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.
108
datasets available to search
ShareScore release 0.9.0
Dataset results
108 results for “riparian forest”
Figure 3 in Structure of insect community in the fungus Inonotus radiatus in riparian boreal forests
Figure 3. Species accumulation curves (and 95% confidence intervals) in Inonotus radiatus samples of different decay stages. The curves for fresh decay stages (n = 16 samples) and advanced decay stages (n = 36) have been extrapolated to a common sample size of 49 samples with both living and dead basidiomes (i.e. mixed). Only taxa that were considered to breed in the basidiomes were included.
FIGURE 2 in Forestiera veracruzana (Oleaceae), a new species from the riparian forests of central Veracruz, Mexico
FIGURE 2. Illustration of Forestiera veracruzana Cast.-Campos & Pal.-Wass. sp. nov.: a, tree; b, branch with pistillate inflorescences; c, pistillate inflorescence; d, detail of pistillate flower; e, style types; f, staminate inflorescence; g, detail of stamen. Illustration by Rosa Pérez based on the type specimen O. Palacios-Wassenaar et al. 965 and 969 (XAL).
Data from: Do riparian forest strips in modified forest landscapes aid in conserving bat diversity?
Open the record for dataset details and reuse information.
Data from: Structure and composition of altered riparian forests in an agricultural Amazonian landscape
Open the record for dataset details and reuse information.
Data from: Riparian reserves help protect forest bird communities in oil palm dominated landscapes
Open the record for dataset details and reuse information.
Data from: Quantification and characterization of vegetation and functional trait diversity of riparian zones of the protected forest of Kashmir Himalaya, India
Open the record for dataset details and reuse information.
Data from: Down by the riverside: Riparian edge effects on three monkey species in a fragmented Costa Rican forest
Open the record for dataset details and reuse information.
GIS Shapefile - Riparian vegetation (forest and grass only) within a 100ft buffer of all 1:24K streams in Baltimore City.
Riparian vegetation (forest and grass only) within a 100ft buffer of all 1:24K streams in Baltimore City. Vegetation data used in this analysis came from the MD DNR Forest Service IKONOS-derived Strategic Urban Forest Assessment (SUFA) vegetation layer.
GIS Shapefile - Riparian vegetation (forest and grass only) within a 100ft buffer of all 1:24K streams in Baltimore City, block group
Block group summary of riparian vegetation (forest and grass only) within a 100ft buffer of all 1:24K streams in Baltimore City for only those block groups that intersect the stream buffers. The riparian area consists of all land within a 100 ft buffer of 1:24K streams. Vegetation data used in this analysis came from the MD DNR Forest Service IKONOS-derived Strategic Urban Forest Assessment (SUFA) vegetation layer.
Importance of riparian reserves and other forest fragments for small mammal diversity in disturbed and converted forest landscapes
<b>Description: </b><p>The primary objective of this study was to document the species richness, community composition of the small mammals in riparian remnants within oil palm plantation and in degraded forests. The purpose is to assess the value of retaining riparian remnants within oil palm plantation and logged forest habitats for small mammals conservation. <br>Main questions <br>1. Is there a difference in species richness and community composition of small mammals in riparian remnants within oil palm and logged forests? <br>2. What effects do maintaining riparian remnants in oil palm and logged forests have on small mammal diversity? <br>3. Does the structure and width of riparian remnants in oil palm and logged forests affect small mammal species diversity? <br>4. How does the structure of riparian reserves could be managed to improve the extent to which they retain small mammals communities in oil palm and logged forests?