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1,141 results for “primary_productivity”
Pelagic primary production in northern lakes
<p>These datasets present data on pelagic gross primary production (GPP) of detailed depth profiles ("GPPzrates") and lake averages ("GPPlakeaverages") of summer pelagic GPP together with environmental and climatic data across 45 small and shallow lakes across northern Sweden. The datasets include 20 boreal, 6 subarctic, and 19 arctic lakes. </p>
Landscape determinants of lake benthic and pelagic primary production
<p>Global change affects gross primary production (GPP) in benthic and pelagic habitats of northern lakes by influencing catchment characteristics and lake water biogeochemistry. However, how changes in key environmental drivers manifest and impact total (i.e., benthic + pelagic) GPP and the partitioning of total GPP between habitats, here represented by the benthic share (autotrophic structuring) is unclear. This dataset presentes compiled data on summer gross primary productivity (GPP) in benthic and pelagic habitats sampled <em>in situ</em> between 2005-2017, together with water chemistry, from 26 shallow lakes (maximum 3.7-15.8 m deep) from three different sites in northern Sweden, located in the Arctic (Norrbotten), subarctic (Jämtland) and boreal (Västerbotten) biomes. The three study regions have variable elevation gradients and vegetation cover. The study lakes cover a wide range of DOC (1.5-16.3 mg·L<sup>-1</sup>) and accompanied water physico-chemistry.</p> <p>Using this dataset, we investigate how catchment properties (air temperature, land cover, hydrology) affect lake physico-chemistry and patterns of total GPP and autotrophic structuring. We find that total GPP was mostly light limited, due to high dissolved organic carbon (DOC) concentrations originating from catchment soils with coniferous vegetation and wetlands, which is further promoted by high catchment runoff. In contrast, autotrophic structuring related mostly to the relative size of the benthic habitat, and was potentially modified by CO<sub>2</sub> fertilization. Across Arctic and subarctic sites, DIC and CO<sub>2</sub> were unrelated to DOC, indicating that external inputs of inorganic carbon can influence lake productivity patterns independent of terrestrial DOC supply. By comparison, DOC and CO<sub>2</sub> were correlated across boreal lakes, suggesting that DOC mineralization acts as an important CO<sub>2</sub> source for these sites.</p> <p>Our results underline that GPP as a resource is regulated by landscape properties, and is sensitive to large-scale global changes (warming, hydrological intensification, recovery of acidification) that promote changes in catchment characteristics and aquatic physico-chemistry. Our findings aid in predicting global change impacts on autotrophic structuring, and thus community structure and resource use of aquatic consumers in general. Given the similarities of global changes across the Northern hemisphere, our findings are likely relevant for northern lakes globally. </p>
New protein production in primary pulmonary artery endothelial cells treated with insulin-like growth factor 1 treatment
<p>Maximum projections of flat-fielded and deconvolved epi-fluorescence imaging data for primary sheep pulmonary artery endothelial cells (PAEC) treated with vehicle or insulin-like growth factor 1 (IGF1) media.</p> <p>Two cell types: normal PAEC and persistent pulmonary hypertension of the newborn (PPHN) PAEC</p> <p>Three time points: 0 minutes, 1 hour, and 24 hours post-treatment</p> <p>Two fluorescence channels:<br> C0 - DAPI for nuclei (R37606, Life Technologies)<br> C1 - Click-IT new protein translation kit (C10428, C10429, Life Technologies)</p>
eLUE-GPP (MODIS): A global gross primary productivity product based on ecosystem light-use-efficiency model and MODIS EVI
<p>Gross Primary Productivity (GPP) represents the cumulative amount of carbon dioxide (CO<sub>2</sub>) assimilated by green plants through photosynthesis at specific time intervals and spatial scales. It is the main component of the carbon exchange between the terrestrial biosphere and the atmosphere, and has a major influence on global climate and terrestrial ecosystem functioning. Over the last two decades, the continuous and reliable collection of global land surface variables by EOS-MODIS, and the parallel development of the eddy-covariance flux tower network (FLUXNET) have enabled the integration of MODIS observations with tower measurements for the calibration and validation of remote sensing models to obtain global GPP estimates. Despite the significant progress and success to date, current remote sensing GPP models based on the light use efficiency (LUE) concept share several limitations, including the difficulty in accurately predicting LUE variability and the associated use of land cover maps and look-up tables for biome specific maximum