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6,569 results for “Long-term”
Figure 4 in A long-term survey of spring monarch butterflies in north-central Florida
Figure 4. Development of Asclepias humistrata at Cross Creek (data for 1997–2017; no counts for 2000 and 2003). Plants without any flower development are excluded. Maximum flowering occurred the week of 12–18 April. Based on 11,707 observations.
Figure 8. Adults captured per hour averaged for the four central weeks, 22 March–18 April, from 1994–2017. Data were not available for 1997, 1999–2001 in A long-term survey of spring monarch butterflies in north-central Florida
Figure 8. Adults captured per hour averaged for the four central weeks, 22 March–18 April, from 1994–2017. Data were not available for 1997, 1999–2001, and 2003–2004.
Figure 3 in A long-term survey of spring monarch butterflies in north-central Florida
Figure 3. Stages of development of Asclepius humistrata. (a) Indeterminate (without reproductive organs, 24 April 2010); (b) early bud (immature flower buds visible outside terminal leaves, 3 April 2012); (c) bud (mature flower buds, 26 March 2009); (d) flowering (8 May 2010); (e) pod (fully mature seed pods, 19 May 2010); (f) post-pod (senesced pods that have released their seeds, 26 May 2010); (g) frost damaged plant (9 April 2009); (h) fifth instar Danaus plexippus on a flowering plant (24 April 1996). Photos by L.P. Brower, K. Sims Dunford, and M. Standridge.
Figure 2. Bubble plot showing diamondback terrapin clutch sizes recorded 1998–2012 in Long-term increases in clutch size in common snapping turtles (Chelydra serpentina) and diamondback terrapins (Malaclemys terrapin)
Figure 2. Bubble plot showing diamondback terrapin clutch sizes recorded 1998–2012. Bubble size indicates the number of clutches of the same size.
Figure 1. Bubble plot showing snapping turtle clutch sizes recorded 2004–2015 in Long-term increases in clutch size in common snapping turtles (Chelydra serpentina) and diamondback terrapins (Malaclemys terrapin)
Figure 1. Bubble plot showing snapping turtle clutch sizes recorded 2004–2015. Bubble size indicates the number of clutches of the same size.
Long-term changes in occurrence, relative abundance, and reproductive fitness of bat species in relation to arrival of White-nose Syndrome in West Virginia, USA
<p>White-nose syndrome (WNS) is a disease caused by the fungus Pseudogymnoascus destructans which has resulted in the deaths of millions of bats across eastern North America. To date, hibernacula counts have been the predominant means of tracking the spread and impact of this disease on bat populations. However, an understanding of the impacts of WNS on demographic parameters outside the winter season is critical to conservation and recovery of bat populations impacted by this disease. We used long-term monitoring data to examine WNS-related impacts to summer populations in West Virginia, where WNS has been documented since 2009. Using capture data from 290 mist-net sites surveyed from 2003–2019 on the Monongahela National Forest, we estimated temporal patterns in presence and relative abundance for each bat species. For species that exhibited a population-level response to WNS, we investigated post-WNS changes in adult female reproductive state and body mass. Myotis lucifugus (little brown bat), M. septentrionalis (northern long-eared bat), and Perimyotis subflavus (tri-colored bat) all showed significant decreases in presence and relative abundance during and following the introduction of WNS, while Eptesicus fuscus (big brown bat) and Lasiurus borealis (eastern red bat) responded positively during the WNS invasion. Probability of being reproductively active was not significantly different for any species, though a shift to earlier reproduction was estimated for E. fuscus and M. septentrionalis. For some species, body mass appeared to be influenced by the WNS invasion, but the response differed by species and reproductive state. Results suggest that continued long-term monitoring studies, additional research into impacts of this disease on the fitness of WNS survivors, and a focus on providing optimal non-wintering habitat may be valuable strategies for assessing and promoting recovery of WNS-affected bat populations.</p>
Both real-time and long-term environmental data perform well in predicting shorebird distributions in managed habitat