<br>Methods<br>Sampling will be conducted at several sites representing four habitat treatments: (1) riparian reserves in old growth forests as control treatment (at Maliau Basin Conservation Area); (2) riparian reserves of different widths in logged forests (SAFE project area); (3) riparian remnants of different widths in oil palm (south of SAFE project area); and (4) oil palm without any riparian remnants (south of SAFE project area). In addition, sampling was conducted in other forest remnants within oil palm habitats. Each habitat treatment will be represented by three sites serving as replicates. <br>Used a grid trapping of 4 x 12 grid points (23m spacing) for sampling the small mammals. We shall establish one grid at each site with 48 trap stations. Two wire-mesh cage traps (28 x 15 x 12.5 cm), baited with oil palm fruits, will be placed at each station. Trapping of small mammals and searchers for amphibians will be conducted in four sampling sessions. In each session we will visit randomly four sites representing the four habitat treatments. Each sampling session at each site will last for four months. Overall, each habitat treatment will be sampled three times over a 12 months period. The following variables will be collected for each sampling site to characterize the habitat structure: canopy cover, number of large and small logs, number of large and small trees, percentage leaf litter cover and other variables that may influence the distribution and abundance of small mammals.</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/3"><b>Importance of riparian reserves and other forest fragments for mammal and amphibian diversity in disturbed and converted forest landscapes</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>Universiti Malaysia Sabah (Grant)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah biodiversity council (Research licence Local)</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3908128">here</a></p><p><b>Files: </b>This consists of 1 file: UMS_Small_mammal_data.xlsx</p><p><b>UMS_Small_mammal_data.xlsx</b></p><p>This file contains dataset metadata and 1 data tables:</p><ol><li><p><b>Data</b> (described in worksheet Data)</p><p>Description: small mammal presence and absense</p><p>Number of fields: 29</p><p>Number of data rows: 140</p><p>Fields: </p><ul><li><b>landuse</b>: Habitat type (Field type: categorical)</li><li><b>site</b>: Location of sampling (Field type: location)</li><li><b>plot</b>: Plot name (Field type: categorical)</li><li><b>day</b>: Day of sampling (Field type: categorical)</li><li><b>Callosciurus notatus</b>: Number of species caught (Field type: abundance)</li><li><b>Echinosorex gymnurus</b>: Number of species caught (Field type: abundance)</li><li><b>Haeromys margarettae</b>: Number of species caught (Field type: abundance)</li><li><b>Lariscus hosei</b>: Number of species caught (Field type: abundance)</li><li><b>Leopoldamys sabanus</b>: Number of species caught (Field type: abundance)</li><li><b>Maxomys alticola</b>: Number of species caught (Field type: abundance)</li><li><b>Maxomys baeodon</b>: Number of species caught (Field type: abundance)</li><li><b>Maxomys ochraceiventer</b>: Number of species caught (Field type: abundance)</li><li><b>Maxomys rajah</b>: Number of species caught (Field type: abundance)</li><li><b>Maxomys surifer</b>: Number of species caught (Field type: abundance)</li><li><b>Maxomys whiteheadi</b>: Number of species caught (Field type: abundance)</li><li><b>Niniventer cremoriventer</b>: Number of species caught (Field type: abundance)</li><li><b>Rattus exulans</b>: Number of species caught (Field type: abundance)</li><li><b>Rattus rattus</b>: Number of species caught (Field type: abundance)</li><li><b>Rattus tiomanicus</b>: Number of species caught (Field type: abundance)</li><li><b>Sundamys muelleri</b>: Number of species caught (Field type: abundance)</li><li><b>Sundasciurus hippurus</b>: Number of species caught (Field type: abundance)</li><li><b>Sundasciurus lowii</b>: Number of species caught (Field type: abundance)</li><li><b>Sundasciurus tenuis</b>: Number of species caught (Field type: abundance)</li><li><b>Trichys fasciculata</b>: Number of species caught (Field type: abundance)</li><li><b>Tupaia glis</b>: Number of species caught (Field type: abundance)</li><li><b>Tupaia gracilis</b>: Number of species caught (Field type: abundance)</li><li><b>Tupaia minor</b>: Number of species caught (Field type: