victoria, Seychelles.</p> <p>Senterre, B., P. P. Lowry II, E. Bidault, and T. Stévart. 2021b. Ecosystemology: a new approach toward a taxonomy of ecosystems. . Ecological Complexity 47:100945. doi:https://doi.org/10.1016/j.ecocom.2021.100945.</p> <p>Senterre, B., A.-H. Paradis, E. Bidault, T. Stévart, and P. P. Lowry II. 2022. Qualité et distribution des savanes montagnardes du Nimba. Rapport de consultance, Missouri Botanical Garden (MBG), Africa and Madagascar Department. P. 73. http://dx.doi.org/10.13140/RG.2.2.13433.34401.</p> <p>Senterre, B., and M. Wagner. 2014. Mapping Seychelles habitat-types on Mahé, Praslin, Silhouette, La Digue and Curieuse. Consultancy Report, Government of Seychelles, United Nations Development Programme, Victoria, Seychelles. P. 119. https://doi.org/10.13140/RG.2.1.4558.6009.</p>
Data from: defining the pyro-thermal niche: do seed traits, ecosystem type and phylogeny influence thermal thresholds in seeds with physical dormancy
<p>Seeds are a key pathway for plant population recovery following disturbance. To prevent germination during unsuitable conditions, most species produce dormant seeds. In fire-prone regions, physical dormancy (PY) enables seeds to germinate after fire. The thermal niche, incorporating seed dormancy and mortality temperature responses, has not been characterised for PY seeds from fire prone environments.</p> <p>We aimed to assess variation in thermal thresholds between species with PY seeds and if the pyro-thermal niche is aligned with seed mass, ecosystem type or phylogenetic relatedness.</p> <p>We collected post heat-shock germination data for 58 Australian species that produce PY seeds. We applied species-specific thermal performance curves to define three critical thresholds (DRT<sub>50, </sub>dormancy release temperature; T<sub>opt</sub>,<sub> </sub>optimum dormancy release temperature and LT<sub>50</sub>, lethal temperature), defining the pyro-thermal niche. Each species was assigned a mean seed weight and ecosystem type. We constructed a phylogeny to account for species relatedness and calculated phylogenetic signal (h<sup>2</sup>) for LT<sub>50,</sub> T<sub>opt</sub>, and<sub> </sub>DRT<sub>50</sub>.</p> <p>Seeds of <em>Pomaderris</em> (Rhamnaceae) had the highest T<sub>opt</sub> and LT<sub>50</sub>, and <em>Pomaderris bodalla</em> having the highest DRT<sub>50 </sub>of 101.3°C. Seeds from species within this family exhibited higher temperature thresholds than those from Fabaceae. Seed mass was only influential in explaining LT<sub>50 </sub>variation.</p>
CESM2.2-8P4Z data supporting Yu et al. (2024): Simulating ecosystem dynamics and marine biogeochemical cycles with multiple plankton functional types
<p><span>This dataset contains the model output from CESM2.2-8P4Z, used in Yu et al. (2024) and</span><span> </span><span>submitted to</span><span> the Journal of Advances in Modeling Earth Systems (JAMES). These are the last 20-year averaged output files from 310 years of the model simulations, which are analyzed in Yu et al., (2024). CESM2.2-8P4Z contains twelve plankton groups, including eight types of phytoplankton:</span><span> </span><span>1</span><span>) picophytoplankton groups: <em>Prochlorococcus</em>, <em>Synechococcus</em>, picoeukaryotes and diazotrophs; 2) nanophytoplankton groups:</span><span> </span><em><span><em>P</em></span></em><em><span><em>haeocystis</em></span></em><span>, <em>coccolithophores</em></span><span> </span><span>and a generic other nanophytoplankton; 3) micro-sized phytoplankton: diatoms</span><span>; and four types of zooplankton:</span><span> </span><span>small microzooplankton (5-20 u</span><span>m, such as ciliates, nanoflagellates), large microzooplankton (20-200 u</span><span>m, such as copepod nauplii, small dinoflagellates etc.), mesozooplankton (200-2000 u</span><span>m, such as smaller copepod, large dinoflagellates) and macrozooplankton (>2000 u</span><span>m, such as larger copepod, krill).</span><span> </span><span>The MARBL-8P4Z model improves seasonal simulation of the spring bloom compared with more simplified MARBL configurations, benefiting from dampened diatom blooms at higher latitudes due to a combination of bottom-up and top-down drivers.</span></p>
Linked collectors and determiners for: Taxonomy and distribution of ecosystem types: implementation of ecosystemology principles.