<p>Highly mobile species, such as migratory birds, respond to seasonal and inter-annual variability in resource availability by moving to better habitats. Despite the recognized importance of resource thresholds, species distribution models typically rely on long-term average habitat conditions, mostly because large-extent, temporally-resolved, environmental data are difficult to obtain. Recent advances in remote sensing make it possible to incorporate more frequent measurements of changing landscapes; however, there is often a cost in terms of model building and processing and the added value of such efforts is unknown. Our study tests whether incorporating real-time environmental data increases the predictive ability of distribution models, relative to using long-term average data. We developed and compared distribution models for shorebirds in California's Central Valley based on high temporal resolution (every 16-days), and 17-year long-term average, surface water data. Using abundance-weighted boosted regression trees, we modeled monthly shorebird occurrence as a function of surface water availability, crop type, wetland type, road density, temperature, and bird data source. While modeling with both real-time and long-term average data provided good fit to withheld validation data (0.79 < AUC < 0.89 across taxa), there were small differences in model performance. The best models incorporated long-term average conditions and spatial pattern information for real-time flooding (e.g. perimeter-area ratio of real-time water bodies). There was not a substantial difference in the performance of real-time and long-term average data models within time periods when real-time surface water differed substantially from the long-term average (specifically during drought years 2013-2016) and in intermittently flooded months or locations. Spatial predictions resulting from the models differed most in the southern region of the study area where there is lower water availability, fewer birds, and lower sampling density. Prediction uncertainty in the southern region of the study area highlights the need for increased sampling in this area. Because both sets of data performed similarly, the choice of which data to use may depend on the management context. Real-time data may ultimately be best for guiding dynamic, adaptive conservation actions whereas models based on long-term averages may be more helpful for guiding permanent wetland protection and restoration. --</p>
Fig. 2 in A Solar-Powered UV Light Trap for Long-Term Monitoring of Insects in Remote Habitats
Fig. 2. The solar-powered UV light trap in A) stabilized-vegetated sands, B) open sand dunes, and C) agricultural crop margin. Note that in addition to the components in Fig. 1, 6–8 ft (1.8–2.4 m) pieces of steel rebar and wire are used to position the solar panel.
Fig. 1 in A Solar-Powered UV Light Trap for Long-Term Monitoring of Insects in Remote Habitats
Fig. 1. Exploded view of solar-powered UV light trap, with component labels corresponding to the items in Table 1. The light trap components battery (n), ballast box (a), photoelectric switch (g), and battery clamps (l) were put inside a second bucket to protect them from corrosion and overheating.
Capturing the dynamics of small populations: A retrospective assessment using long-term data for an island reintroduction
<p>1. The art of population modelling is to incorporate factors essential for capturing a population's dynamics while otherwise keeping the model as simple as possible. However, it is unclear how optimal model complexity should be assessed, and whether this optimal complexity has been affected by recent advances in modelling methodology. This issue is particularly relevant to small populations because they are subject to complex dynamics but inferences about those dynamics are often constrained by small sample sizes.</p> <p>2. We fitted Bayesian hierarchical models to long-term data on vital rates (survival and reproduction) for the toutouwai (Petroica longipes) population reintroduced to Tiritiri Matangi, a 220-ha New Zealand island, and quantified the performance of those models in terms of their likelihood of replicating the observed population dynamics. These dynamics consisted of overall growth from 33 (± 0.3) to 160 (± 6) birds from 1992–2018, including recoveries following five harvest events for further reintroductions to other sites.</p> <p>3. We initially included all factors found to affect vital rates, which included inbreeding, post-release effects, density-dependence, sex, age and random annual variation, then progressively removed these factors. We also compared performance of models where data analysis and simulations were done simultaneously to those produced with the traditional two-step approach, where vital rates are estimated first then fed into a separate simulation model. Parametric uncertainty and demographic stochasticity were incorporated in all projections.