abundance)</li><li><b>Tupaia tana</b>: Number of species caught (Field type: abundance)</li><li><b>Grand Total</b>: Total (Field type: numeric)</li></ul></li></ol><p><b>Date range: </b>2015-03-01 to 2019-04-30</p><p><b>Latitudinal extent: </b>4.5000 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Animalia <br> -  -  Chordata <br> -  -  -  Mammalia <br> -  -  -  -  Rodentia <br> -  -  -  -  -  Sciuridae <br> -  -  -  -  -  -  <i>Callosciurus</i> <br> -  -  -  -  -  -  -  <i>Callosciurus notatus</i> <br> -  -  -  -  -  -  <i>Lariscus</i> <br> -  -  -  -  -  -  -  <i>Lariscus hosei</i> <br> -  -  -  -  -  -  <i>Sundasciurus</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus hippurus</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus lowii</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus tenuis</i> <br> -  -  -  -  -  Hystricidae <br> -  -  -  -  -  -  <i>Trichys</i> <br> -  -  -  -  -  -  -  <i>Trichys fasciculata</i> <br> -  -  -  -  -  Muridae <br> -  -  -  -  -  -  <i>Maxomys</i> <br> -  -  -  -  -  -  -  <i>Maxomys alticola</i> <br> -  -  -  -  -  -  -  <i>Maxomys baeodon</i> <br> -  -  -  -  -  -  -  <i>Maxomys ochraceiventer</i> <br> -  -  -  -  -  -  -  <i>Maxomys rajah</i> <br> -  -  -  -  -  -  -  <i>Maxomys surifer</i> <br> -  -  -  -  -  -  <i>Rattus</i> <br> -  -  -  -  -  -  -  <i>Rattus exulans</i> <br> -  -  -  -  -  -  -  <i>Rattus rattus</i> <br> -  -  -  -  -  -  -  <i>Rattus tiomanicus</i> <br> -  -  -  -  -  -  <i>Sundamys</i> <br> -  -  -  -  -  -  -  <i>Sundamys muelleri</i> <br> -  -  -  -  -  -  <i>Haeromys</i> <br> -  -  -  -  -  -  -  <i>Haeromys margarettae</i> <br> -  -  -  -  -  -  <i>Niviventer</i> <br> -  -  -  -  -  -  -  <i>Niviventer cremoriventer</i> <br> -  -  -  -  -  -  <i>Chrotomys</i> <br> -  -  -  -  -  -  -  <i>Chrotomys whiteheadi</i> (as homotypic_synonym: <i>Maxomys whiteheadi</i>)<br> -  -  -  -  -  -  <i>Leopoldamys</i> <br> -  -  -  -  -  -  -  <i>Leopoldamys sabanus</i> <br> -  -  -  -  Erinaceomorpha <br> -  -  -  -  -  Erinaceidae <br> -  -  -  -  -  -  <i>Echinosorex</i> <br> -  -  -  -  -  -  -  <i>Echinosorex gymnura</i> <br> -  -  -  -  Scandentia <br> -  -  -  -  -  Tupaiidae <br> -  -  -  -  -  -  <i>Tupaia</i> <br> -  -  -  -  -  -  -  <i>Tupaia glis</i> <br> -  -  -  -  -  -  -  <i>Tupaia gracilis</i> <br> -  -  -  -  -  -  -  <i>Tupaia minor</i> <br> -  -  -  -  -  -  -  <i>Tupaia tana</i> <br></div><p></p>
Bat activity in riparian reserves in forest and oil palm plantations
<b>Description: </b><p>Number of bat calls recorded by an Echometer-3 recorder during 10-minute point counts. Counts are classified within 5 acoustic call types, and several Rhinolophoid species where possible.</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/12"><b>Investigating the importance of riparian reserves for insectivorous bat species in oil palm and forest estates in Sabah, Malaysia</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>UK Natural Environment Research Council (NERC) (Human Modified Tropical Forests programme & a PhD scholarship jointly funded by University of Kent & NERC & EnvEast DTP scholarship, NE/K016407/1 & NE/L002582/1)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Council (Research licence JKM/MBS.1000-2/2(374))</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3971012">here</a></p><p><b>Files: </b>This consists of 1 file: SAFE_data_archive_Bat_Riparian_Acoustic_Struebig_Mullin_Yoh_v2_0308202.xlsx</p><p><b>SAFE_data_archive_Bat_Riparian_Acoustic_Struebig_Mullin_Yoh_v2_0308202.xlsx</b></p><p>This file contains dataset metadata and 1 data tables:</p><ol><li><p><b>All data </b> (described in worksheet MasterData)</p><p>Description: All bat passes and their metadata inc frequencies & species identification for a subset of recordings when possible</p><p>Number of fields: 19</p><p>Number of data rows: 5696</p><p>Fields: </p><ul><li><b>Location</b>: where data was collected (Field type: location)</li><li><b>Type</b>: Habitat type (Field type: categorical)</li><li><b>Visit</b>: Visit number (Field type: numeric)</li><li><b>Date</b>: Date surveyed (Field type: date)</li><li><b>Sunset</b>: Sun set time (Field type: time)</li><li><b>Time</b>: Time data collected (Field type: