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601 results for “Global changes”
Can we predict global patterns of long-term climate change from short-term simulations?
<p>Post-processed data from "Can we predict global patterns of long-term climate change from short-term simulations?". Also includes python dictionary for translating file code into the name of the run. For use with code publicly available on github.com/lm2612/Ridge_3 and github.com/lm2612/GPRegression.</p>
Data from: Increases and decreases in marine disease reports in an era of global change
<p>Outbreaks of <span class="il">marine</span> infectious diseases have caused widespread mass mortalities, but the lack of baseline data has precluded evaluating whether <span class="il">disease</span> is increasing or decreasing in the ocean. We use an established literature proxy method from Ward and Lafferty (2004) to analyze a 44-year <span class="il">global</span> record of normalized <span class="il">disease</span> reports from 1970 to 2013. Major <span class="il">marine</span> hosts are combined into nine taxonomic groups, from seagrasses to <span class="il">marine</span> mammals, to assess <span class="il">disease</span> swings, defined as positive or negative multi-decadal shifts in <span class="il">disease</span> reports across related hosts. Normalized <span class="il">disease</span> reports increased significantly between 1970 and 2013 in corals and urchins, indicating positive <span class="il">disease</span> swings in these environmentally sensitive ectotherms. Coral <span class="il">disease</span> reports in the Caribbean correlated with increasing temperature anomalies, supporting the hypothesis that warming oceans drive infectious coral diseases. Meanwhile, <span class="il">disease</span> risk may also decrease in a changing ocean. <span class="il">Disease</span> reports decreased significantly in fish and elasmobranchs, which have experienced steep human-induced population declines and diminishing population density that, while concerning, may reduce <span class="il">disease</span>. The <span class="il">increases</span> and decreases in <span class="il">disease</span> reports across the 44-year record transcend short-term fluctuations and regional variation. Our results show that long-term changes in <span class="il">disease</span> reports coincide with recent decades of widespread environmental <span class="il">change</span> in the ocean.</p>
Data from: Plant-bacteria-soil response to frequency of simulated nitrogen deposition has implications for global ecosystem change
<ol> <li><span>Atmospheric nitrogen (N) deposition, generally, has been simulated through a single or relatively few N applications per year for its ecological effect study. Despite the importance of timing in ecosystem processes, ecological experiments with more realistic N addition frequencies are rare.</span></li> <li><span>We employed a novel design with typical twice (2X) vs. atypical monthly (12X) N applications per year to explore effects of N addition frequency on above- and below-ground biodiversity and function. </span></li> <li><span>Each year, several response variables from either belowground or aboveground growth, N status and cycling, or plant and bacterial diversity differed as a result of N addition frequency. BNPP showed a large frequency effect in the relatively moist year but not in the dry year. Nitrogen addition decreased root growth in the monthly relative to the biannual applications, which could be highly consequential for predicting changes in global carbon and nitrogen cycling. Simulated N deposition tended to perturb biodiversity, but it is noteworthy that 12X applications that spread N deposition more evenly through a year have much less negative impacts on plant and bacterial diversities than 2X amendments per year. Soil N mineralization rate in year 6 was much lower when N additions were monthly compared with a biannual amendment, especially when simulated N deposition was high. </span></li> <li><span>We have established that amendment frequency matters for understanding ecosystem response to N deposition. Experiments that more closely mimic the anthropogenic process of N deposition are needed to best assess ecosystem and potential global biogeochemical changes.</span></li> </ol>
The umbrella value of caribou management strategies for biodiversity conservation in boreal forests under global change
