Find research datasets worth reusing

opencc-zeroNov 2023View details →

The umbrella value of caribou management strategies for biodiversity conservation in boreal forests under global change

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.

opencc-by-4.0Dec 2023View details →

Interacting impacts of hydrological changes and air temperature warming on lake temperatures highlight the potential for adaptive management: Model output

This archive includes the output from the General Ocean Turbulence Model for a series of simulations that used differing model drivers (inflow discharge, Q, and air temperature, T).  The Experiment_output.zip contains text files generated from the GOTM workflow containing modelled water temperatures and the Mod_z.txt are the corresponding depths for these temperatures. The file name corresponds to the change made to the driving data from baseline (unchanged conditions), a combination of air temperature increase and flow percentage change e.g. Mod_temp_T_2_Q_1.5 refers to an air temperature increase of 2 degrees Celsius and a flow increase of 50% and a Mod_temp_T_3.5_Q_0.7 refers to an air temperature increase of 3.5 degrees Celsius and a flow decrease of 30%.

opencc-zeroDec 2023View details →

Data from: navigating uncertainty: managing herbivore communities enhances savanna ecosystem resilience under climate change

Savannas are characterized by water scarcity and degradation, making them highly vulnerable to increased uncertainties in water availability resulting from climate change. This poses a significant threat to ecosystem services and rural livelihoods that depend on them. In addition, the lack of consensus among climate models on precipitation change makes it difficult for land managers to plan for the future. Therefore, savanna rangeland management needs to develop strategies that can sustain savanna resilience and avoid tipping points under an uncertain future climate. Our study aims to analyze the impacts of climate change and rangeland management on degradation in savanna ecosystems of southern Africa, providing insights for the management of semi-arid savannas under uncertain conditions worldwide. To achieve this, we simulated the effects of projected changes in temperature and precipitation, as predicted by ten global climate models, on water resources and vegetation (cover, functional diversity, tipping points (transition from grass-dominated to shrub-dominated vegetation)). We simulated three different rangeland management options (herbivore community dominated by grazers, by browser and by mixed-feeders), each with low and high animal densities using the ecohydrological model EcoHyD. Our results identified intensive grazing as the primary contributor to the increased risk of degradation in response to changing climatic conditions across all climate change scenarios. This degradation encompassed a reduction in available water for plant growth within the context of predicted climate change. It also entails a decline in the overall vegetation cover, the loss of functionally important plant species, and the inefficient utilization of available water resources, leading to earlier tipping points. Our findings underscore that in the face of climate uncertainty, farmers' most effective strategy for securing their livelihoods and ecosystem stability is to integrate browsers and apply management of mixed herbivore communities. This management approach not only significantly delays or averts tipping points but also maintained greater plant functional diversity, fostering a more robust and resilient ecosystem that acts as a vital buffer against adverse climatic conditions.

opencc-by-4.0Apr 2022View details →

Managing for the unexpected: building resilient forest landscapes to cope with global change: Supporting data

Input files and installers 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. The model documentation is freely available at <a href="https://www.landis-ii.org/">https://www.landis-ii.org/</a> 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>. If interested in using this dataset for a research study or project, please contact <a href="https://www.marco-mina.com">Marco Mina</a> --------------------- Mina, M., Messier, C., Duveneck, M., Fortin, M. J., & Aquilué, N. (2022) Managing for the unexpected: building resilient forest landscapes to cope with global change. Global Change Biology 28, 4323– 4341 <a href="https://doi.org/10.1111/gcb.16197">https://doi.org/10.1111/gcb.16197</a> 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.

openafl-3.0Dec 2014View details →

Near real-time ultrahigh-resolution imaging from unmanned aerial vehicles for sustainable land use management and biodiversity conservation in semi-arid savanna under regional and global change (SAVMAP)

To prevent aggravation of existing poverty in semi-arid savannas, a comprehensive concept for the sustainable adaptive management and use of these ecosystems under unprecedented conditions is needed. SAVMAP is an innovative, trans-, and inter-disciplinary initiative whose goal is to develop a valuable monitoring tool for both sustainable land-use management and rare species conservation (black rhinoceros) in semi-arid savanna in Namibia. SAVMAP uses near real-time ultrahigh-resolution photographic imaging (NURI) facilitated by unmanned aerial vehicles (UAVs) designed at EPFL.

