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27 results for “human-modified landscapes”
Human-modified landscapes provide key foraging areas for a threatened flying mammal: the grey-headed flying-fox
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Data from: The ecology and economics of shorebird conservation in a tropical human-modified landscape
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Data from: Assessing the distribution of disease-bearing rodents in human-modified tropical landscapes
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Data from: Forest fragmentation alters winter microclimates and microrefugia in human-modified landscapes
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Investigating the Distribution and Occupancy of Otter Species across Human-modified Landscapes in Sabah, Malaysia.
<b>Description: </b><p>A study on the occupancy of otters in streams across land-use gradient, within four habitat treatments: logged forest (LF), heavily degraded forest (HDF), riparian reserves within oil palm plantation (RR), and oil palm plantation (ROP).</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/171"><b>Investigating the Occupancy & Habitat Use of Tropical Otters Across Human Modified Landscapes in SAFE Project, Kalabakan, Sabah.</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>Universiti Malaysia Sabah (Studentship)</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 2016/56)</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=3897377">here</a></p><p><b>Files: </b>This consists of 1 file: Otter_Data_Annabel_Pianzin.xlsx</p><p><b>Otter_Data_Annabel_Pianzin.xlsx</b></p><p>This file contains dataset metadata and 3 data tables:</p><ol><li><p><b>Otter occupancy</b> (described in worksheet Otter_Occupancy)</p><p>Description: Otter occupancy</p><p>Number of fields: 12</p><p>Number of data rows: 36</p><p>Fields: </p><ul><li><b>site</b>: Location within the SAFE landscape (Field type: location)</li><li><b>subtransect_ID</b>: Point ID (Field type: id)</li><li><b>treatment</b>: Habitat type (Field type: categorical)</li><li><b>oc1</b>: Presence absence of otter (Field type: abundance)</li><li><b>oc2</b>: Presence absence of otter (Field type: abundance)</li><li><b>oc3</b>: Presence absence of otter (Field type: abundance)</li><li><b>oc4</b>: Presence absence of otter (Field type: abundance)</li><li><b>spraint</b>: Visual observation of spraint (Field type: abundance)</li><li><b>footprint</b>: Visual observation of otter footprint (Field type: abundance)</li><li><b>taxa</b>: Species detected at the site (Field type: taxa)</li><li><b>A.cinereus</b>: Presence absence of otter (Field type: abundance)</li><li><b>L.perspicillata</b>: Presence absence of otter (Field type: abundance)</li></ul></li><li><p><b>Occupancy Survey Date</b> (described in worksheet Occupancy_Survey_Date)</p><p>Description: Occupancy_Survey_Date</p><p>Number of fields: 7</p><p>Number of data rows: 36</p><p>Fields: </p><ul><li><b>site</b>: Location within the SAFE landscape (Field type: location)</li><li><b>subtransect_ID</b>: Point ID (Field type: id)</li><li><b>treatment</b>: Habitat type (Field type: categorical)</li><li><b>oc1_date</b>: Date of survey (Field type: date)</li><li><b>oc2_date</b>: Date of survey (Field type: date)</li><li><b>oc3_date</b>: Date of survey (Field type: date)</li><li><b>oc4_date</b>: Date of survey (Field type: date)</li></ul></li><li><p><b>Habitat covariates</b> (described in worksheet Habitat_Covariates)</p><p>Description: Habitat covariates</p><p>Number of fields: 20</p><p>Number of data rows: 36</p><p>Fields: </p><ul><li><b>site</b>: Location within the SAFE landscape (Field type: location)</li><li><b>point_ID</b>: Point ID (Field type: id)</li><li><b>treatment</b>: Habitat type (Field type: categorical)</li><li><b>width</b>: Stream width (Field type: numeric)</li><li><b>depth</b>: Stream depth (Field type: numeric)</li><li><b>altitude</b>: Altitude of site (Field type: numeric)</li><li><b>stmedge</b>: Width of stream edge (Field type: numeric)</li><li><b>canco</b>: Stream canopy cover (Field type: numeric)</li><li><b>ugro</b>: Undergrowth cover (Field type: numeric)</li><li><b>bankco</b>: Bank canopy cover (Field type: numeric)</li><li><b>bk.rock</b>: Bank rock cover (Field type: numeric)</li><li><b>bk.soil</b>: Bank soil cover (Field type: numeric)</li><li><b>bk.both</b>: Bank soil and rock cover (Field type: numeric)</li><li><b>no.tree</b>: Number of trees (Field type: numeric)</li><li><b>no.log</b>: Number of logs (Field type: numeric)</li><li><b>fquality</b>: Forest quality (Field type: numeric)</li><li><b>bankheight</b>: Bank height (Field type: numeric)</li><li><b>bankdbh</b>: Bank diatmeter at breast height (Field type: numeric)</li><li><b>human</b>: Distance from human settlements (Field type: numeric)</li><li><b>estate</b>: Distance from oil palm estate (Field type: numeric)</li></ul></li></ol><p><b>Date range: </b>2017-02-22 to 2019-06-03</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> -  -  -  -  Carnivora <br> -  -  -  -  -  Mustelidae <br> -  -  -  -  -  -  <i>Lutrogale</i> <br> -  -  -  -  -  -  -  <i>Lutrogale perspicillata</i> <br> -  -  -  -  -  -  <i>Aonyx</i> <br> -  -  -  -  -  -  -  <i>Aonyx cinereus</i> <br></div><p></p>
Data from: Trade-offs for butterfly alpha and beta diversity in human-modified landscapes and tropical rainforests
The accelerating expansion of human populations and associated economic activity across the globe have made maintaining large, intact natural areas increasingly challenging. The difficulty of preserving large intact landscapes in the presence of growing human populations has led to a growing emphasis on landscape approaches to biodiversity conservation with a complementary strategy focused on improving conservation in human-modified landscapes. This, in turn, is leading to intense debate about the effectiveness of biodiversity conservation in human-modified landscapes and approaches to better support biodiversity in those landscapes. Here, we compared butterfly abundance, alpha richness, and beta diversity in human-modified landscapes [urban, sugarcane] and natural, forested areas to assess the conservation value of human-modified landscapes within the Wet Tropics bioregion of Australia. We used fruit-baited traps to sample butterflies and analyzed abundance and species richness in respective land uses over a one-year period. We also evaluated turnover and spatial variance components of beta diversity to determine the extent of change in temporal and spatial variation in community composition. Forests supported the largest numbers of butterflies, but were lowest in each, alpha species richness, beta turnover, and the spatial beta diversity. Sugarcane supported higher species richness, demonstrating the potential for conservation at local scales in human-modified landscapes. In contrast, beta diversity was highest in urban areas, likely driven by spatial and temporal variation in plant composition within the urban landscapes. Thus, while improving conservation on human-modified landscapes may improve local alpha richness, conserving variation in natural vegetation is critical for maintaining high beta diversity.
Data from: Trade-offs for butterfly alpha and beta diversity in human-modified landscapes and tropical rainforests
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