<p><span>Single-species conservation management is often proposed to preserve biodiversity in human-disturbed landscapes. How global change will impact the umbrella value of single-species management strategies remains an open question of critical conservation importance. We assessed the effectiveness of threatened boreal caribou as an umbrella for bird and beetle conservation under global change. We combined mechanistic, spatially explicit models of forest dynamics and predator-prey interactions to forecast the impact of management strategies on the survival of boreal caribou in boreal forest. We then used predictive models of species occupancy to characterize concurrent impacts on bird and beetle diversity. Landscapes were simulated based on three scenarios of climate change and four of forest management. We found that strategies that best mitigate human impact on boreal caribou were an effective umbrella for maintaining bird and beetle assemblages. While we detected a stronger effect of land-use change compared to climate change, the umbrella value of management strategies for caribou habitat conservation were still impacted by the severity of climate change. Our results showed an interplay among changes in forest attributes, boreal caribou mortality, as well as bird and beetle species assemblages. The conservation status of some species mandates the development of recovery strategies, highlighting the importance of our study which shows that single-species conservation can have important umbrella benefits despite global change.</span></p>
Data from: Mammal communities of primeval forests as sentinels of global change
<p>Understanding the drivers and consequences of global environmental change is crucial to inform predictions of effects on ecosystems. We used the mammal community of Białowieża Forest, the last lowland near-primeval forest in temperate Europe, as a sentinel of global change. We analyzed changes in stable carbon (δ<sup>13</sup>C) and nitrogen (δ<sup>15</sup>N) isotope values of hair in 687 specimens from 50 mammal species across seven decades (1946–2011). We classified mammals into four taxonomic-dietary groups (herbivores, carnivores, insectivores, bats). We found a significant negative trend in hair δ<sup>15</sup>N for the mammal community, particularly strong for herbivores. This trend is consistent with temporal patterns in nitrogen deposition from (<sup>15</sup>N depleted) industrial fertilizers and fossil fuel emissions. It is also in line with global-scale declines in δ<sup>15</sup>N reported in forests and other unfertilized, non-urban terrestrial ecosystems and with local decreases in N foliar concentrations. The global depletion of <sup>13</sup>C content in atmospheric CO<sub>2</sub> due to fossil fuel burning (Suess effect) was detected in all groups. After correcting for this effect, the hair δ<sup>13</sup>C trend became non-significant for both community and groups, except for bats, which showed a strong decline in δ<sup>13</sup>C. This could be related to an increase in the relative abundance of freshwater insects taken by bats or increased use of methane-derived carbon in food webs used by bats. This work is the first broad-scale and long-term mammal isotope ecology study in a near-primeval forest in temperate Europe. Mammal communities from natural forests represent a unique benchmark in global change research; investigating their isotopic temporal variation can help identify patterns and early detections of ecosystem changes and provide more comprehensive and integrative assessments than single-species approaches.</p>
MESI: a database of terrestrial global change experiments
<p>effects of experimental eCO2, warming, nutrient addition and/or water addition/removal on carbon and nutrient cycle related variables</p> <p> </p> <p>New in v1.0.3:</p> <p>Improved accuracy and further completion of the following variables:</p> <p>• longitude (lon) of the experiment site (site)</p> <p>• latitude (lat) of the experiment site (site)</p> <p>• elevation (elevation) of the experiment site (site)</p> <p>• ecosystem type (ecosystem_type)</p> <p>• experiment type: field/FACE, open-top chamber, pot (experiment_type and fumigation_type)</p> <p>• treatment level (particularly c_c, c_t, n_c, n_t, p_c, p_t, k_c, k_t)</p> <p>• sampling year of the experiment (sampling_year and duration)</p> <p>• warming type (w_t1)</p> <p>• some site (site), study (study) and experiment (exp) names</p> <p> </p> <p>Response variable (response) 'leaf_area' replaced by leaf_area_leaf, leaf_area_plant, leaf_area_eco</p> <p>Response variable (response) 'leaf_biomass' replaced by leaf_biomass_leaf, leaf_biomass_plant, leaf_biomass_eco</p>