Natural history specimen data linked to collectors and determiners held within, "Taxonomy and distribution of ecosystem types: implementation of ecosystemology principles". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf">https://bionomia.net/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf">https://gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf</a>. Formatted as a Frictionless Data package.
Dataset from: The effects of crop type, landscape composition and agroecological practices on biodiversity and ecosystem services in tropical smallholder farms
<p>1. In the tropics, smallholder farming characterizes some of the world's most biodiverse landscapes. Agroecology as a pathway to sustainable agriculture has been proposed and implemented in sub-Saharan Africa, but the effects of agricultural practices in smallholder agriculture on biodiversity and ecosystem services are understudied. Similarly, the contribution of different landscape elements, such as shrubland or grassland cover, on biodiversity and ecosystem services to fields remains unknown.</p> <p>2. We selected 24 villages situated in landscapes with varying shrubland and grassland cover in Malawi. In each village, we assessed biodiversity of eight taxa and ecosystem services in relation to crop type, shrubland and grassland cover and the number of agroecological pest and soil management practices on smallholder's fields of different crop types (bean monoculture, maize-bean intercrop, and maize monoculture).</p> <p>3. Increasing shrubland cover altered carabid and soil bacteria communities. Carabid abundance increased in maize but decreased in intercrop and bean fields with increasing shrubland cover. Carabid abundance and richness and wasp abundance increased with soil management practices. Carabid, spider, and parasitoid abundances were higher in bean monocultures, but this was modulated by surrounding shrubland cover. Natural enemy abundances in beans were especially high in landscapes with little shrubland, possibly leading to lower bean damage in monocultures compared to intercropped fields, whereas maize monocultures had higher damage. In maize, grassland cover and pest management practices were positively related to damage. Carabid abundance was higher in fields with high bean damage and increased carabid richness in fields with high maize damage. Parasitoid abundance was negatively associated with bean damage.</p> <p>4. <em>Synthesis and application:</em> Our results suggest that maintaining biodiversity and ecosystem services on smallholder farms is not achievable with a "one size fits all" approach but should instead be adapted to the landscape context and the priorities of smallholders. Shrubland is important to maintain carabid and soil bacterial diversity, but legume cultivation beneficial to natural enemies could complement pest management in landscapes with a low shrubland cover. An increased number of agroecological soil management practices can lead to improved pest control whilst the effectiveness of agroecological pest management practices needs to be re-evaluated.</p>
Data from: Defining the pyro-thermal niche: do seed traits, ecosystem type and phylogeny influence thermal thresholds in seeds with physical dormancy
Open the record for dataset details and reuse information.
Data from: Trade-offs among restored ecosystem functions are context-dependent in Mediterranean-type regions
Open the record for dataset details and reuse information.
Dataset from: The effects of crop type, landscape composition and agroecological practices on biodiversity and ecosystem services in tropical smallholder farms
Open the record for dataset details and reuse information.
