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110 results for “ecological response”
Data from: Ecological effects on metabolic scaling amphipod responses to fish predators in freshwater springs
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Data from: Ecological co-associations influence species’ responses to past climatic change: an example from a Sonoran Desert bark beetle
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Data from: Trophic response to ecological conditions of habitats: evidence from trophic variability of freshwater fish
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Telomere length correlates with physiological and behavioural responses of a long-lived seabird to an ecologically-relevant challenge
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Data from: Ecological changes in coyotes (Canis latrans) in response to the Ice Age megafaunal extinctions
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Data from: Puma responses to unreliable human cues suggest an ecological trap in a fragmented landscape
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Data from: Ecological and evolutionary responses of an arctic plant to variation in microclimate and soil
<p>The arctic and alpine regions are predicted to experience some of the highest rates of climate change, and the arctic vegetation is expected to be especially sensitive to such changes. Understanding the ecological and evolutionary responses of arctic plant species to changes in climate is therefore a key objective. Geothermal areas, where natural temperature gradients occur over small spatial scales, and without many of the confounding environmental factors present in latitudinal and other gradient studies, provide a natural experimental setting in which to examine the response of arctic-alpine plants to increasing temperatures. To test the ecological and evolutionary response of the circumpolar alpine bistort (Persicaria vivipara) to temperature, we collected plant material and soil from areas with low, intermediate, and high soil temperatures and grew them at three different temperatures in a threefactorial growth chamber experiment. At higher experimental soil temperatures, sprouting was earlier, and plants had more leaves. Sprouting was earlier in soil originating from intermediate temperature and plants had more leaves when grown in soil originating from low temperatures. We did not find evidence of local adaptation or genetic variation in reaction norms among plants originating from areas with low, intermediate, and high soil temperature. Our findings suggest that the alpine bistort has a strong plastic response to warming, but that differences in soil temperature have not resulted in genetic differentiation. The lack of an observed evolutionary response may, for example, be due to the absence of temperature-mediated selection on P. vivipara, the low rate of sexual recombination, or high levels of gene flow balancing differences in selection. When placed within the context of other studies, we conclude that arctic-alpine plant species often show strong plastic responses to spring warming, while evidence of evolutionary responses varies among species.</p>
Broadening the ecology of fear: non-lethal effects arise from diverse responses to predation and parasitism
<p><span>The ecology of fear demonstrates how prey responses to avoid predation cause non-lethal effects at all ecological scales. Parasites also elicit defensive responses in hosts with associated non-lethal effects, which raises the longstanding, yet unresolved question of how non-lethal effects of parasites compare with those of predators. We developed a framework for systematically answering this question for all types of predator and parasite systems. Our framework predicts that trait responses and their non-lethal effects should be strongest from predators and parasites that do not kill individuals to feed on them, but which nevertheless damage fitness. Analysing trait response data on amphibians, which have been well-studied for this area of research, showed that individuals generally responded more directly to short-term predation risks than to parasitism. Apart from studies using amphibians, there have been few direct comparisons of responses to predation and parasitism, and none have incorporated responses to micropredators, parasitoids, or parasitic castrators, or examined their long-term consequences. Addressing these and other data gaps highlighted by our general framework can advance the field toward understanding how non-lethal effects shape real food webs, which contain multiple predator and parasite species. </span></p>
Data from: When does extreme drought elicit extreme ecological responses?