Data from: Projected loss of brown macroalgae and seagrasses with global environmental change
<p>Data associated with the paper "Projected loss of brown macroalgae and seagrasses with global environmental change" by Federica Manca, Lisandro Benedetti-Cecchi, Corey J. A. Bradshaw, Mar Cabeza, Camilla Gustafsson, Alf M. Norkko, Tomas V. Roslin, David N. Thomas, Lydia White, Giovanni Strona</p>
Supporting Data for "Climate Sensitivity and Relative Humidity Changes in Global Storm-Resolving Model Simulations of Climate Change"
<p>Code and netcdf files of processed X-SHiELD and CMIP6 simulations to reproduce the figures of Timothy M. Merlis, Kai-Yuan Cheng, Ilai Guendelman, Lucas Harris, Christopher S. Bretherton, Maximilien Bolot, Linjiong Zhou, Alex Kaltenbaugh, Spencer K. Clark, Gabriel A. Vecchi, and Stephan Fueglistaler (2024): "Climate Sensitivity and Relative Humidity Changes in Global Storm-Resolving Model Simulations of Climate Change".</p>
Data from: Climate change is predicted to impact the global distribution and richness of pines (genus Pinus) by 2070
<p>Aim: Climate change is altering habitat suitability for many organisms and modifying species ranges at a global scale. Here we explored the impact of climate change on 112 pine species (<em>Pinus</em>), fundamental elements of Northern terrestrial ecosystems.</p> <p>Location: Global.</p> <p>Methods: We applied a novel methodology for species distribution modelling that considers uncertainty in climatic projections and taxon sampling, and incorporates elements of species' recent evolutionary history. We based our niche calculations on climate and soil data and computed projections across multiple algorithms and IPCC scenarios, which were ensembled into one single suitability map. We then used phylogenetic methods to account for recent evolution in climatic requirements by estimating the evolution of climatic niche. Edaphoclimatic and evolutionary analyses were then combined to calibrate the projections in areas showing high uncertainty. We validated our models using naturalized occurrences of invasive pine species.</p> <p>Results: Our models predicted that by 2070 most pine species (58%) might face important reductions of habitat suitability, potentially leading to range losses and a decrease in species richness, particularly in some regions such as the Mediterranean Basin and South North America, albeit migration might mitigate these shifts in some cases. In contrast, our projections showed increased habitat suitability for approx. 20% of species, which may undergo range expansions under climate change. Moreover, the consideration of recent evolutionary trends modified projected scenarios, decreasing range loss and increasing range expansion for some species. The independent validation endorsed our models for many species and the influence of recent evolution in some cases.</p> <p>Conclusions: We predict that climate change will impose drastic changes in pine distribution and diversity across biogeographical regions, but the magnitude and direction of change will vary significantly across regions and taxa. Species-level responses are likely to be influenced by regional conditions and the recent evolutionary history of each taxon.</p>
Local reflects global: Life-stage dependent changes in the phenology of coastal habitat use by North Sea herring
<p>Climate warming is affecting the suitability and utilisation of coastal habitats by marine fishes around the world. Phenological changes are an important indicator of population responses to climate-induced changes but remain difficult to detect in marine fish populations. The design of large-scale monitoring surveys does not allow fine-grained temporal inference of population responses, while the responses of ecologically and economically important species groups such as small pelagic fish are particularly sensitive to temporal resolution. Here, we use the longest, highest-resolution time series of species composition and abundance of marine fishes in northern Europe to detect possible phenological shifts in the small pelagic