Data from: Type Maastrichtian gastropod faunas evidencing rapid ecosystem recovery following the Cretaceous-Palaeogene boundary
The study of the global mass extinction event at the Cretaceous–Palaeogene (K/Pg) boundary can aid in understanding patterns of selective extinction and survival, and dynamics of ecosystem recovery. Outcrops in the Maastrichtian type area (southeast Netherlands, northeast Belgium) comprise an exceptionally expanded K/Pg boundary succession that offers a unique opportunity to study marine ecosystem recovery within the first thousands of years following the mass extinction event. A quantitative analyses was performed on systematically sampled macrofossils of the topmost Maastrichtian and lowermost Danian strata at the former Curfs-Ankerpoort quarry (Geulhem), which represent 'snapshots' of the latest Cretaceous and earliest Palaeogene marine ecosystems, respectively. Molluscs in particular are diverse and abundant in the studied succession. Regional ecosystem changes across the K/Pg boundary are relatively minor, showing a decline in suspension feeders, accompanied by an ecological shift to endobenthic molluscs. The earliest Paleocene gastropod assemblage retains many 'Maastrichtian' features and documents a fauna that temporarily survived into the Danian. The shallow, oligotrophic carbonate platform in this area was inhabited by taxa that were adapted to low nutrient levels and resistant to starvation. As a result, the local taxa were less affected by the short-lived detrimental conditions related to K/Pg boundary perturbations, such as darkness, cooling, starvation and ocean acidification. This resulted in relatively high survival rates, which enabled rapid recolonization and recovery of marine faunas in the Maastrichtian type area.
Influences of Satellite Sensor and Scale on Derivation of Ecosystem Functional Types and Diversity
<p>These are the datasets where were generated for paper "Influences of Satellite Sensor and Scale on Derivation of Ecosystem Functional Types and Diversity"</p>
Trophic cascade within and across ecosystems: the role of anti-predatory defenses, predator type, and detritus quality
<ol> <li>Species in one ecosystem can indirectly affect multiple biodiversity components and ecosystem functions of adjacent ecosystems. The magnitude of these cross-ecosystem effects depends on the attributes of the organisms involved in the interactions, including traits of the predator, prey and basal resource. However, it is unclear how predators with cross-ecosystem habitat interact with predators with single-ecosystem habitat to affect their shared ecosystem. Also, unknown is how such complex top-down effects may be mediated by the anti-predatory traits of prey and quality of the basal resource.</li> <li>We used the aquatic invertebrate food webs in tank bromeliads as a model system to investigate these questions. We manipulated the presence of a strictly aquatic predator (damselfly larvae) and a predator with both terrestrial and aquatic habitats (spider) and examined effects on survival of prey (detritivores grouped by anti-predator defense), detrital decomposition (of two plant species differing in litter quality), nitrogen flux and host plant growth. To evaluate the direct and indirect effects of each predator type on multiple detritivore groups and ultimately on multiple ecosystem processes, we used piecewise structural equation models. For each response variable, we isolated the contribution of different detritivore groups to overall effects by comparing alternate model formulations.</li> <li>Alone, damselfly larvae and spiders each directly decreased survival of detritivores and caused multiple indirect negative effects on detritus decomposition, nutrient cycling, and host plant growth. However, when predators co-occurred, the spider caused a negative non-consumptive effect on the damselfly larva, diminishing the net direct and indirect top-down effects on the aquatic detritivore community and ecosystem functioning. Both detritivore traits and detritus quality modulated the strength and mechanism of these trophic cascades. Predator interference was mediated by undefended or partially defended detritivores as detritivores with anti-predatory defenses evaded consumption by damselfly larvae but not spiders. Predators and detritivores affected ecosystem decomposition and nutrient cycling only in the presence of high-quality detritus, as the low-quality detritus was consumed more by microbes than invertebrates.</li> <li>The complex responses of this system to predators from both recipient and adjacent ecosystems highlight the critical role of maintaining biodiversity components across multiple ecosystems. </li> </ol>
Data from: Species contributions to ecosystem stability change with disturbance type