LUE, further down-regulated by coarse resolution interpolated meteorological data, which introduce significant uncertainties in the predicted GPP. To address the above limitations, here we applied a simple yet ecologically sound remote sensing GPP model based on the ecosystem light use efficiency (eLUE) concept, using the more than two decades of global MODIS Enhanced Vegetation Index (EVI) product and the publicly available FLUXDATA2015 dataset, to generate a global 5 km, 16-d GPP product (eLUE-GPP) from February 2000 to March 2024. Cross-validation with 202 flux tower sites (1494 site/year) showed favorable accuracy of eLUE-GPP (hereafter GPP<sub>eLUE</sub>) (<em>R</em><sup>2</sup> = 0.71, RMSE = 2.11 g C m<sup>-2</sup> d<sup>-1</sup>). The uncertainty associated with GPP<sub>eLUE</sub> is comparatively lower than that of the other global GPP datasets (MOD17, FluxSat, VPM, among others). We have also calculated the uncertainty analytically for each GPP estimate based on the law of error propagation, which allows quantification of the error budget in applications such as Earth system model benchmarking and atmospheric inversion. Our estimate of global total annual GPP, averaged over the period 2001-2023, was 138.46±13.92 Pg C yr<sup>-1</sup>. Furthermore, we found a significant increasing trend in global total annual GPP at a rate of 0.28±0.05 Pg C yr<sup>-1</sup> (<em>p</em> < 0.001) from 2001 to 2023, particularly in eastern Asia, northern India, Europe, eastern North America, and central South America. We expect that the eLUE-GPP product will enable a more accurate diagnostic analysis of the global carbon budget and thus contribute to climate change research.</p>
Above ground net primary productivity
<b>Description: </b><p>Tree plot data</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/110"><b>Above ground net primary productivity</b></a></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=71">here</a></p><p><b>Data worksheets: </b>There are 1 data worksheets in this dataset:</p><ol><li><p><b>Live tree measurements</b> (Worksheet Data)</p><p>Dimensions: 4795 rows by 38 columns</p><p>Description: Tree plot data from first survey (2010/11)</p><p>Fields: </p><ul><li><b>2ndOrder</b>: SAFE Project site code (Field type: Location)</li><li><b>SurveyNum</b>: Survey number (Field type: ID)</li><li><b>Date</b>: Date of survey (Field type: Date)</li><li><b>TagNum</b>: Tag number attached to the tree (Field type: ID)</li><li><b>Area</b>: Subplot location (Field type: Categorical)</li><li><b>Tree/Vine</b>: Tree or vine (Field type: Categorical)</li><li><b>Easting</b>: Location within plot (m east of origin in SW corner) (Field type: Numeric)</li><li><b>Northing</b>: Location within plot (m north of origin in SW corner) (Field type: Numeric)</li><li><b>PreviousNum</b>: Previous tag number for this tree (Field type: ID)</li><li><b>POM</b>: Height above ground at which tree is manually measured (Field type: Numeric)</li><li><b>DBHdend</b>: Tree diameter as recorded on dendrometer (Field type: Numeric)</li><li><b>DBH</b>: tree diameter measured manually (Field type: Numeric)</li><li><b>DBHvert</b>: NA (Field type: Numeric)</li><li><b>DBHwidest</b>: NA (Field type: Numeric)</li><li><b>CaliperScore</b>: NA (Field type: Numeric)</li><li><b>CanopyRad.N</b>: Distance from tree trunk to edge of crown (north) (Field type: Numeric)</li><li><b>CanopyRad.E</b>: Distance from tree trunk to edge of crown (east) (Field type: Numeric)</li><li><b>CanopyRad.S</b>: Distance from tree trunk to edge of crown (south) (Field type: Numeric)</li><li><b>CanopyRad.W</b>: Distance from tree trunk to edge of crown (west) (Field type: Numeric)</li><li><b>Crown</b>: Crown irradiance (Field type: Ordered Categorical)</li><li><b>HeightTotal</b>: Tree height (Field type: Numeric)</li><li><b>HeightBranch</b>: Height above ground where first branch is encountered (Field type: Numeric)</li><li><b>HeightLeaf</b>: Height above ground where the first leaves are encountered (Field type: Numeric)</li><li><b>TreeAttach</b>: TagNum of the tree that the vine is attached to (vines only) (Field type: ID)</li><li><b>CanopyVines</b>: Proportion of canopy covered by vines (Field type: Numeric)</li><li><b>Epiphytes</b>: NA (Field type: Numeric)</li><li><b>OPEpiphyteTrunk</b>: NA (Field type: Numeric)</li><li><b>Fruiting</b>: Amount of flowering (Field type: Ordered Categorical)</li><li><b>FruitingOP</b>: Number of fruit bunches (oil palm only) (Field type: Numeric)</li><li><b>Flowering</b>: Amount of flowering (Field type: Ordered Categorical)</li><li><b>FloweringOP</b>: Number of flower bunches (oil palms only) (Field type: Numeric)</li><li><b>Status</b>: Tree status (Field type: Comments)</li><li><b>LeafHerbivoryOP</b>: Amount of herbivory on oil palm fronds (Field type: Numeric)</li><li><b>NumFrondsOP</b>: Number of fronds; counted on oil palm trees only (Field type: Numeric)</li><li><b>Species</b>: Field ID of tree species, mostly in local names (Field type: Comments)</li><li><b>Recorder</b>: Field team collecting and recording the data (Field type: Comments)</li><li><b>Notes</b>: Notes related to the tree (Field type: Comments)</li></ul><br></li></ol><p><b>Date range: </b>2010-07-01 to 2011-08-25</p><p><b>Latitudinal extent: </b>4.6353 to 4.7714</p><p><b>Longitudinal extent: </b>116.9477 to 117.7028</p>