North Sea herring. We detect a clear forward temporal shift in the phenology of nearshore habitat use by small juvenile North Sea herring. This forward shift can best be explained by changes in water temperatures in the North Sea. We find that reducing the temporal resolution of our data to reflect the resolution typical of larger surveys makes it difficult to detect phenological shifts and drastically reduces the effect sizes of environmental covariates such as seawater temperature. Our study therefore shows how local, long-term, high-resolution time series of fish catches are essential to understand the general phenological responses of marine fishes to climate warming and to define ecological indicators of system-level changes.</p>
GSOCS-LULCC: the Global Soil Organic Carbon Stock dataset after Land Use and Land Cover Change
<p>We complied the Global Soil Organic Carbon Stock dataset after Land Use and Land Cover Change (GSOCS-LULCC) from 632 papers documented in Web of Science till the June 2024. This database comprises 1,187 sites with 5,805 records at multiple sample depths.<br>This dataset (in csv formats) is associated to the "GSOCS-LULCC: the Global Soil Organic Carbon Stock dataset after Land Use and Land Cover Change" by Chen et al. (2025). The README file includes the full explanation of all the columns.<br>Manuscript citation: Chen, S., Shuai, Q., Arrouays, D., Chen, Z., Dai, L., Hong, Y., Hu, B., Huang, Y., Ji, W., Li, S., Liang, Z., Ma, Y., Richer-de-Forges, A.C., Schillaci, C., Su, Y., Teng, H., Wang, N., Wang, X., Wang, Y., Wang, Z., Wang, Z., Xu, D., Xue, J., Ye, S., Zhang, X., Zhou, Y., Zhu, P., Shi, Z. , 2025. GSOCS-LULCC: the Global Soil Organic Carbon Stock dataset after Land Use and Land Cover Change. In preparation.<br>When using the data, please cite repositories as well as the original manuscript.<br>For any questions on the data, please contact Dr. Songchao Chen (chensongchao@zju.edu.cn).</p>
Do tradeoffs govern plant species responses to different global change treatments?
<p>Plants are subject to tradeoffs among growth strategies such that adaptations for optimal growth in one condition can preclude optimal growth in another. Thus, we hypothesized that the response of plant species abundance to one global change treatment would relate inversely to the response to a second treatment, particularly for treatment combinations that accentuate distinct traits. To address this hypothesis, we examined plant species abundances in 39 global change experiments manipulating CO2, nitrogen, phosphorus, water, temperature, or disturbance. Overall, the directional response of a species to one treatment was 13% more likely than expected to oppose its response to a second. This tendency was detectable across the global dataset but held little predictive power for individual treatment combinations or within individual experiments. While tradeoffs in the ability to respond to different global change drivers exert detectable effects globally, other forces may obscure their influence in local communities.</p>
Model output for analyses conducted in de la Vega & Buchanan et al. (2022) Global Change Biology
<p>Model data for:</p> <p>De La Vega & Buchanan et al. (2022) Multi-decadal environmental change in the<br> Barents Sea recorded by seal teeth. Global Change Biology.</p> <p>Each netcdf file (.nc) contains model output from simulations performed with the<br> NEMO-SI3-PISCES global ocean-seaice-biogeochemistry model. These simulations were<br> forced by the Japanese Atmospheric Reanalysis 55 (Tsujino et al. 2018), which<br> provides "best-guess" atmospheric conditions since 1958 to present day. Simulations<br> for this study were performed from Jan 1958 - Dec 2019.</p> <p>Variables included here are:<br> - zonal velocity (u) m s-1<br> - meridional velocity (v) m s-1<br> - potential temperature (thetao) degrees C<br> - salinity (so) psu<br> - sea ice concentraton (siconc) 0-1<br> - nitrate (NO3) mmol m-3<br> - nitrate 15 (NO3_15) mmol m-3<br> - small particulate organics (POC) mmol m-3<br> - small particulate organics 15 (POC_15) mmol m-3<br> - large particulate organics (GOC) mmol m-3<br> - large particulate organics 15 (GOC_15) mmol m-3<br> - nanophytoplankton NPP (PPPHYN) mol C m-3 s-1<br> - diatoms NPP (PPPHYD) mol C m-3 s-1<br> - nanophytoplankton chlorophyll (NCHL) mmol m-3<br> - diatoms chlorophyll (DCHL) mmol m-3<br> - atmospheric