Table 2 in Changes in a soil microarthropod community in the vicinity of dominant tree species under trampling management at the Safari Zoological Center, Israel

Table 2 Mean values (± SD) of soil physical and chemical parameters at different treatment sites at the Safari Zoological Center, Israel, December 2013. SM = soil moisture, OM = organic matter, pH = soil pH, SEC = soil electrical conductivity, SD = soil density, WHC = water-holding capacity. OE = open places under enclosure conditions, OT = open places under trampling conditions; EE E. = camaldulensis canopy habitat under enclosure conditions, ET = E. camaldulensis canopy habitat under trampling conditions, TE T =. aphylla canopy habitat under enclosure conditions, TT = T. aphylla canopy habitat under trampling conditions, CE = C. sempervirens canopy habitat under enclosure conditions, CT = C. sempervirens canopy habitat under trampling conditions. Different letters in the same column represent significant difference p at <0.05.<table><tbody><tr><th></th><th>SM (%)</th><th>OM (%)</th><th>pH</th><th>SEC (µ -1) cm</th><th>SD (g -3) cm</th><th>WHC (%)</th></tr></tbody><tbody><tr><th>OE</th><td>25.6±3.4a</td><td>1.1±0.2b</td><td>7.5±0.2b</td><td>87.6±17.5d</td><td>1.1±0.0b</td><td>53.6±0.9ab</td></tr><tr><th>OT</th><td>7.8±1.7c</td><td>0.2±0.0e</td><td>7.6±0.0b</td><td>150.3±51.3c</td><td>1.6±0.0a</td><td>25.6±1.0c</td></tr><tr><th>EE</th><td>16.6±1.6b</td><td>1.3±0.2b</td><td>7.6±0.0b</td><td>130.2±9.4cd</td><td>1.0±0.1c</td><td>52.6±11.1ab</td></tr><tr><th>ET</th><td>23.2±3.8a</td><td>2.0±0.3a</td><td>7.6±0.0b</td><td>255.3±39.6ab</td><td>1.1±0.0bc</td><td>31.9±3.5c</td></tr><tr><th>TE</th><td>21.9±4.4ab</td><td>0.4±0.1d</td><td>7.9±0.0a</td><td>152.0±17.8c</td><td>1.0±0.1c</td><td>52.1±14.6ab</td></tr><tr><th>TT</th><td>14.1±5.2b</td><td>1.1±0.1b</td><td>7.6±0.1b</td><td>254.1±48.0ab</td><td>1.0±0.1c</td><td>43.3±6.2b</td></tr><tr><th>CE</th><td>26.9±3.4a</td><td>0.8±0.3c</td><td>7.6±0.1b</td><td>209.9±22.5b</td><td>1.0±0.1c</td><td>56.3±5.8a</td></tr><tr><th>CT</th><td>22.0±6.0ab</td><td>0.5±0.2d</td><td>7.8±0.1a</td><td>275.9±21.9a</td><td>1.0±0.0c</td><td>43.0±3.9b</td></tr></tbody></table>

Table 3 in Changes in a soil microarthropod community in the vicinity of dominant tree species under trampling management at the Safari Zoological Center, Israel