time)</li><li><b>Mins_after_sunset</b>: Minutes after sunset (Field type: numeric)</li><li><b>Call_type</b>: Taxa (Field type: categorical)</li><li><b>Species_ID</b>: Species ID (Field type: taxa)</li><li><b>Buzz</b>: Presence of feeding buzz (Field type: numeric)</li><li><b>Av_High_freq</b>: Bat frequency (Field type: numeric)</li><li><b>Av_Low_freq</b>: Bat frequency (Field type: numeric)</li><li><b>Average_of_CallDuration</b>: Bat frequency (Field type: numeric)</li><li><b>Rip_res_width</b>: Riparian reserve width (Field type: numeric)</li><li><b>Canopy_gap</b>: Canopy gap within 50m radius buffer (Field type: numeric)</li><li><b>Avg_CH_50mR</b>: Average canopy height within 50m radius buffer (Field type: numeric)</li><li><b>Avg_Biomass_50mR</b>: Average biomass within 50m radius buffer (Field type: numeric)</li><li><b>Prop_Fcover_1km</b>: Proportion forest cover within 1km buffer (Field type: numeric)</li><li><b>Avg_Rug_50mR</b>: Average ruggedness within 50m radius buffer (Field type: numeric)</li></ul></li></ol><p><b>Date range: </b>2014-04-28 to 2018-11-15</p><p><b>Latitudinal extent: </b>4.5000 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Animalia <br> -  -  Chordata <br> -  -  -  Mammalia <br> -  -  -  -  Chiroptera <br> -  -  -  -  -  [BBFM1] <br> -  -  -  -  -  [BBFM2] <br> -  -  -  -  -  [BBFM3] <br> -  -  -  -  -  [BBFM4] <br> -  -  -  -  -  [BBFM5] <br> -  -  -  -  -  [BBFM6] <br> -  -  -  -  -  Hipposideridae <br> -  -  -  -  -  -  <i>Hipposideros</i> <br> -  -  -  -  -  -  -  <i>Hipposideros cervinus</i> <br> -  -  -  -  -  -  -  <i>Hipposideros galeritus</i> <br> -  -  -  -  -  -  -  <i>Hipposideros ridleyi</i> <br> -  -  -  -  -  Rhinolophidae <br> -  -  -  -  -  -  <i>Rhinolophus</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus acuminatus</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus borneensis</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus sedulus</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus trifoliatus</i> <br></div><p></p>
Riparian forests can mitigate warming and ecological degradation of agricultural headwater streams
<p>1. Riparian forests are commonly advocated as a key management option to mitigate the effects of agriculture on headwater stream biodiversity and ecosystem functions. However, the benefits of riparian forests might be reduced by uninterrupted catchment-scale pollution.</p> <p>2.We studied the effects of riparian land use on multiple ecological endpoints in headwater streams in an agricultural landscape. We studied stream habitat characteristics, water temperature and algal accrual, and macrophyte, benthic macroinvertebrate and fish communities in 11 paired forested and open agricultural headwater stream reaches that differed in their extent of riparian forest cover but had similar water quality.</p> <p>3. Hydromorphological habitat quality was higher in forested reaches than in open reaches. Riparian forest had a strong effect on the summer water temperature regime, with maximum and mean water temperatures and temperature variation in forested reaches substantially lower than in open reaches.</p> <p>4. Macrophyte communities differed between forested and open reaches. The mean abundance of bryophytes was higher in forested reaches but the difference to open reaches was only marginally significant, whereas graminoids were significantly more abundant in open reaches. Within-stream dissimilarity of benthic macroinvertebrate community structure was significantly related to the difference in riparian land use between reach pairs. The relative DNA sequence abundance of pollution-sensitive EPT (Ephemeroptera, Plecoptera, Trichoptera) species tended to be higher in forested reaches than in open reaches. Finally, fish densities were not significantly different between forested and open reaches, although densities were higher in forested reaches.</p> <p>5. This unequivocal evidence for the ecological benefits of forested riparian reaches in agricultural headwater streams suggests that riparian forest can partly mitigate the adverse impacts of agricultural diffuse pollution on biota. The strong effect of forests on stream water temperature suggest that riparian forest could also mitigate harmful effects on headwater stream biodiversity and ecosystem functions of the predicted more frequent high summer temperatures. </p>
