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17 results for “patch occupancy”
Patch occupancy of stream fauna across a land cover gradient in the southern Appalachians, USA
Field sampling of four functionally important focal stream consumers within the Little Tennessee River Basin took place in thirty-seven stream reaches between May - July 2009. Sampled reaches all drained an area less than 17 km2, and land cover varied among these reaches. This data was used to model patch occupancy to examine factors that best predicted the prevalence of the four groups.
Patch occupancy sampling of invertebrates and salamanders from Coweeta Synoptic sampling sites located in the Upper Little Tennessee River Basin, 2009 to 2012.
This research was conducted in Macon County, North Carolina, as part of the Coweeta LTER synoptic sampling program. In the summers of 2009-2012 we sampled and counted Tallaperla species, Elimia species, fish, and salamanders found in a 150meter stretch at the synoptic sites, a total of 44 sites. The 150meter stretch was divided into thirty 5meter plots that were sampled on three occasions each year of sampling; in 2009 all 44 sites were sample, in 2010 a subset of 8 sites were sampled, in 2011 a subset of 9 sites were sampled, and in 2012 a subset of 8 sites were sampled.
A plumage patch signaling occupancy is shaped by social environment
Open the record for dataset details and reuse information.
Predicting patch occupancy reveals the complexity of host range expansion
<p>Specialized plant-insect interactions are a defining feature of life on earth, yet we are only beginning to understand the factors that set limits on host ranges in herbivorous insects. To better understand the recent adoption of alfalfa as a host plant by the Melissa blue butterfly, we quantified arthropod assemblages and plant metabolites across a wide geographic region, while controlling for climate and dispersal inferred from population genomic variation. The presence of the butterfly is successfully predicted by direct and indirect effects of plant traits and interactions with other species. Results are consistent with the predictions of a theoretical model of parasite host range in which specialization is an epiphenomenon of the many barriers to be overcome rather than a consequence of trade-offs in developmental physiology.</p>
Data from: A model for non-equilibrium metapopulation dynamics utilizing data on species occupancy, patch ages and landscape history
1. The distribution pattern of many species reflects the past rather than the current structure of landscapes. Consequently, species are most often not in equilibrium with the current landscape structure. Yet this is a well-known fact, there is no appropriate approach to estimate the colonization rate of non-equilibrium species based on only data on the species occurrence pattern in the landscape. 2. We present an approach to estimate the colonization rate of non-equilibrium metapopulations. The approach requires only data on species presence/absence among its patches (occurrence pattern), data on patch ages and data on the historic distribution of the patches in the landscape. By estimating the past occurrence patterns and colonization events leading to the current pattern of occupied and non-occupied patches, we estimate the colonization rate, including the dispersal kernel. We also show how to estimate effects of local patch conditions and how to include an independent estimate of the local extinction rate based on other data. We use nine epiphytic lichen species confined to beech trees to illustrate the method. 3. Five species had restricted dispersal range, between 200 and 4700 m, and their colonization rate decreased with increasing fragmentation. Species colonization rates were related to niche width. Among the demographic parameters, the force of colonization was more important than the dispersal range in explaining the colonization rates. Local patch conditions did not explain the colonization probability of any species. In metapopulation projections that did not account for restricted dispersal range, higher future metapopulation sizes were projected. 4. Synthesis. The presented approach uses data on only species occurrence, patch age and landscape history to estimate the species colonization rate and dispersal kernel. It can also utilize independent data on local extinction rate. Rather than identifying factors explaining the occurrence pattern, the model estimates the rate of change in the occurrence pattern. This dynamic modelling allows testing general and applied questions on the dynamics or viability of metapopulations of sessile species. The approach is applicable for species whose distribution pattern reflects the past rather than the current landscape structure, e.g. certain epiphytes and ground-floor plants.
FIGURE 9. A in An investigation of patch occupancy and dispersal by third to final instar nymphs of Brachytrupes megacephalus Lefèbvre, 1827 (Orthoptera: Gryllidae: Gryllinae) across the sand dune biotope at the Għadira Nature Reserve, Malta
FIGURE 9. A stridulating male at the mouth of its burrow. The wide mouth of the burrow serves as an 'acoustic chamber' for amplification (Photo: J.J. Borg).
