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89 results for “ecological time”
In the right place, at the right time: the integration of bacteria into the Plankton Ecology Group model
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Behaviour across time and space–how large scale ‘trait-based’ approaches can shape behavioural ecology
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Supporting data for: Physical controls and ecological implications of the timing of the spring phytoplankton bloom on the Newfoundland and Labrador shelf
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Time series methods for the analysis of soundscapes and other cyclical ecological data
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[Model outputs] Identifying major hydrologic change drivers in a highly managed transboundary endorheic basin: integrating hydro‐ecological models and time‐series data mining techniques
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Data for: Deep-time demographic inference suggests ecological release as driver of Neoavian adaptive radiation
<p>Data for:</p> <p>Houde P, Braun EL, Zhou L. 2020. Deep-time demographic inference suggests ecological release as driver of Neoavian adaptive radiation. Diversity, in review</p> <p>**************************************************<br> The .tar.gz file will expand to yield a directory named "Houde_Braun_Zhou_data_files". That directory has three subdirectories:</p> <p>1. alignments<br> 2. indel_matrices<br> 3. trees</p> <p>The Houde_Braun_Zhou_data_files directory also includes a README.txt file with complete details regarding the contents of each subdirectory.</p>
Unique genetic signatures of local adaptation over space and time for diapause, an ecologically relevant complex trait, in Drosophila melanogaster
<p>Organisms living in seasonally variable environments utilize cues such as light and temperature to induce plastic responses, enabling them to exploit favorable seasons and avoid unfavorable ones. Local adapation can result in variation in seasonal responses, but the genetic basis and evolutionary history of this variation remains elusive. Many insects, including <i>Drosophila melanogaster,</i> are able to undergo an arrest of reproductive development (diapause) in response to unfavorable conditions. In <i>D. melanogaster</i>, the ability to diapause is more common in high latitude populations, where flies endure harsher winters, and in the spring, reflecting differential survivorship of overwintering populations. Using a novel hybrid swarm-based genome wide association study, we examined the genetic basis and evolutionary history of ovarian diapause. We exposed outbred females to different temperatures and day lengths, characterized ovarian development for over 2800 flies, and reconstructed their full phased genomes. We found that diapause scored at two different developmental cutoffs has modest heritability, and we identified hundreds of SNPs associated with each of the two phenotypes. Alleles associated with one of the diapause phenotypes tend to be more common at higher latitudes, but these alleles do not show predictable seasonal variation. The collective signal of many small-effect, clinally varying SNPs can plausibly explain latitudinal phenotypic variation seen in North America. SNPs associated with diapause do not exhibit signs of recent selective sweeps, but most are segregating at relatively high frequencies in Africa, suggesting that variation in diapause relies on ancestral polymorphisms. Finally, we utilized outdoor mesocosms to track diapause under natural conditions. We found that hybrid swarms reared outdoors evolved increased propensity for diapause in late fall, whereas indoor control populations experienced no such change. Our results indicate that diapause is a complex, quantitative trait with different evolutionary patterns across time and space.</p>
Acoustic indices perform better when applied at ecologically meaningful time and frequency scales
Abstract: 1. Acoustic indices are increasingly employed in the analysis of soundscapes to ascertain biodiversity value. However, conflicting results and lack of consensus on best practices for their usage has hindered their application in conservation and land-use management contexts. Here we propose that the sensitivity of acoustic indices to ecological change and fidelity of acoustic indices to ecological communities are severely impacted by signal masking. Signal masking can occur when acoustic responses sensitive to the effect being monitored are masked by less sensitive acoustic groups, or target taxa sonification is masked by non-target noise. We argue that by calculating acoustic indices at ecologically appropriate time and frequency bins, masking effects can be reduced and the efficacy of indices increased. 2. We test this on a large acoustic dataset collected in Eastern Amazonia spanning a disturbance gradient including undisturbed, logged, burned, logged-and-burned, and secondary forests. We calculated values for two acoustic indices: the Acoustic Complexity Index and the Bioacoustic Index, across the entire frequency spectrum (0-22.1 kHz), and four narrower subsets of the frequency spectrum; at dawn, day, dusk and night. 3. We show that signal masking has a large impact on the sensitivity of acoustic indices to forest disturbance classes. Calculating acoustic indices at a range of narrower time-frequency bins substantially increases the classification accuracy of forest classes by random forest models. Furthermore, signal masking led to highly misleading correlations, including spurious inverse correlations, between biodiversity indicator metrics and acoustic index values compared to correlations derived from manual sampling of the audio data. 4. Consequently, we recommend that acoustic indices are calculated either at a range of time and frequency bins, or at a single narrow bin, predetermined by a priori ecological understanding of the soundscape.
Data from: Population genetic and field ecological analyses return similar estimates of dispersal over space and time in an endangered amphibian
The explosive growth of empirical population genetics has seen a proliferation of analytical methods leading to a steady increase in our ability to accurately measure key population parameters, including genetic isolation, effective population size, and gene flow in natural systems. Assuming they yield similar results, population genetic methods offer an attractive complement to, or replacement of, traditional field ecological studies. However, empirical assessments of the concordance between direct field ecological and indirect population genetic studies of the same populations are uncommon in the literature. In this study, we investigate genetic isolation, rates of dispersal, and population sizes for the endangered California tiger salamander, Ambystoma californiense, across multiple breeding seasons in an intact vernal pool network. We then compare our molecular results to a previously published study based on multi-year, mark-recapture data from the same breeding sites. We found that field and genetic estimates of population size were only weakly correlated, but dispersal rates were remarkably congruent across studies and methods. In fact, dispersal probability functions derived from genetic data and traditional field ecological data were a significant match, suggesting that either method can be used effectively to assess population connectivity. These results provide one of the first explicit tests of the correspondence between landscape genetic and field ecological approaches to measuring functional population connectivity and suggest that even single-year genetic samples can return biologically meaningful estimates of natural dispersal and gene flow.