Data from: Unravelling the role of allochthonous aquatic resources to food web structure in a tropical riparian forest
1. The role of matter and energy flow across ecosystem boundaries for subsidized consumer populations is well known. However, little is known on the effects of allochthonous subsidies on food web structure and trophic niche dimensions of consumers in the tropics. 2. We excluded allochthonous aquatic insects from tropical streams using greenhouse-type exclosures to test the influence of aquatic allochthonous subsidies on the trophic structure and niche dimensions of terrestrial predators using stable isotope methods. 3. In exclosure treatments, abundance and biomass of terrestrial predators, and biomass of phytophages, decreased and increased, respectively. Vegetation-living predators were more responsive to allochthonous inputs than those living on the ground. Overall, lower availability of allochthonous inputs did not affect community-wide metrics and niche width of predators. However, the niche width of some spider families had very low overlap between treatments, and others had wider isotopic niches in the control than exclusion treatment. Most of the C and N in predators living in control stretches came from aquatic subsidies, and those predators living in exclusion treatments switched their diets to terrestrial sources, showing a preference of predators for allochthonous subsidies. 4. Our results suggest that allochthonous subsidies are also relevant to tropical fauna living upon vegetation. Moreover, allochthonous resources may amplify the niche dimension of certain predators, or considerably change the trophic niche of others. Our study highlights the importance of including modern isotopic tools in elucidating the role of allochthonous resources on the patterns of trophic structure and niche dimensions of consumers from donor ecosystems.
Data from: Functional redundancy in bird community decreases with riparian forest width reduction
1. Riparian ecosystems are suffering anthropogenic threats that reduce biodiversity and undermine ecosystem services. However, there is a great deal of uncertainty about the way species composition of assemblages is related to ecosystem function, especially in a landscape fragmentation context. 2. Here we assess the impact of habitat loss and disturbance on Functional Diversity (FD) components Functional Redundancy (FRed), Functional Evenness (FEve) and Functional Richness (FRic) of riparian forest bird assemblages to evaluate (1) how FD components respond to riparian forest width reduction and vegetation disturbance; (2) the existence of thresholds within these relationships; (3) which of the main birds diet guild (frugivores, insectivores and omnivores) respond to such thresholds. We predict that FD components will be affected negatively and non-linearly by riparian changes. However, guilds could have different responses due to differences of species sensitivity to fragmentation and disturbance. We expect to find thresholds in FD responses, because fragmentation and disturbance drive loss of specific FD components. 3. Our results show that FRed and FEve were linearly affected by width and disturbance of riparian habitats, respectively. FRed was significantly lower in riparian forests assemblages below 400 m wide and FEve was significantly higher above 60% disturbance. These responses of FD were also followed to the decline in insectivores and frugivores richness in riparian forests most affected by these changes. 4. Consequently, our study suggests communities do not tolerate reduction in riparian forest width or disturbance intensification without negative impact on FD, and this becomes more critical for riparian area less than 400 m wide or with more than 60% disturbance. This minimum riparian width required to maintain FRed is greater than the minimum width required for riparian forests by Brazilian law. Thus, is important to consider mechanisms to expand riparian habitats and reduce the disturbance intensity in riparian forests so that riparian bird community FD may be effectively conserved.