Table 3 Effects of sampling habitat (“Habitat”), trampling management (“Trampling”), and their interaction on soil parameters, abundance of soil microarthropods, and diversity indices of soil Acari at the Safari Zoological Center, Israel, December 2013 (General linear model, α = 0.05). * p <0.05, ** p <0.01, *** p <0.001.<table><tbody><tr><th>Microarthropods</th><th>d f</th><th>F</th><th>Soil parameters</th><th>d f</th><th>F</th></tr></tbody><tbody><tr><th>Total microarthropod abundance</th><td></td><td></td><td>Soil moisture</td><td></td><td></td></tr><tr><th>Model</th><td>8</td><td>15.85***</td><td>Model</td><td>8</td><td>109.38***</td></tr><tr><th>Trampling</th><td>1</td><td>39.13***</td><td>Trampling</td><td>1</td><td>18.46***</td></tr><tr><th>Habitat</th><td>3</td><td>1.65</td><td>Habitat</td><td>3</td><td>5.90**</td></tr><tr><th>Trampling * Habitat</th><td>3</td><td>4.89**</td><td>Trampling * Habitat</td><td>3</td><td>12.84***</td></tr><tr><th>Collembola abundance</th><td></td><td></td><td>Organic matter</td><td></td><td></td></tr><tr><th>Model</th><td>8</td><td>4.90**</td><td>Model</td><td>8</td><td>116.32***</td></tr><tr><th>Trampling</th><td>1</td><td>11.18**</td><td>Trampling</td><td>1</td><td>0.05</td></tr><tr><th>Habitat</th><td>3</td><td>2.29</td><td>Habitat</td><td>3</td><td>48.99***</td></tr><tr><th>Trampling * Habitat</th><td>3</td><td>2.56</td><td>Trampling * Habitat</td><td>3</td><td>32.99***</td></tr><tr><th>Other arthropod abundance</th><td></td><td></td><td>Soil pH</td><td></td><td></td></tr><tr><th>Model</th><td>8</td><td>1</td><td>Model</td><td>8</td><td>35120.21***</td></tr><tr><th>Trampling</th><td>1</td><td>1.8</td><td>Trampling</td><td>1</td><td>0.5</td></tr><tr><th>Habitat</th><td>3</td><td>0.73</td><td>Habitat</td><td>3</td><td>4.69*</td></tr><tr><th>Trampling * Habitat</th><td>3</td><td>0.73</td><td>Trampling * Habitat</td><td>3</td><td>13.93***</td></tr><tr><th>Soil Acari abundance</th><td></td><td></td><td>Electrical conductivity</td><td></td><td></td></tr><tr><th>Model</th><td>8</td><td>18.85***</td><td>Model</td><td>8</td><td>156.31***</td></tr><tr><th>Trampling</th><td>1</td><td>43.09***</td><td>Trampling</td><td>1</td><td>61.80***</td></tr><tr><th>Habitat</th><td>3</td><td>0.88</td><td>Habitat</td><td>3</td><td>20.89***</td></tr><tr><th>Trampling * Habitat</th><td>3</td><td>3.60*</td><td>Trampling * Habitat</td><td>3</td><td>1.76</td></tr><tr><th>Taxon richness of soil Acari</th><td></td><td></td><td>Soil density</td><td></td><td></td></tr><tr><th>Model</th><td>8</td><td>16.11***</td><td>Model</td><td>8</td><td>1769.86***</td></tr><tr><th>Trampling</th><td>1</td><td>34.68***</td><td>Trampling</td><td>1</td><td>57.12***</td></tr><tr><th>Habitat</th><td>3</td><td>3.17*</td><td>Habitat</td><td>3</td><td>82.99***</td></tr><tr><th>Trampling * Habitat</th><td>3</td><td>1.23</td><td>Trampling * Habitat</td><td>3</td><td>36.99***</td></tr><tr><th>Shannon index of soil Acari</th><td></td><td></td><td>Water-holding capacity</td><td></td><td></td></tr><tr><th>Model</th><td>8</td><td>18.88***</td><td>Model</td><td>8</td><td>155.49***</td></tr><tr><th>Trampling</th><td>1</td><td>51.07***</td><td>Trampling</td><td>1</td><td>45.98***</td></tr><tr><th>Habitat</th><td>3</td><td>4.03*</td><td>Habitat</td><td>3</td><td>3.22*</td></tr><tr><th>Trampling * Habitat</th><td>3</td><td>0.78</td><td>Trampling * Habitat</td><td>3</td><td>2.6</td></tr><tr><th>Simpson index of soil Acari</th></tr><tr><th>Model</th><td>8</td><td>13.42***</td><td></td><td></td><td></td></tr><tr><th>Trampling</th><td>1</td><td>0</td><td></td><td></td><td></td></tr><tr><th>Habitat</th><td>3</td><td>7.47**</td><td></td><td></td><td></td></tr><tr><th>Trampling * Habitat</th><td>3</td><td>5.22**</td><td></td><td></td><td></td></tr><tr><th>Evenness index of soil Acari</th></tr><tr><th>Model</th><td>8</td><td>42.11***</td><td></td><td></td><td></td></tr><tr><th>Trampling</th><td>1</td><td>120.61***</td><td></td><td></td><td></td></tr><tr><th>Habitat</th><td>3</td><td>3.68*</td><td></td><td></td><td></td></tr><tr><th>Trampling * Habitat</th><td>3</td><td>1.82</td><td></td><td></td><td></td></tr></tbody></table>