N deposition (NDEP) kg N m-2 s-1</p> <p><br> Files:<br> ETOPO_JRA55_pic_1y_u_1958-2019.nc<br> ETOPO_JRA55_pic_1y_v_1958-2019.nc<br> ETOPO_JRA55_pic_1y_TS_1958-2019.nc<br> ETOPO_JRA55_pic_1y_ice_1958-2019.nc<br> ETOPO_JRA55_pic_1y_isos_1958-2019.nc<br> ETOPO_JRA55_pic_1y_npp_1958-2019.nc<br> ETOPO_JRA55_pic_1y_chl_1958-2019.nc<br> ETOPO_JRA55_ndep_1y_isos_1958-2019.nc<br> ETOPO_JRA55_ndep_1y_npp_1958-2019.nc<br> ETOPO_JRA55_ndep_1y_chl_1958-2019.nc<br> ETOPO_ndep_files_1801-2100.nc --> Atmospheric deposition</p> <p>Naming convention:<br> "ETOPO" refers to being on a regular 1x1 degree horizontal grid<br> "JRA55" refers to forcing by the Japanese atmospheric reanalysis<br> "pic" refers to an experiment WITHOUT the historical increase in<br> atmospheric nitrogne deposition </p> <p> "ndep" refers to an experiment WITH the historical increase in<br> atmospheric nitrogne deposition<br> "1y" refers to the timestep resolution, here all 1 year. Thus, all<br> data presented here is annually averaged values.<br> "u" refers to zonal velocity<br> "v" refers to meridional velocity<br> "TS" refers to temperature and salinity<br> "ice" refers to sea ice<br> "isos" refers to NO3, NO3_15, POC, POC_15, GOC and GOC_15<br> "npp" refers to PPPHYN and PPPHYD<br> "chl" refers to NCHL and DCHL</p> <p><br> Atmospheric deposition files are created by linear interpolation using the fields<br> produced by Hauglustaine et al. (2014).</p> <p><br> Contact:</p> <p> Camille.De-La-Vega@liverpool.ac.uk<br> Pearse.Buchanan@liverpool.ac.uk</p> <p> </p> <p>Refs:</p> <p> Tsujino et al. (2018) JRA-55 based surface dataset for driving ocean–sea-ice<br> models (JRA55-do). Ocean Modelling. doi:10.1016/j.ocemod.2018.07.002</p> <p> Hauglustaine et al. (2014) A global model simulation of present and future<br> nitrate aerosols and their direct radiative forcing of climate. Atmospheric<br> Chemistry and Physics. doi:10.5194/acp-14-11031-2014.</p> <p> </p> <p> </p>
Global forest reference set with time series annual change information
<p><strong>Brief introduction of the reference set:</strong></p> <ul> <li>The initial sample points were stratified. The ratio of non-forest, forest and forest change stratum area is about 67:27:6. In order to increase the number of forest and forest change sample points, the ration of forest sample, forest change sample and non-forest sample points is roughly 4:1:1. The information of stratum identifier is provided in this sample set. The study generated 12925 initial sample points which were further reduced to 10339 points (6252 persisting forest sample points, 2049 change sample points and 2038 persisting non-forest sample points). The details are shown in Table 1. </li> </ul> <table> <caption>Table 1. Initial and finial sample size in each stratum</caption> <tbody> <tr> <td><strong>Stratum name</strong></td> <td><strong>Percent area of each stratum</strong></td> <td><strong>Initial sample size</strong></td> <td><strong>Final sample size</strong></td> <td><strong>Eliminated sample size</strong></td> </tr> <tr> <td>Forest</td> <td>27%</td> <td>8332</td> <td>6252</td> <td>1644</td> </tr> <tr> <td>Non-forest</td> <td>67%</td> <td>1892</td> <td>2038</td> <td>207</td> </tr> <tr> <td>Forest change</td> <td>6%</td> <td>2701</td> <td>2049</td> <td>735</td> </tr> <tr> <td>Sum</td> <td>100%</td> <td>12925</td> <td>10339</td> <td>2586</td> </tr> </tbody> </table> <p> </p> <ul> <li>The sample set will be provided in shapefile version. (The eliminated sample points will not be provided.) In this version, the provided attributions are shown in Table 2.</li> </ul> <p> </p> <table> <caption>Table 2. Details of provided attributions in this version</caption> <tbody> <tr> <td><strong>Name</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>per_f</td> <td>unchanged forest (0: No 1: Yes)</td> </tr> <tr> <td>per_nonf</td> <td>unchanged non-forest (0: No 1: Yes)</td> </tr> <tr> <td>change</td> <td>forest change (0: No 1: Yes)</td> </tr> <tr> <td>loss</td> <td>forest loss times</td> </tr> <tr> <td>gain</td> <td>forest gain times</td> </tr> <tr> <td>times</td> <td>change times (gain + loss)</td> </tr> <tr> <td>changeinfo</td> <td>year and order of change</td> </tr> <tr> <td>initial_s</td> <td>initial stratum identifier: change/perf (persisting forest)/nonf (persisting non-forest)</td> </tr> </tbody> </table> <p> </p> <ul> <li>This reference set will be updated regularly. Now it's version 1.1 (from 2000 to 2020).