Productivity of riparian Populus forests: satellite assessment along a prairie river with an environmental flow regime
<p>In semi-arid regions, the growth and survival of cottonwoods (riparian Populus species) depend on river water supplementing the limited precipitation. Indicators of growth and productivity are needed to assess how altered streamflow regimes on regulated rivers impact cottonwood trees and the riparian forest ecosystems they support. Satellite imagery from the Landsat program was used to make historical assessments of ecosystem productivity in a riparian cottonwood forest along a regulated prairie river in southern Alberta, Canada from 1984 to 2020, with an environmental flow regime that increased the minimum flows implemented in 1993. A version of the near-infrared reflectance of vegetation scaled with incoming sunlight (NIRvP) was calculated from Landsat images to provide a proxy for primary production. NIRvP was validated against gross primary production measurements from eddy covariance and cottonwood basal area increment measurements from tree ring analyses. Streamflow and weather data were used to assess what environmental conditions drive year-to-year variations in NIRvP.</p>
Investigating the effects of retaining riparian forest buffer zones of differing width on stream channel geomorphology
<b>Description: </b><p>To monitor temporal stream shape change over a gradient of RBZ widths, channel cross section measurements were continued at preestablished points that have been present since 2011. The points are marked with 0.4-metre-long PVC pipes that are spray painted yellow for easier identification and surrounding bedrock or roots are also marked at the exact location of the pipes in case a pipe should be eroded away in future. Channel cross sections were calculated using a standardised method. Cross- sectional area (CSA) measurement was repeated for every pre-established cross section point along the stream. These were located 250 m apart and numbered 4- 10, depending on the accessibility of the trails upstream. The stream with a '0 metre' buffer, for instance, had only four measurement points due to a steep waterfall which could not be passed. The CSA of these stream points were re-measured on a yearly basis in 2011 - 2014, 2018 and 2019.</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/210"><b>Investigating the effects of retaining riparian forest buffer zones of differing width on stream channel geomorphology. </b></a></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3476390">here</a></p><p><b>Files: </b>This consists of 1 file: Template_cross_sections.xlsx</p><p><b>Template_cross_sections.xlsx</b></p><p>This file contains dataset metadata and 1 data tables:</p><ol><li><p><b>Stream cross section measurements</b> (described in worksheet CrossSections)</p><p>Description: Cross section measurements</p><p>Number of fields: 7</p><p>Number of data rows: 8377</p><p>Fields: </p><ul><li><b>Identity</b>: Original site label in field data (Field type: id)</li><li><b>Stream</b>: Stream transect (Field type: location)</li><li><b>Site</b>: Location of stream cross section (Field type: location)</li><li><b>DistanceAcross</b>: Distance across the stream at which the measurement was taken (Field type: numeric)</li><li><b>Height</b>: Stream depth (Field type: numeric)</li><li><b>BaseMaterial</b>: Ground cover at the measurement point (Field type: categorical)</li><li><b>Date</b>: Date cross section was measured (Field type: date)</li></ul></li></ol><p><b>Date range: </b>2011-01-12 to 2019-03-30</p><p><b>Latitudinal extent: </b>4.6314 to 4.7345</p><p><b>Longitudinal extent: </b>117.4554 to 117.6414</p>
Data from: Effects of riparian forest harvest on streams: a meta-analysis
1. Riparian forest harvesting impacts streams in many ways, from altering temperature regimes, shifting geomorphic structure, increasing sediment fluxes and affecting fish populations. However, we have noted considerable variation in the results between studies that led us to ask whether the effects of forest harvesting on streams were consistent between studies. We used meta-analysis of 34 replicated studies to address the effects of riparian logging on biological and chemical components of streams in contrast to control sites. 2. We found that the overall effect sizes of several response variables in replicated studies were significantly higher than zero, especially benthic invertebrates, and nitrogen and potassium concentrations. However, there was a very large amount of variation in the effect sizes between studies, and for many measures, the effect sizes from different studies were positive or negative, indicating site-specific responses. 3. We explored whether stream size, stream gradient and regional potential evapotranspiration could explain some of the effect size variation between studies. Relations with these environmental variables were weak, but suggestive that some of the context-specific, individual outcomes might be due to underlying environmental differences between sites. 4. Synthesis and applications. Despite relatively low numbers of replicated studies, we found significant overall effects of riparian forest harvesting although the magnitude and direction of responses within individual studies were site specific. This lack of consistency in the direction of effect sizes suggests we need a more context-dependent approach to the protection of freshwaters from forest management.
FIGURE 1 in Forestiera veracruzana (Oleaceae), a new species from the riparian forests of central Veracruz, Mexico
FIGURE 1. Collection localities of Forestiera veracruzana sp. nov.
Productivity of riparian Populus forests: satellite assessment along a prairie river with an environmental flow regime
Open the record for dataset details and reuse information.
Data from: Effects of riparian forest harvest on streams: a meta-analysis
Open the record for dataset details and reuse information.
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.