Table 1 in Changes in a soil microarthropod community in the vicinity of dominant tree species under trampling management at the Safari Zoological Center, Israel

Table 1 Sampling design (replication = 4) for sites at the Safari Zoological Center, Israel, December 2013. Herbaceous ground cover: +++ patchy; + a few plants, – no plants. OE = open places under enclosure conditions, OT = open places under trampling conditions; EE E =. camaldulensis canopy habitat under enclosure conditions, ET = E. camaldulensis canopy habitat under trampling conditions, TE T =. aphylla canopy habitat under enclosure conditions, TT T =. aphylla canopy habitat under trampling conditions, CE = C. sempervirens canopy habitat under enclosure conditions, CT = C. sempervirens canopy habitat under trampling conditions.<table><tbody><tr><th>Habitat</th><th>Code</th><th>Treatment</th><th>Tree height (m)</th><th>Tree canopy crown (m2)</th><th>Herbaceous vegetation</th><th>Soil physical/biological top layer</th><th>Litter layer (cm)</th></tr></tbody><tbody><tr><th>Open spaces</th><td>OT OE</td><td>Trampling Enclosure</td><td>- -</td><td>- -</td><td>No +++</td><td>No Physical top layer</td><td>No No</td></tr><tr><th>E. camaldulensis</th><td>ET EE</td><td>Trampling Enclosure</td><td>10-13</td><td>6×8</td><td>No +</td><td>No Biological top layer</td><td>No 2-3</td></tr><tr><th>T. aphylla</th><td>TT TE</td><td>Trampling Enclosure</td><td>14-16</td><td>8×8</td><td>No +++</td><td>No Physical top layer</td><td>No Few</td></tr><tr><th>C. sempervirens</th><td>CT CE</td><td>Trampling Enclosure</td><td>14-16</td><td>7×9</td><td>No +</td><td>No Biological layer</td><td>No 1-2</td></tr></tbody></table>

Table 4 in Changes in a soil microarthropod community in the vicinity of dominant tree species under trampling management at the Safari Zoological Center, Israel

Table 4 Correlation coefficients (Pearson correlation, r) between the abundance of microarthropods, diversity indices of soil Acari, and soil parameters at the Safari Zoological Center, Israel, December 2013. SM = soil moisture, OM = organic matter, pH = soil pH, SEC = soil electrical conductivity, SD = soil density, WHC = water-holding capacity p. <*0.05, ** p <0.01, *** p <0.001.<table><tbody><tr><th>Index</th><th></th><th>SM</th><th>OM</th><th>pH</th><th>SEC</th><th>SD</th><th>WHC</th></tr></tbody><tbody><tr><th></th><td>Acari</td><td>0.349*</td><td>0.068</td><td>-0.198</td><td>-0.506**</td><td>-0.299</td><td>0.571***</td></tr><tr><th>Abundance</th><td>Collembola Other soil arthropods</td><td>0.153 0.202</td><td>0.210 0.098</td><td>-0.486** -0.294</td><td>-0.506** -0.209</td><td>-0.107 -0.065</td><td>0.207 0.245</td></tr><tr><th></th><td>Total microarthropod</td><td>0.292</td><td>0.158</td><td>-0.403*</td><td>-0.574***</td><td>-0.233</td><td>0.445*</td></tr><tr><th>Diversity indices of Acari</th><td>Taxon richness Shannon index Simpson index</td><td>0.253 0.285 -0.006</td><td>0.023 0.032 -0.175</td><td>-0.098 -0.120 0.165</td><td>-0.392* -0.455** 0.240</td><td>-0.316 -0.293 -0.475**</td><td>0.561*** 0.585*** 0.336</td></tr><tr><th></th><td>Evenness index</td><td>0.387*</td><td>0.009</td><td>-0.203</td><td>-0.466**</td><td>-0.411*</td><td>0.739***</td></tr></tbody></table>

opencc-by-4.0Oct 2024View details →

Data analysis & code: Quantifying the impact of climate change and forest management on Swedish forest ecosystems using the dynamic vegetation model LPJ-GUESS