</p> <p>4. The essential factors for replicating the population's dynamics were density-dependence in juvenile survival and post-release effects, i.e. initial depression of survival and reproduction in translocated birds. Inclusion of other factors reduced the precision of projections, and therefore the likelihood of matching observed dynamics. However, this reduction was modest when the modelling was done in an integrated framework. In contrast, projections were much less precise when done with a two-step modelling approach, and the cost of additional parameters was much higher under the two-step approach.</p> <p>5. These results suggest that minimization of complexity may be less important than accounting for covariances in parameter estimates, which is facilitated by integrating data analysis and population projections using Bayesian methods. 13-Aug-2021 --</p>
Data from: Dispersal limitations and long-term persistence drive differentiation from haplotypes to communities within a tropical sky-island: evidence from community metabarcoding
<p>Neutral theory proposes that dispersal stochasticity is one of the main drivers of local diversity. Haplotypes-level genetic variation can now be efficiently sampled from across whole communities, thus making it possible to test neutral predictions from the genetic to species-level diversity, and higher. However, empirical data is still limited, with the few studies to date coming from temperate latitudes. Here, we focus on a tropical mountain within the Transmexican Volcanic Belt to evaluate spatially fine-scale patterns of arthropod community assembly to understand the role of dispersal limitation and landscape features as drivers of diversity. We sampled whole-communities of arthropods for eight orders at a spatial scale ranging from 50 m to 19 km, using <span>whole community metabarcoding. We explored multiple hierarchical levels, from individual haplotypes to lineages at 0.5, 1.5, 3, 5, 7.5% similarity thresholds, to evaluate patterns of richness, turnover,</span><span> and distance decay of similarity </span><span>with isolation-by-distance and isolation-by-resistance (</span><span>costs to dispersal given by landscape features</span><span>) approaches. </span><span>Our results showed that distance and altitude influence distance decay of similarity at all hierarchical levels. This holds for arthropod groups of contrasting dispersal abilities, but with different strength depending on the spatial scale. Our results support a model where local-scale differentiation mediated by dispersal constraints, combined with long-term persistence of lineages, is an important driver of diversity within tropical sky islands.</span></p>
Long-term changes in flowering synchrony reflect climatic changes across an elevational gradient
<p>These are the data with the accompanying R code used in the article "Long-term changes in flowering synchrony reflect climatic changes across an elevational gradient", by Fisogni A, de Manincor N, Bertelsen CD, and Rafferty NE.</p> <p>We provide the raw data on flowering phenology, temperature and precipitation data in the study area, and overlap estimates used to evaluate temporal changes within and between elevations and their relationship with changing climatic variables.</p> <p>Data are .txt files with tab separated values.</p> <p>The raw dataset was created by C. David Bertelsen from field observations performed from 1984 to 2019 along a fixed transect in the Santa Catalina Mountains, Arizona, USA.</p>
Long-term snow chemical composition monitoring - Ariebreen glacier (Hornsund) - raw data
<p>Since 2020, snow samples have been taken from the Ariebreen glacier several times a season during the accumulation season. The snow samples are collected in polyethylene sterile bags and transported to the Polish Polar Station Hornsund. After melting at room temperature, they are analysed in the chemical laboratory of the Polish Polar Station for pH, conductivity and chemical composition (major ions).<br> <br> Site Information Ariebreen - 0.5 km long glacier between Skoddefjellet and the northern part of Ariekammen, southernmost in Wedel Jarlsberg Land.</p> <p>Presented data from 2020 to 2022</p> <p>The data has not been checked, which means that it is raw data.</p> <p>Principal investigator (PI) Adam Nawrot</p>
Hygro-thermo-mechanical model for concrete pavement from an early age to a long-term performance
<p>A new 3D hygro-thermo-mechanical model for a concrete pavement slab is formulated, capturing its behavior from casting to long-term drying. The model includes a microprestress-solidification viscoelastic model for concrete ageing creep. Calibrations and validations are based on lab experiments and a four year continuous monitoring of a real highway slab. The results show that slab drying leads to the highest principal tensile stress on the surface as high as 3.5 MPa. Simulated temperature cycles and traffic loading yield smaller stresses. In this regard, concrete crack resistance during drying should be considered in material and structural design.</p>