Multilevel modeling of time-series cross-sectional data reveals the dynamic interaction between ecological threats and democratic development
<p>What is the relationship between environment and democracy? The framework of cultural evolution suggests that societal development is an adaptation to ecological threats. Pertinent theories assume that democracy emerges as societies adapt to ecological factors such as higher economic wealth, lower pathogen threats, less demanding climates, and fewer natural disasters. However, previous research confused within-country processes with between-country processes and erroneously interpreted between-country findings as if they generalize to within-country mechanisms. In this article, we analyze a time-series cross-sectional dataset to study the dynamic relationship between environment and democracy (1949-2016), accounting for previous misconceptions in levels of analysis. By separating within-country processes from between-country processes, we find that the relationship between environment and democracy not only differs by countries but also depends on the level of analysis. Economic wealth predicts increasing levels of democracy in between-country comparisons, but within-country comparisons show that democracy declines as countries become wealthier over time. This relationship is only prevalent among historically wealthy countries but not among historically poor countries, whose wealth also increased over time. By contrast, pathogen prevalence predicts lower levels of democracy in both between-country and within-country comparisons. Our longitudinal analyses identifying temporal precedence reveal that not only reductions in pathogen prevalence drive future democracy, but also democracy reduces future pathogen prevalence and increases future wealth. These nuanced results contrast with previous analyses using narrow, cross-sectional data. As a whole, our findings illuminate the dynamic process by which environment and democracy shape each other.</p>
Data from: coexistence across space and time: social-ecological patterns within a decade of human-coyote interactions in San Francisco
<p><span>Global change is increasing the frequency and severity of human-wildlife interactions by pushing people and wildlife into increasingly resource-limited shared spaces. To understand the dynamics of human-wildlife interactions, and what may constitute human-wildlife coexistence in the Anthropocene, there is a critical need to explore the spatial, temporal, sociocultural, and ecological variables that contribute to human-wildlife conflicts in urban areas.</span></p> <p><span>Due to their opportunistic foraging and behavioral flexibility, coyotes (<em>Canis latrans</em>) frequently interact with people in urban environments. San Francisco, California, USA hosts a very high density of coyotes, making it an excellent region for analyzing urban human-coyote interactions and attitudes toward coyotes over time and space.</span></p> <p><span>We used a community-curated long-term data source from San Francisco Animal Care and Control to summarize a decade of coyote sightings and human-coyote interactions in San Francisco and to characterize spatiotemporal patterns of attitudes and interaction types in relation to housing density, socioeconomics, pollution and human vulnerability metrics, and green space availability.</span></p> <p><span>We found that human-coyote conflict reports have been significantly increasing over the past 5 years and that there were more conflicts during the coyote pup-rearing season (April-June), the dry season (June-September), and the COVID-19 pandemic. Conflict reports were also more likely to involve dogs and occur inside of parks, despite more overall sightings occurring outside of parks. Generalized linear mixed models revealed that conflicts were more likely to occur in places with higher vegetation greenness and median income. Meanwhile reported coyote boldness, hazing, and human attitudes toward coyotes were also correlated with pollution burden and human population vulnerability indices.</span></p> <p><span><em>Synthesis and applications</em>: </span><span>Our results provide compelling evidence suggesting that human-coyote conflicts are intimately associated with social-ecological heterogeneities and time, emphasizing that the road to coexistence will require socially-informed strategies. Additional long-term research articulating how the social-ecological drivers of conflict (e.g., human food subsidies, interactions with domestic species, climate-induced droughts, socioeconomic disparities, etc.) change over time will be essential in building adaptive management efforts that effectively mitigate future conflicts from occurring. </span></p>
Ecological conditions predict the intensity of Hendra virus excretion over space and time from bat reservoir hosts
<p>The ecological conditions experienced by wildlife reservoirs affect infection dynamics and thus the distribution of pathogen excreted into the environment, which have been hypothesized to shape risks of zoonotic spillover. However, few systems have data on both long-term ecological conditions and pathogen excretion to advance mechanistic understanding and test environmental drivers of spillover risk. We here analyze three years of Hendra virus data from nine Australian flying fox roosts with covariates derived from long-term studies of bat ecology. We show that the magnitude of winter pulses of viral excretion, previously considered idiosyncratic, are most pronounced after recent food shortages and in bat populations displaced to novel habitats. We further show that cumulative pathogen excretion over time is shaped by bat ecology and positively predicts spillover frequency. Our work emphasizes the role of reservoir host ecology in shaping pathogen excretion and provides a new approach to estimate spillover risk.</p>
Ecological conditions predict the intensity of Hendra virus excretion over space and time from bat reservoir hosts
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Data from: coexistence across space and time: social-ecological patterns within a decade of human-coyote interactions in San Francisco
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Multilevel modeling of time-series cross-sectional data reveals the dynamic interaction between ecological threats and democratic development
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Data from: Timing of breeding in an ecologically trapped bird
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Data from: The impact of geographic range, sampling, ecology, and time on extinction risk in the volatile clade Graptoloida
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Data from: Insect herbivores drive real-time ecological and evolutionary change in plant populations
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Data from: Coexistence of three sympatric cormorants (Phalacrocorax spp.); partitioning of time as an ecological resource
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Acoustic indices perform better when applied at ecologically meaningful time and frequency scales
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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.