This file contains code to optimize the allometric parameters, to plot the figures, and details of the underlying data analysis in "Quantifying the impact of climate change and forest management on Swedish forest ecosystems using the dynamic vegetation model LPJ-GUESS" (Bergkvist et al.).

opencc-zeroDec 2022View details →

Future supply of boreal forest ecosystem services is driven by management rather than by climate change

Forests provide a wide variety of ecosystem services (ES) to society. The boreal biome is experiencing the highest rates of warming on the planet and increasing demand for forest products. To foresee how to maximize the adaptation of boreal forests to future warmer conditions and growing demands of forest products, we need a better understanding of the relative importance of forest management and climate change on the supply of ecosystem services. Here, using Finland as a boreal forest case study, we assessed the potential supply of a wide range of ES (timber, bilberry, cowberry, mushrooms, carbon storage, scenic beauty, species habitat availability and deadwood) given seven management regimes and four climate change scenarios. We used the forest simulator SIMO to project forest dynamics for 100 years into the future (2016–2116) and estimate the potential supply of each service using published models. Then, we tested the relative importance of management and climate change as drivers of the future supply of these services using generalized linear mixed models. Our results show that the effects of management on the future supply of these ES were, on average, eleven times higher than the effects of climate change across all services but greatly differed among them (from 0.53 to 24 times higher for timber and cowberry, respectively). Notably, the importance of these drivers substantially differed among biogeographical zones within the boreal biome. The effects of climate change were 1.6 times higher in northern Finland than in southern Finland, whereas the effects of management were the opposite – they were three times higher in the south compared to the north. We conclude that new guidelines for adapting forests to global change should account for regional differences and the variation in the effects of climate change and management on different forest ES.

opencc-zeroJul 2023View details →

Cropland management impacts on soil organic carbon stock changes in US croplands from 1990 to 2015

This geospatial dataset represents soil organic carbon stock changes estimated from a counterfactual analysis of climate-smart soil management practices that were adopted in U.S. croplands between 1990 and 2015. The counterfactual scenarios are relative to historical cropland management implemented in the U.S. for the temporal domain of this study. These data provide a large-scale overview of the carbon stock changes in US cropland agricultural soils associated with conservation tillage, manure amendments, cover crops terminated with cultivation, cover crop terminated with herbicide, hay and pasture in rotation with annual crops, set-aside/Conservation Reserve Program lands. Data were generated using the DayCent ecosystem model driven by cropping histories in the USDA National Resources Inventory (NRI) and associated agricultural management data. The average annual stock change was calculated for each management practice to determine the impact. Average rates of annual stock changes on a per-hectare basis (averaged from 1990 to 2015) are presented as a gridded dataset. Data are in a GeoTIFF format on a 5 km grid.

opencc-by-4.0Jun 2023View details →

Data from: Changes in environment and management practices improve foot health in zoo-housed flamingos