1. Global climate change models predict an increase in the frequency and intensity of extreme droughts, with uncertain ecological impacts across ecosystems. In particular, it is not clear when extreme droughts will elicit extreme ecological responses. 2. For this study, we employed three complementary approaches to explore the relationships between extreme drought and ecosystem responses. First, we used global data mining to evaluate the relationship between extreme gross primary productivity (GPP) and extreme precipitation from 1980 to 2013. Second, we conducted a meta‐analysis using 132 drought experiments across the globe to assess the response ratios of aboveground net primary productivity (ANPP) to extreme vs. non‐extreme drought treatments. Third, we examined community and ecosystem responses in an alpine meadow to a drought gradient experiment, which included five precipitation treatment levels (1/12 P, 1/4 P, 1/2 P, 3/4 P, and P, where P is the growing season precipitation). 3. This study had three key results. In our historical data mining, we found that extreme droughts elicited extreme ecological responses only 15.1% of the time. The meta‐analysis results indicated that there were no significant differences in the response ratios of ANPP between the extreme vs. non‐extreme drought treatments. The drought gradient experiment results revealed that although the four drought treatments were statistically extreme, only the most extreme drought treatment (1/12 P) significantly reduced ANPP over the three years. Meanwhile, species richness and asynchrony were significantly reduced under the 1/12 P treatment, which led to a significant reduction in productivity. 4. Synthesis. These results suggest that extreme ecological responses to extreme drought may be less frequent than previously thought. But when they do occur, extreme ecological responses may be driven by plant community changes such as species asynchrony, species loss or species reordering. Our experimental results highlight the key role of community dynamics in determining the resistance of ecosystem productivity to extreme drought, which should be assessed when predicting ecological responses to climate change.
Data from: A replicated climate change field experiment reveals rapid evolutionary response in an ecologically important soil invertebrate
Whether species can respond evolutionarily to current climate change is crucial for the persistence of many species. Yet, very few studies have examined genetic responses to climate change in manipulated experiments carried out in natural field conditions. We examined the evolutionary response to climate change in a common annelid worm using a controlled replicated experiment where climatic conditions were manipulated in a natural setting. Analyzing the transcribed genome of 15 local populations, we found that about 12% of the genetic polymorphisms exhibit differences in allele frequencies associated to changes in soil temperature and soil moisture. This shows an evolutionary response to realistic climate change happening over short-time scale, and calls for incorporating evolution into models predicting future response of species to climate change. It also shows that designed climate change experiments coupled with genome sequencing offer great potential to test for the occurrence (or lack) of an evolutionary response.
Transcriptional response to long-term thermal acclimation in an ecologically relevant marine cyanobacterium of the ubiquitous Synechococcus clade II
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Supplementary material 1 from: Marinovska PG, Todorova TI, Boyadzhiev KP, Pisareva EI, Tomova AA, Parvanova PN, Dimitrova M, Chankova SG, Petrova VY (2022) Cellular susceptibility and oxidative stress response to menadione of logarithmic, quiescent, and nonquiescent Saccharomyces cerevisiae cell populations. In: Chankova S, Peneva V, Metcheva R, Beltcheva M, Vassilev K, Radeva G, Danova K (Eds) Current trends of ecology. BioRisk 17: 127-138. https://doi.org/10.3897/biorisk.17.77320
Figure S1
Data from: Light sensing by opsins and fungal ecology: NOP-1 modulates entry into sexual reproduction in response to environmental cues
Understanding the genetic basis of the switch from asexual to sexual lifestyles in response to sometimes rapid environmental changes is one of the major challenges in fungal ecology. Light appears to play a critical role in the asexual–sexual switch—but fungal genomes harbour diverse light sensors. Fungal opsins are homologous to bacterial green-light-sensory rhodopsins, and their organismal functions in fungi have not been well understood. Three of these opsin-like proteins were widely distributed across fungal genomes, but homologs of the Fusarium opsin-like protein CarO were present only in plant-associated fungi. Key amino acids, including potential retinal binding sites, functionally diverged on the phylogeny of opsins. This diversification of opsin-like proteins could be correlated with life history-associated differences among fungi in their expression and function during morphological development. In Neurospora crassa and related species, knockout of the opsin NOP-1 led to a phenotype in the regulation of the asexual–sexual switch, modulating response to both light and oxygen conditions. Sexual development commenced early in ∆nop-1 strains cultured in unsealed plates under constant blue and white light. Furthermore, comparative transcriptomics showed that the expression of nop-1 is light-dependent and that the ∆nop-1 strain abundantly expresses genes involved in oxidative stress response, genes enriched in NAD/NADP binding sites, genes with functions in proton transmembrane movement and catalase activity, and genes involved in the homeostasis of protons. Based on these observations, we contend that light and oxidative stress regulate the switch via light-responsive and ROS pathways in model fungus N. crassa and other fungi.