</li> </ul> <p> </p> <p><strong>NOTES:</strong></p> <ol> <li>Please be cautious while using the sample points with multiple change times. </li> <li>We encourage people to send us feedback if you found some mistakes while using this sample set via email.</li> <li>Welcome discussions around potential collaborations. 【You can email Jing (guoj15@tsinghua.org.cn).】</li> </ol> <p> </p> <p><strong>Citation:</strong></p> <p>Please cite the dataset including the version number and the following paper when using this data: </p> <p>Jing Guo, Zhiliang Zhu & Peng Gong (2022) A global forest reference set with time series annual change information from 2000 to 2020, International Journal of Remote Sensing, 43:9, 3152-3162, DOI: <a href="https://doi.org/10.1080/01431161.2022.2088256">10.1080/01431161.2022.2088256</a></p>
Managing for the unexpected: building resilient forest landscapes to cope with global change: Supporting data
<p><strong>Input files</strong> and <strong>installers </strong>of the versions of LANDIS-II, PnET-Succession and other extensions used in the associated paper. They can be used to to reproduce results of the study.</p> <p>The model documentation is freely available at <a href="https://www.landis-ii.org/">https://www.landis-ii.org/</a></p> <p>The LANDIS-II code is distributed under an open source license at <a href="https://github.com/LANDIS-II-Foundation">https://github.com/LANDIS-II-Foundation</a>.</p> <p>If interested in using this dataset for a research study or project, please contact <a href="https://www.marco-mina.com">Marco Mina</a></p> <p>---------------------</p> <p>Mina, M., Messier, C., Duveneck, M., Fortin, M. J., & Aquilué, N. (2022) <strong>Managing for the unexpected: building resilient forest landscapes to cope with global change</strong>. <em>Global Change Biology </em>28, 4323– 4341 <em> </em><a href="https://doi.org/10.1111/gcb.16197">https://doi.org/10.1111/gcb.16197</a></p> <p>ABSTRACT. Natural disturbances exacerbated by novel climate regimes are increasing worldwide, threatening the ability of forest ecosystems to mitigate global warming through carbon sequestration and to provide other key ecosystem services. One way to cope with unknown disturbance events is to promote the ecological resilience of the forest by increasing both functional trait and structural diversity and by fostering functional connectivity of the landscape to ensure a rapid and efficient self-reorganization of the system. We investigated how expected and unexpected variations in climate and biotic disturbances affect ecological resilience and carbon storage in a forested region in southeastern Canada. Using a process-based forest landscape model (LANDIS-II), we simulated ecosystem responses to climate change and insect outbreaks under different forest policy scenarios – including a novel approach based on functional diversification and network analysis – and tested how the potentially most damaging insect pests interact with changes in forest composition and structure due to changing climate and management. We found that climate warming, lengthening the vegetation season, will increase forest productivity and carbon storage, but unexpected impacts of drought and insect outbreaks will drastically reduce such variables. Generalist, non-native insects feeding on hardwood are the most damaging biotic agents for our region, and their monitoring and early detection should be a priority for forest authorities. Higher forest diversity driven by climate-smart management and fostered by climate change that promotes warm-adapted species, might increase disturbance severity. However, alternative forest policy scenarios led to a higher functional and structural diversity as well as functional connectivity – and thus to higher ecological resilience – than conventional management. Our results demonstrate that adopting a landscape-scale perspective by planning interventions strategically in space and adopting a functional trait approach to diversify forests is promising for enhancing ecological resilience under unexpected global change stressors.</p>
Eco-evolutionary dynamics modulate plant responses to global change depending on plant diversity and species identity