FIGURE 8 in An investigation of patch occupancy and dispersal by third to final instar nymphs of Brachytrupes megacephalus Lefèbvre, 1827 (Orthoptera: Gryllidae: Gryllinae) across the sand dune biotope at the Għadira Nature Reserve, Malta
FIGURE 8. Correlation between atmospheric pressure and the count interval (difference in the count between successive, weekly observation periods) with trendlines for all points (grey) and when not considering the only outlier (blue).
FIGURE 1 in An investigation of patch occupancy and dispersal by third to final instar nymphs of Brachytrupes megacephalus Lefèbvre, 1827 (Orthoptera: Gryllidae: Gryllinae) across the sand dune biotope at the Għadira Nature Reserve, Malta
FIGURE 1. Aerial image of the area of study and its surrounding terrain (Source: Google Earth—imagery 23/5/2021).
FIGURE 6 in An investigation of patch occupancy and dispersal by third to final instar nymphs of Brachytrupes megacephalus Lefèbvre, 1827 (Orthoptera: Gryllidae: Gryllinae) across the sand dune biotope at the Għadira Nature Reserve, Malta
FIGURE 6. Sustained wind speed (main chart) and accompanying wind gusts (inset) are practically aligned, which indicates a quasi-constant wind during observation periods.
FIGURE 7. Humidity chart across observation periods with a range varying from 75 in An investigation of patch occupancy and dispersal by third to final instar nymphs of Brachytrupes megacephalus Lefèbvre, 1827 (Orthoptera: Gryllidae: Gryllinae) across the sand dune biotope at the Għadira Nature Reserve, Malta
FIGURE 7. Humidity chart across observation periods with a range varying from 75% to 94%. Notwithstanding the high level of humidity registered on some days, no precipitation was recorded during or immediately prior to field sessions.
FIGURE 3 in An investigation of patch occupancy and dispersal by third to final instar nymphs of Brachytrupes megacephalus Lefèbvre, 1827 (Orthoptera: Gryllidae: Gryllinae) across the sand dune biotope at the Għadira Nature Reserve, Malta
FIGURE 3. Abundance across the eleven weeks of field observations on the area of study and its immediate surroundings.
FIGURE 2 in An investigation of patch occupancy and dispersal by third to final instar nymphs of Brachytrupes megacephalus Lefèbvre, 1827 (Orthoptera: Gryllidae: Gryllinae) across the sand dune biotope at the Għadira Nature Reserve, Malta
FIGURE 2. The high concentration of individuals on the sand dune biotope patch devoid of trees demonstrates a preference for such habitat conditions (each orange dot represents a single sighting record).
Data from: A model for non-equilibrium metapopulation dynamics utilizing data on species occupancy, patch ages and landscape history
Open the record for dataset details and reuse information.
Predicting patch occupancy reveals the complexity of host range expansion
Open the record for dataset details and reuse information.
FIGURE 10. A in An investigation of patch occupancy and dispersal by third to final instar nymphs of Brachytrupes megacephalus Lefèbvre, 1827 (Orthoptera: Gryllidae: Gryllinae) across the sand dune biotope at the Għadira Nature Reserve, Malta
FIGURE 10. A multifaceted approach for the conservation of Brachytrupes megacephalus (Photo inset: J.J. Borg).
FIGURE 5. Air temperature for observation periods 1–10 in An investigation of patch occupancy and dispersal by third to final instar nymphs of Brachytrupes megacephalus Lefèbvre, 1827 (Orthoptera: Gryllidae: Gryllinae) across the sand dune biotope at the Għadira Nature Reserve, Malta
FIGURE 5. Air temperature for observation periods 1–10; the highest nymph count was that of 77 individuals (OP5) and the lowest was that of 11 individuals (OP8).
FIGURE 4 in An investigation of patch occupancy and dispersal by third to final instar nymphs of Brachytrupes megacephalus Lefèbvre, 1827 (Orthoptera: Gryllidae: Gryllinae) across the sand dune biotope at the Għadira Nature Reserve, Malta
FIGURE 4 (A–J). Heat maps based on weekly observation data of Brachytrupes megacephalus third, fourth and fifth instar nymphs at their respective burrow entrance—area of study: sand dune, Għadira Nature Reserve.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.