Spatial dataset for ecological response models and spatial distribution of Ataeniobius toweri (Cyprinodontiformes: Goodeidae) in the Media Luna spring, Mexico
<p>Dataset for the endangered endemic fish Ataeniobius toweri in the Media Luna spring, Mexico. This information includes field records for the adult and juvenile stage of the species in three sessions corresponding to the summer period, in the years 1999, 2009 and 2019.</p> <p>Our original databases are those concerning the records of the species' presence by life stage and summer period: <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Occ_records_DOMAIN_At_Ad_09.csv?versionId=9566fb68-3948-49ca-b485-2d7aac863445">Occ_records_DOMAIN_At_Ad_09.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Occ_records_DOMAIN_At_Ad_19.csv?versionId=6f7a0f47-4990-465c-a02c-191247c395c6">Occ_records_DOMAIN_At_Ad_19.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Occ_records_DOMAIN_At_Ad_99.csv?versionId=e9158e08-bf91-4097-828f-3ce850e1bee4">Occ_records_DOMAIN_At_Ad_99.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Occ_records_DOMAIN_At_Ju_09.csv?versionId=5bd51f0e-7215-4657-bfb5-bb49e6cdd57f">Occ_records_DOMAIN_At_Ju_09.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Occ_records_DOMAIN_At_Ju_19.csv?versionId=32d0c72a-a548-406d-8694-8d939e73058e">Occ_records_DOMAIN_At_Ju_19.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Occ_records_DOMAIN_At_Ju_99.csv?versionId=d786131a-f445-44d2-a319-0a75aa666f3f">Occ_records_DOMAIN_At_Ju_99.csv</a>.</p> <p>From the above files, we generate the following dataset:</p> <p>The general basis of the species records by life stage and period: <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Occ_records_by_sector&period_At_Ad_Ju.csv?versionId=13ffb71e-ef52-43f0-9605-e416359d5997">Occ_records_by_sector&period_At_Ad_Ju.csv</a>.</p> <p>The database that includes the 500 background points generated from records of the species' presence by life stage: <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Pres_back_GLM_At_Ad_09.csv?versionId=7083cda2-a16d-4a25-9404-4c134adc2fa5">Pres_back_GLM_At_Ad_09.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Pres_back_GLM_At_Ad_19.csv?versionId=2cbd76f6-241d-4035-b25b-1ce490362d6a">Pres_back_GLM_At_Ad_19.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Pres_back_GLM_At_Ad_99.csv?versionId=c570be15-2b21-4a2e-9377-0e7962a26d1b">Pres_back_GLM_At_Ad_99.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Pres_back_GLM_At_Ju_09.csv?versionId=11624daf-2da0-4bb1-95d4-b3c917c94c4f">Pres_back_GLM_At_Ju_09.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Pres_back_GLM_At_Ju_19.csv?versionId=1c06bcd0-4e34-49c4-859e-100f3401e225">Pres_back_GLM_At_Ju_19.csv</a> y <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Pres_back_GLM_At_Ju_99.csv?versionId=e10d7c51-f6f8-407c-8141-1b0196d00aed">Pres_back_GLM_At_Ju_99.csv</a>.</p> <p>The databases with the extracted values of the underwater coverage (UC) and water depth (WDp) variables from the presence and background points: <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/GBM_rel_contribution_At_Ad_09.csv?versionId=0735fbdb-5f3d-4842-ae3e-a45e849bb12f">GBM_rel_contribution_At_Ad_09.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/GBM_rel_contribution_At_Ad_19.csv?versionId=3ba6c099-e807-4e07-b1ef-32a63d347a50">GBM_rel_contribution_At_Ad_19.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/GBM_rel_contribution_At_Ad_99.csv?versionId=49e89e06-7740-425a-be2e-db5f38c0aeca">GBM_rel_contribution_At_Ad_99.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/GBM_rel_contribution_At_Ju_09.csv?versionId=fcc857f9-4332-4e15-901e-c4deecda46ab">GBM_rel_contribution_At_Ju_09.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/GBM_rel_contribution_At_Ju_19.csv?versionId=34dd733a-af86-46ad-a973-4e90e9299117">GBM_rel_contribution_At_Ju_19.csv</a> y <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/GBM_rel_contribution_At_Ju_99.csv?versionId=c7fe7fa9-e85b-45ba-9681-21f6a9cd3924">GBM_rel_contribution_At_Ju_99.csv</a>.