Global change has dramatic impacts on grassland diversity. However, little is known about how fast species can adapt to diversity loss and how this affects their responses to global change. Here, we performed a common garden experiment testing whether plant responses to global change are influenced by their selection history and the conditioning history of soil at different plant diversity levels. Using seeds of four grass species and soil samples from a 14-year-old biodiversity experiment, we grew the offspring of the plants either in their own soil or in soil of a different community, and exposed them either to drought, increased nitrogen input, or a combination of both. Under nitrogen addition, offspring of plants selected at high diversity produced more biomass than those selected at low diversity, while drought neutralized differences in biomass production. Moreover, under the influence of global change drivers, soil history, and to a lesser extent plant history, had species-specific effects on trait expression. Our results show that plant diversity modulates plant-soil interactions and growth strategies of plants, which in turn affects plant eco-evolutionary pathways. How this change affects species' response to global change and whether this can cause a feedback loop should be investigated in more detail in future studies.
Grazing and global change factors differentially affect biodiversity-ecosystem functioning relationships in grassland ecosystems
<p><span>Grazing and </span><span>global change</span><span> (e.g., warming, nitrogen deposition</span> <span>and altered precipitation</span><span>) both contribute to biodiversity loss and alter ecosystem structure and function</span><span>ing</span><span>. However, how grazing and </span><span>global </span><span>change interactively influence plant diversity, ecosystem productivity, and the</span><span>ir relationship </span><span>remains unclear at the global scale. Here, we synthesized 73 field studies to quantify the individual and/or interactive effects of grazing and global change factors on biodiversity-</span><span>productivity relationship</span><span> in grasslands.</span><span> Our results showed that grazing significantly reduced plant richness by 3.7% and aboveground net primary productivity (ANPP) by 29.1%, but increased belowground net primary productivity (BNPP) by 9.3%. Global change factors, however, decreased richness by 8.0% but increased ANPP and BNPP by 13.4% and 14.9%, respectively</span><span>. Interestingly, the strengt</span><span>h of the change in biodiversity in response to grazing was positively correlated with</span> <span>the strength of the change in BNPP. Yet, global change flipped these relationships from positive to negative even when combined with grazing</span><span>.</span><span> These results indicate that the impacts of global change factors are more dominant than grazing on the</span><span> belowground</span> <span>biodiversity-productivity relationship, which</span><span> is contrary to the pattern of aboveground one</span><span>.</span><span> Therefore, incorporating global change factors with herbivore grazing into Earth system models is necessary to accurately predict climate-grassland </span><span>carbon</span><span> cycle feedbacks in the Anthropocene.</span></p>
Multiple global changes drive grassland productivity and stability: A meta-analysis
<p><span>Temporal stability of primary productivity is the key to stable provisioning of ecosystem services to human beings. Yet, the effects of various global changes on grassland stability remain ambiguous. </span></p> <p><span>Here, we conducted a comprehensive meta-analysis based on 1,070 multi-year paired observations from 173 studies, to examine the impacts of various global changes on productivity, community stability and plant diversity of grasslands on a global scale. The global change drivers include nitrogen (N) addition, phosphorus (P) addition, N & P addition, precipitation increase, precipitation decrease, elevated CO2, and warming. </span></p> <p><span>Global change drivers generally had stronger impacts on grassland productivity than on temporal stability, except for precipitation changes. Community temporal stability was reduced by N addition, N & P addition, and precipitation decrease, but was increased by precipitation increase and remained unchanged under P addition, elevated CO2, and warming. In addition, species richness decreased under N addition, N & P addition, and precipitation decrease. At the plant functional group level, N & P addition reduced grasses' stability and precipitation increase enhanced forbs' stability.