Summary This dataset accompanies the publication "Changes in Environment and Management Practices Improve Foot Health in Zoo-Housed Flamingos" published in Animals. This study tracked changes in foot lesions for an individual flock of Chilean flamingos (97 birds) at Dublin Zoo (Ireland) over an 18-month period in response to management and substrate changes . Photos of each flamingo's feet were taken on May 6th 2021, when all flamingos had access to their outdoor habitat (Time Point A). Photos were taken again on 16th April 2022, following a six month period when the flamingos were restricted to their indoor habitat due to a Government order to prevent the spread of Avian Influenza (Time Point B). Final photos were taken on 9th November 2022, six months following the release of the birds back into their outdoor habitat (Time Point C). Further details can be found in the corresponding publication.  Scoring was undertaken blindly by two independent and trained evaluators. These scores reflect the scoring metric developed by Nielsen et al. 2010, and include the four types of common flamingo foot lesion: hyperkeratosis, fissures, nodular lesions, and papillomatous growths. The independently calculated foot scores were subsequently compared, and in instances where the foot scores did not match, a consensus was sought between both evaluators to provide a final value for subsequent analysis. The data presented here reflects the consensus values used in the analysis. Discrepancies in the foot scores between both evaluators are reported and discussed in the corresponding publication.  Description of the Dataset One file is provided in .csv format. The file contains the following 11 columns:  <ul> <li>Time_Point: The Time Point at which photos were taken (A = 6th May 2021, B = 16th April 2022, and C = 9th November 2022).   </li> <li>Animal_Identifier: An anonymous code used to identify individual flamingos (n = 97).</li> <li>Hyperkeratosis_Total: The total hyperkeratosis score for that flamingo at that Time Point (considering both feet).</li> <li>Fissures_Total: The total fissures score for that flamingo at that Time Point (considering both feet).</li> <li>Nodular_Lesions_Total: The total nodular lesions score for that flamingo at that Time Point (considering both feet).</li> <li>Papillomatous_Growths_Total: The total papillomatous growths score for that flamingo at that Time Point (considering both feet).</li> <li>L_Total: The total left foot lesions score for that flamingo at that Time Point (considering all types of foot lesion).</li> <li>R_Total: The total right foot lesions score for that flamingo at that Time Point (considering all types of foot lesion).</li> <li>Overall_Total: The total foot lesions score for that flamingo at that Time Point (considering both feet and all types of foot lesion).</li> <li>Sex: The sex of the flamingo (Male or Female) </li> <li>Age: The age of the flamingo (Years)</li> </ul>   Acknowledgements We acknowledge and thank all Dublin Zoo staff and volunteers for their support and assistance throughout the project. Additionally, we thank Dr. Laura Kane for her technical assistance and support.      Disclaimer Despite our best efforts at screening the data for errors and inconsistencies, some information could be erroneous.    Credit If you use this dataset, please cite the corresponding publication: Mooney, A., McCall, K., Bastow, S., & Rose, P. (2023). Changes in Environment and Management Practices Improve Foot Health in Zoo-Housed Flamingos. Animals, 13(15), 2483. <a href="https://doi.org/10.3390/ani13152483">https://doi.org/10.3390/ani13152483</a>

opencc-zeroAug 2023View details →

Eutrophication, water quality, and fisheries: a wicked management problem with insights from a century of change in Lake Erie

The datasets here were used to examine relationships between the overall productivity of Lake Erie and the commercial harvest of lake whitefish (Coregonus clupeaformis), walleye (Sander vitreus), and yellow perch (Perca flavescens) during 1915–2011. Here, we provide the two datasets used in the paper by Sinclair et al. titled "Eutrophication, water quality, and fisheries: a wicked management problem with insights from a century of change in Lake Erie". Each dataset is provided as a separate tab in a single Excel worksheet. The first dataset ("Productivity") provides the annual values of the five metrics used to develop the index of overall Lake Erie productivity. The second dataset ("Commercial harvest") provides the total annual commercial harvest (kg) of the three fish species, which were obtained from the Great Lakes Fishery Commission (<a href="http://www.glfc.org/great-lakes-databases.php">http://www.glfc.org/great-lakes-databases.php</a>). A summary and explanation of each variable is provided in the "Info" tab. Further information on how values were calculated (and transformed if necessary) is provided in either the info tab or the methods and supporting information of the associated article.

controlledIPD-YESFeb 2026View details →

Wound Management Following Gl Tumor Surgery: Comparing Outcomes of Dressing Changes Versus Non-Dressing Techniques

ClinicalTrials.gov study NCT06263205. IPD Sharing: YES. Countries: 1. Publications: 13.

closedIPD-NOFeb 2026View details →

Mechanisms Of Change in Adolescent Pain Self-management

ClinicalTrials.gov study NCT04043962. IPD Sharing: NO. Countries: 1. Publications: 3.

restrictedIPD-UNDECIDEDFeb 2026View details →

A Study to Assess Changes in Clinical Management After DaTSCAN Imaging of Subjects With Clinically Uncertain Parkinsonism or an Illness With Similar Symptoms

ClinicalTrials.gov study NCT00382967. IPD Sharing: Not stated. Countries: 2. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →

Stories for Change: Digital Storytelling for Diabetes Self-Management Among Hispanic Adults

ClinicalTrials.gov study NCT03766438. IPD Sharing: Not stated. Countries: 1. Publications: 2.

publicAug 2023View details →

Eutrophication, water quality, and fisheries: a wicked management problem with insights from a century of change in Lake Erie

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