Pre-analysis and figure data for Lomax et al. (2024), Untangling the environmental drivers of gross primary productivity in African rangelands
<p>Data required to reproduce main analyses and main text figures for the following publication:</p> <p>Lomax, G. A., Powell, T. W. R., Lenton, T. M., Economou, T., and Cunliffe, A. M. (in press), Untangling the environmental drivers of gross primary productivity in African rangelands.</p> <p> </p> <p>File details:</p> <ol> <li>df_annual.csv - the full 19-year dataset of model variables for reproducing the main analysis (for Figures 2-3).</li> <li>df_multi_annual.csv - a smaller dataset of multi-annual mean and variability variables for reproducing the analysis behind Figure 4.</li> <li>Fig1_data.tif - raster dataset containing the four variables shown in Figure 1.</li> <li>Fig2_data.csv - model results for the main analysis underlying Figure 2.</li> <li>Fig3_data.csv - model results for the binned analysis underlying Figure 3.</li> <li>Fig4_data.csv - model results for the multi-annual analysis underlying Figure 4.</li> </ol>
D-PLACE dataset derived from NASA TERRA/MODIS 'Net Primary Productivity'
<p>Cite the source of the dataset as:</p> <blockquote> <p>NASA. Net Primary Productivity (1 month - TERRA/MODIS)</p> </blockquote>
The gross primary productivity and leaf area index from TRENDY v7 project
<p>The gross primary productivity and leaf area index from TRENDY v7 DGVMs S3, including:</p> <p>CABLE-POP</p> <p>CLASS-CTEM</p> <p>CLM5.0</p> <p>DLEM</p> <p>JSBACH</p> <p>JULES</p> <p>LPX</p> <p>OCN</p> <p>ORCHIDEE</p> <p>ORCHIDEE-CNP</p> <p>SDGVM</p> <p>SURFEX</p> <p>VISIT</p>
Sea-ice, primary productivity and ocean temperatures at the Antarctic marginal zone during late Pleistocene
<p>These data in excel refer to all proxies used to reconstruct late Quaternary sea ice and productivity in in cape Adare, Ross Sea, Antarctica, for the publication in Quaternary Science Reviews, for open access </p>
Aboveground net primary productivity in regenerating seasonally dry tropical forest: contributions of rainfall, forest age, and soil
<p>Identifying factors controlling forest productivity is critical to understanding forest-climate change feedbacks, modeling vegetation dynamics, and carbon finance schemes. However, little research has focused on productivity in regenerating tropical forest which are expanding in their fraction of global area have an order of magnitude larger carbon uptake rates relative to older forest.</p> <p>We examined aboveground net primary productivity (ANPP) and its components (wood production and litterfall) over ten years in forest plots that vary in successional age, soil characteristics, and species composition using band dendrometers and litterfall traps in regenerating seasonally dry tropical forests in northwestern Costa Rica.</p> <p>We show that the components of ANPP are differentially driven by age and annual rainfall and that local soil variation is important. Total ANPP was explained by a combination of age, annual rainfall, and soil variation. Wood production comprised 35% of ANPP on average across sites and years, and was explained by annual rainfall but not forest age. Conversely, litterfall increased with forest age and soil fertility yet was not affected by annual rainfall. In this region, edaphic variability is highly correlated with plant community composition. Thus, variation in ecosystem processes explained by soil may also be partially explained by species composition.</p> <p>These results suggest that future changes in annual rainfall can alter the secondary forest carbon sink, but that this effect will be buffered by the litterfall flux which varies little among years. In determining the long-term strength of the secondary forest carbon sink, both rainfall and forest age will be critical variables to track. We also conclude that a detailed understanding of local site variation in soils and plant communities may be required to accurately predict the impact of changing rainfall on forest carbon uptake.</p> <p>Synthesis We show that in seasonally dry tropical forests, annual rainfall has a positive relationship with the growth of aboveground woody tissues of trees and that droughts lead to significant reductions in aboveground productivity. These results provide evidence for climate change – carbon cycle feedbacks in the seasonal tropics and highlight the value of longitudinal data on forest regeneration.</p>
Datasets for: Primary production and habitat stability organize marine communities