</span></p> <p><span>Nutrient additions decreased community stability via increasing the inter-annual variation more than the mean of primary productivity, while precipitation changes mainly affected community temporal stability via changing mean productivity. The negative impacts of global change drivers (i.e. N & P addition, warming) on community temporal stability increased with the degree of species loss, but decreased with increasing stability of grasses. Moreover, the negative impacts of nutrient addition and precipitation decrease on community stability was lessened while the positive effect of precipitation increase on community stability was enhanced in grasslands with higher historical precipitation variability, greater soil fertility, and longer experimental duration.</span></p> <p><span><strong>Synthesis</strong>.</span><span> Our findings demonstrate that N-based nutrient additions and drought destabilise grassland productivity, while precipitation increase enhances community stability. Impacts of global changes on community productivity and stability are mediated by species richness, plant functional group, site-specific environmental conditions (i.e. climate, soil), and experimental duration, which deserve more attention in grassland management practices under future global change scenarios.</span></p>
Net effect of environmental fluctuations in multiple global-change drivers across the tree of life
<p>This dataset contains the raw data presented in the article and supplementary material by M. J. Cabrerizo and E. Marañón entitled: "<strong>Net effect of environmental fluctuations in multiple global-change drivers across the tree of life"</strong></p>
Invasive rodent responses to experimental and natural hurricanes with implications for global climate change
<p>Hurricanes cause dramatic changes to forests by opening the canopy and depositing debris onto the forest floor. How invasive rodent populations respond to hurricanes is not well understood, but shifts in rodent abundance and foraging may result from scarce fruit and seed resources that follow hurricanes. We conducted studies in a wet tropical forest in Puerto Rico to better understand how experimental (Canopy Trimming Experiment) and natural (Hurricane Maria) hurricane effects alter populations of invasive rodents (Rattus rattus [rats] and <em>Mus musculus</em> [mice]) and their foraging behaviors. To monitor rodent populations, we used tracking tunnels (inked and baited cards inside tunnels enabling identification of animal visitors' footprints) within experimental hurricane plots (arborist trimmed in 2014) and reference plots (closed canopy forest). To assess shifts in rodent foraging, we compared seed removal of two tree species (Guarea guidonia and Prestoea acuminata) between vertebrate-excluded and free-access treatments in the same experimental and reference plots, and did so 3 months before and 9 months after Hurricane Maria (2017). Trail cameras were used to identify animals responsible for seed removal. Rat incidences generated from tracking tunnel surveys indicated that rat populations were not significantly affected by experimental or natural hurricanes. Before Hurricane Maria there were no mice in the forest interior, yet mice were present in forest plots closest to the road after the hurricane, and their forest invasion coincided with increased grass cover resulting from open forest canopy. Seed removal of Guarea and Prestoea across all plots was rat dominated (75%-100% rat-removed) and was significantly less after than before Hurricane Maria. However, following Hurricane Maria, the experimental hurricane treatment plots of 2014 had 3.6 times greater seed removal by invasive rats than did the reference plots, which may have resulted from rats selecting post-hurricane forest patches with greater understory cover for foraging. Invasive rodents are resistant to hurricane disturbance in this forest. Predictions of increased hurricane frequency from expected climate change should result in forest with more frequent periods of grassy understories and mouse presence, as well as with heightened rat foraging for fruit and seed in pre-existing areas of disturbance.</p>
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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.