Victorian Water and Climate dataset: long-term streamflow, climate, and vegetation observation records and catchment attributes
<p>This dataset contains streamflow, climate, and vegetation data for 155 minimally impaired catchments in Victoria, Australia. </p> <p>What's included:</p> <p>- Streamflow long-term observation records in daily, monthly, and hydroannual (based on March to February water year) resolution</p> <p>- Catchment climate characteristics in daily, monthly, and hydroannual resolution</p> <p>- Catchment vegetation characteristics in monthly resolution and actual evapotranspiration estimate in monthly and hydroannual resolution</p> <p>- Catchment boundaries</p> <p>- Catchment attributes (topographic, geological, soil, groundwater, vegetation, and human impacts characteristics)</p> <p>- Hydroclimatic characteristics for 3 different periods.</p> <p>Precipitation (p), streamflow (q), and PET (pet) data and their derivatives are in mm (i.e. normalised by catchment area). </p> <p>A paper containing a detailed description of the data including units, data sources, and processing details is submitted, please contact Margarita Saft for a private copy of the draft.</p>
The climatic drivers of long-term population changes in rainforest montane birds
<p>Climate-driven biodiversity erosion is escalating at an alarming rate. The pressure imposed by climate change is exceptionally high in tropical ecosystems, where species adapted to narrow environmental ranges exhibit strong physiological constraints. Despite the observed detrimental effect of climate change on ecosystems at a global scale, our understanding of the extent to which multiple climatic drivers affect population dynamics is limited. Here, we disentangle the impact of different climatic stressors on 47 rainforest birds inhabiting the mountains of the Australian Wet Tropics using hierarchical population models. We estimate the effect of spatiotemporal changes in temperature, precipitation, heatwaves, droughts, and cyclones on the population dynamics of rainforest birds between 2000–2016. We find a strong effect of warming and changes in rainfall patterns across the elevational-segregated bird communities, with lowland populations benefiting from increasing temperature and precipitation, while upland species show an inverse strong negative response to the same drivers. Additionally, we find a negative effect of heatwaves on lowland populations, a pattern associated with the observed distribution of these extreme events across elevations. In contrast, cyclones and droughts have a marginal effect on spatiotemporal changes in rainforest bird communities, suggesting a species-specific response unrelated to the elevational gradient. This study demonstrated the importance of unravelling the drivers of climate change impacts on population changes, providing significant insight into the mechanisms accelerating climate-induced biodiversity degradation.</p>
(11)-Strobl2023A-DS0001--0010 – Ten Tribolium castaneum long-term live imaging datasets of embryonic development acquired with light sheet fluorescence microscopy
<p>(11)-Strobl2023A-DS0001--0010 – Ten <em>Tribolium castaneum</em> long-term live imaging datasets of embryonic development acquired with light sheet fluorescence microscopy</p>
Data from: Evidence of low within-pair genetic relatedness in a relict population of Thorn-tailed Rayadito despite long-term isolation
<p>Investigating whether mating patterns are biased in relation to kinship in isolated populations can provide a better understanding of the occurrence of inbreeding avoidance mechanisms in wild populations. Here we report on the genetic relatedness (<em>r</em>) among breeding pairs in a relict population of Thorn-tailed Rayadito (<em>Aphrastura spinicauda</em>) in north-central Chile that has experienced a long-term history of isolation. We used simulations based on eight years of data to assess whether mating is random with respect to relatedness. We found that mean and median population values of pair relatedness tended to be lower than randomly generated values, suggesting that mating is not random with respect to kinship. We hypothesize that female-biased dispersal is the main mechanism reducing the likelihood of mating among kin, and that the proportion of related pairs (i.e., <em>r </em>> 0.125) in the study population (25%) would presumably be higher in the absence of sex-biased dispersal. The occurrence of other mechanisms such as extra-pair copulations, delayed breeding and active inbreeding avoidance through kin discrimination cannot be dismissed and require further study.</p>