<p>Simultaneous exposure to multiple stressors complicates the challenge of predicting ecological responses to global environmental change. Here, we show that the contributions of individual species and functional groups to the overall stability of ecosystems can be modified by the presence of different stressors, both individually and in combination. By disturbing natural rocky shore communities with nutrients and sediments and simulating extinction of predatory whelks and grazers, we also found that consumers can simultaneously stabilise and destabilise communities along different stability dimensions, irrespective of their trophic position. Our results suggest that our experimental disturbances influenced consumer contributions to stability indirectly by modifying the interactions between consumers and macroalgae in different ways. These findings merit further exploration in different systems exposed to a range of different stressors to better understand how perturbations of different kinds can modify the multifaceted contributions of species to the overall stability of ecosystems.</p>
Composite landscape predictors improve distribution models of ecosystem types
<p><strong>Aim</strong>: Distribution modelling is a useful approach to obtain knowledge about the spatial distribution of biodiversity, required for e.g., red list assessments. While distribution modelling methods have been applied mostly to single species, modelling of communities and ecosystems (EDM; ecosystem-level distribution modelling) produces results that are more directly relevant for management and decision-making. Although the choice of predictors is a pivotal part of the modelling process, few studies have compared the suitability of different sets of predictors for EDM. In this study, we compare the performance of 50 single environmental variables with that of 11 composite landscape gradients (CLGs) for prediction of ecosystem types. The CLGs represent gradients in landscape element composition derived from multivariate analyses, e.g., 'inner-outer coast' and 'land use intensity'.</p> <p><strong>Location</strong>: Norway.</p> <p><strong>Methods</strong>: We used data from field-based ecosystem type mapping of nine ecosystem types, and environmental variables with a resolution of 100×100 m. We built nine models for each ecosystem type with variables from different predictor sets. Logistic regression with forward selection of variables was used for EDM. Models were evaluated with independently collected data.</p> <p><strong>Results</strong>: Most ecosystem types could be predicted reliably, although model performance differed among ecosystem types. We identified significant differences in predictive power and model parsimony across models built from different predictor sets. Climatic variables alone performed poorly, indicating that the current climate alone is not sufficient to predict the current distribution of ecosystems. Used alone, the CLGs resulted in parsimonious models with relatively high predictive power. Used together with other variables, they consistently improved the models.</p> <p><strong>Main conclusions</strong>: We argue that the use of composite variables as proxies for complex environmental gradients has the potential to improve predictions from EDMs and thus to inform conservation planning as well as improve the precision and credibility of red lists and global change assessments.</p>
Single species acute lethal toxicity tests are not predictive of relative population, community and ecosystem effects of two salinity types
<p>Human mediated salinity increases are occurring in freshwaters globally, with consequent negative effects on freshwater biodiversity. Salinity comprises multiple anions and cations. While total concentrations are typically used to infer effects, individual ion concentrations and ion ratios are critical in determining effects. Moreover, estimates of toxicity from single species laboratory tests, may not accurately predict relative effects on populations, communities and ecosystems. Here we compare salinity increases from synthetic marine salts (SMS) and sodium bicarbonate (NaHCO3) in an outdoor mesocosm experiment in south-eastern Australia. We found different effects of salt types on stream macroinvertebrates at the population, community, and ecosystem function levels, where similar effects were predicted from single species laboratory tests. Our results caution against the use of single species laboratory derived toxicological data to predict both environmentally safe salinity levels and the relative effects of different salt sources on freshwater biodiversity.</p>
Distribution of vegetation sampling plots in four ecosystem types
<p>The table contains a number of bear cuscus presence points based on direct and indirect encounters (representative information from the local guide), as well as a number of plots constructed in each bear cuscus presence point in various ecosystem types in Bantimurung Bulusaraung National Park and Hasanuddin University Educational Forest, South Sulawesi.</p> <p>Three plots of 20 x 20 m were constructed in each bear cuscus presence point, with fifteen plots were established in each ecosystem type.</p>
ScienceDex guides
Understand access before you commit
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.