</p> <p>The database with the results of the relative contribution for each variable by life stage and summer period: <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Summary_GBM_At_Ad_Ju.csv?versionId=f0b0b4d4-62b0-4d95-b6f4-ec5e00b97633">Summary_GBM_At_Ad_Ju.csv</a>.</p> <p>The databases containing the correlation values between the UC and WDp variables, by Pearson's method, for each point of presence and background: <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Pearson_corr_At_Ad_09.csv?versionId=99e74579-6edf-46e2-8f5d-3dd06a9a325f">Pearson_corr_At_Ad_09.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Pearson_corr_At_Ad_19.csv?versionId=ea4d938e-133e-426d-b11a-85ed877876f8">Pearson_corr_At_Ad_19.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Pearson_corr_At_Ad_99.csv?versionId=a499ab48-6be0-447c-9521-8e500769d4de">Pearson_corr_At_Ad_99.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Pearson_corr_At_Ju_09.csv?versionId=da583fda-0bc5-4769-bab8-bfb3c365232e">Pearson_corr_At_Ju_09.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Pearson_corr_At_Ju_19.csv?versionId=88e89cc1-2bfa-45cb-b6af-c87737a6fbd7">Pearson_corr_At_Ju_19.csv</a> y <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/Pearson_corr_At_Ju_99.csv?versionId=fddca19c-fa6b-460d-a571-966229fad955">Pearson_corr_At_Ju_99.csv</a>.</p> <p>And, the databases that contain the probability values for the generation of the ecological response curves in function of the UC variable: <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/At_Ad_09_Prob_UC.csv?versionId=240d8a0c-c0f6-4a1f-8983-74320b0863f8">At_Ad_09_Prob_UC.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/At_Ad_19_Prob_UC.csv?versionId=2bff87d1-b910-4cfd-b521-881e56034b19">At_Ad_19_Prob_UC.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/At_Ad_99_Prob_UC.csv?versionId=02050376-e34d-46ac-bdf9-7bc7b1f8570f">At_Ad_99_Prob_UC.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/At_Ju_09_Prob_UC.csv?versionId=a3182956-bbf4-4853-a3a2-4296e7acf79c">At_Ju_09_Prob_UC.csv</a>, <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/At_Ju_19_Prob_UC.csv?versionId=21a89330-89d3-442a-a801-19842a3bed70">At_Ju_19_Prob_UC.csv</a> y <a href="https://zenodo.org/api/files/05c9851d-72bc-406a-baee-4b09a28882b9/At_Ju_99_Prob_UC.csv?versionId=ff7d3966-6248-49d2-9000-07e374f0ba76">At_Ju_99_Prob_UC.csv</a>.</p> <p>For more information about the codes where the previous dataset was generated, visit the following repository URL: <a href="https://doi.org/10.5281/zenodo.7603557">https://doi.org/10.5281/zenodo.7603557</a>.</p> <p>Also, to download the UC and WDp variables to run the modeling processes, visit the following repository URL: <a href="https://doi.org/10.5281/zenodo.7603890">https://doi.org/10.5281/zenodo.7603890</a>.</p>
Data from: A replicated climate change field experiment reveals rapid evolutionary response in an ecologically important soil invertebrate
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Data from: Ecological and evolutionary responses of an arctic plant to variation in microclimate and soil
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Data from: Light sensing by opsins and fungal ecology: NOP-1 modulates entry into sexual reproduction in response to environmental cues
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Data from: Molecular data and ecological niche modeling reveal population dynamics of widespread shrub Forsythia suspensa (Oleaceae) in China’s warm-temperate zone in response to climate change during the Pleistocene
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Broadening the ecology of fear: non-lethal effects arise from diverse responses to predation and parasitism
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Data from: When does extreme drought elicit extreme ecological responses?
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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.