Synergistic effects of warming and internal nutrient loading interfere with the long-term stability of lake restoration and induce sudden re-eutrophication
<p><strong>This repository contains the dataset linked to the following publication:</strong></p> <p><strong>Article title: </strong>Synergistic effects of warming and internal nutrient loading interfere with the long-term stability of lake restoration and induce sudden re-eutrophication</p> <p><strong>Journal: </strong><em>Environmental Science & Technology</em></p> <p><strong>DOI</strong>: 10.1021/acs.est.2c07181</p> <p><strong>Abstract:</strong> Phosphorus (P) precipitation is among the most effective treatments to mitigate lake eutrophication. However, after a period of high effectiveness, studies have shown possible re-eutrophication and the return of harmful algal blooms. While such abrupt ecological changes were attributed to the internal P loading, the role of lake warming and its potential synergistic effects with internal loading, thus far, has been understudied. Here, in a eutrophic lake in central Germany, we quantified the driving mechanisms of the abrupt re-eutrophication and cyanobacterial blooms in 2016 (30 years after the first P precipitation). A process-based lake ecosystem model (GOTM-WET) was established using a high-frequency monitoring dataset covering contrasting trophic states. Model analyses suggested that the internal P release accounted for 68% of the cyanobacterial biomass proliferation, while lake warming contributed to 32%, including direct effects via promoting growth (18%) and synergistic effects via intensifying internal P loading (14%). The model further showed that the synergy was attributed to prolonged lake hypolimnion warming and oxygen depletion. Our study unravels the substantial role of lake warming in promoting cyanobacterial blooms in re-eutrophicated lakes. The warming effects on cyanobacteria via promoting internal loading need more attention in lake management, particularly for urban lakes.</p> <p><strong>SYNOPSIS: </strong>Warming synergistically promotes re-eutrophication with internal nutrient loading and exacerbates cyanobacterial blooms in urban lakes 30 years after phosphorus mitigation.</p> <p> </p> <p><strong>Data description </strong>by Xiangzhen Kong (<a href="mailto:xzkong@niglas.ac.cn">xzkong@niglas.ac.cn</a>), 2023-02-20</p> <p>---Wet chemical analysis on water samples taken at five depths (0.5, 2.5, 5.0, 7.0 and 9.0 m) from the deepest point in the lake (BA1) at biweekly intervals from 2018.5-2021.8.</p> <p> File name:</p> <ul> <li>BAB_BA1_TN_mgL.obs (total nitrogen concentration)</li> <li>BAB_BA1_NH4_mgL.obs (ammonium nitrogen concentration)</li> <li>BAB_BA1_NO3_mgL.obs (nitrate nitrogen concentration)</li> <li>BAB_BA1_TP_mgL.obs (total phosphorus concentration)</li> <li>BAB_BA1_SRP_mgL.obs (Soluble reactive phosphorus concentration)</li> <li>BAB_BA1_DP_mgL.obs (dissolved P concentration)</li> <li>BAB_BA1_DOC_mgL.obs (Dissolved organic carbon concentration)</li> <li>BAB_BA1_Si_mgL.obs (dissolved silicon concentration)</li> <li>BAB_BA1_Chla_HPLC_DIN_mgL.obs (Chl-a concentration)</li> </ul> <p> </p> <p>---CTD probe profile data from the deepest point in the lake (BA1) from 2017.8 to 2021.8 at biweekly basis with approximately 0.1 m vertical resolution</p> <p> File name:</p> <ul> <li>t_prof_file_barleber_ctm644.obs (water temperature)</li> <li>oxy_prof_file_barleber_ctm644 (Dissolved oxygen)</li> <li>turb_prof_file_barleber_ctm644.obs (Turbidity)</li> <li>chla_prof_file_barleber_ctm644.obs (Chl-a concentration)</li> </ul> <p> </p> <p>---BBE probe profile data from the deepest point in the lake (BA1) from 2017.8 to 2021.8 at biweekly basis with approximately 0.1 m vertical resolution</p> <p> File name:</p> <ul> <li>totalChla_prof_file_barleber_FP2101.obs (Chl-a concentration)</li> <li>bluegreen_prof_file_barleber_FP2101.obs (Blue-green algae Chl-a concentration)</li> <li>green_prof_file_barleber_FP2101.obs (Green algae Chl-a concentration)</li> <li>diatom_prof_file_barleber_FP2101.obs (Diatom Chl-a concentration)</li> </ul> <p> </p> <p> </p>
FIG. 3 in A Long-term Demographic Study of a Spotted Salamander (Ambŋstoma maculatum) Population in Central Ohio
FIG. 3.—Relationships between percent mass loss and number of days spent in Taylor–Ochs Pond, Ohio, for individually marked female (R2 ¼ 0.57, P ¼ 0.001; y ¼ 1.25x þ 6.76) and male (R2 ¼ 0.18, P ¼ 0.001, y ¼ 0.29x þ 3.39) Ambŋstoma maculatum sampled from 2005 to 2014.
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.