<p><strong>Aim: </strong>The emergence of pattern in the natural world can carry important messages about underlying processes. For example, collections of broadly similar terrestrial ecosystems have historically been categorized as biomes – groupings of systems which sort along energetic and structural process axes. In marine systems however, a similar classification of biomes has not emerged. The aim here is to develop an effective classification scheme for marine biomes and communities.</p> <p><strong>Approach: </strong>Candidate predictor variables that could explain pattern and process in differentiating marine communities, such as light, nutrients, depth, etc., were collected from the existing literature with a systematic review. The candidate predictors were then evaluated in an inductive process, allowing community level observations to demonstrate patterns across marine biomes. Marine biomes and communities were identified <i>a priori</i>,<i> </i>and emergent patterns were evaluated quantitatively, via Principal Component ordination based on the vectors of explanatory predictors, and qualitatively via mapping.</p> <p><strong>Conclusions: </strong>Gross primary production and substrate mobility not only effectively sort marine biomes, but also work on finer scales discriminating communities within biomes. As a result, these predictors were more effective in classifying marine communities than other scales, such as available light and nutrients. The richness of this classification is also demonstrated in revealing other patterns, such as the distribution of human impacts. The effectiveness of this mapping provides support for, but is not a test of, the hypothesis that primary production and substrate mobility are important underlying processes that interact to structure marine ecosystems.<i> </i></p>
Belowground net primary productivity stability in response to a nitrogen addition gradient in an alpine meadow
<p>1.Temporal stability of ecosystem productivity is important for providing reliable ecosystem services under global changes. Great efforts have been made to explore the response of aboveground net primary productivity (ANPP) stability to nitrogen (N) enrichment, yet how it affects belowground net primary productivity (BNPP) stability remains elusive, which hinders a comprehensive understanding of ecosystem stability from the view of a whole system.</p> <p>2. Here, using a field manipulative experiment with six N addition rates (0, 2, 4, 8, 16, 32 g N m-2 year-1), we explored the response patterns and drivers of BNPP stability in the topsoil (0-20 cm) and subsoil (20-40 cm) in the alpine meadow.</p> <p>3. The results showed that BNPP stability at both soil depths showed a unimodal response to increasing N addition rates. Specifically, for both the topsoil and subsoil, low-level N addition significantly promoted BNPP stability, while high doses of N addition had no significant impact on BNPP stability, suggesting that current low level of N deposition likely benefits the stable provision of belowground functioning. Furthermore, dominant species stability and species richness contributed most to the changes in BNPP stability in the topsoil, whereas only dominant species stability was the dominant driver of BNPP stability in the subsoil.</p> <p>4. This study is among the first to illuminate the main mechanisms underlying the responses of BNPP stability to N enrichment at various soil depths, which will advance our current understanding of N addition effects on belowground processes and benefit the sustainable provision of ecosystem functioning in the context of atmospheric N deposition.</p>
The potential bias of nitrogen deposition effects on primary productivity and biodiversity
<p><span>Atmospheric nitrogen (N) deposition is composed of both inorganic N (IN) and organic N (ON), and these sources of N may exhibit different impacts on ecosystems. However, our understanding of the impacts of N deposition is largely based on experimental gradients of INs or more rarely ONs. Thus, the effects of N deposition on ecosystem productivity and biodiversity may be biased. We explored the differential impacts of different IN:ON ratios on aboveground net primary productivity (ANPP) and plant species richness in a typical temperate grassland with a long-term N addition experiment. Our results showed that N addition significantly increased ANPP and reduced species richness. While the IN:ON ratios showed no different effects on ANPP, more species loss occurred with increasing IN:ON ratios. Thus, the evaluation of N deposition on biodiversity might be overestimated if only IN is added or underestimated if only ON is added.</span></p>
Dataset supporting the paper "Effect of prebiotic fermentation products from primary human gut microbiota on an in vitro intestinal model"
<p>Short chain fatty acids (SCFA) originate from the bacterial fermentation of dietary fibre in the gastrointestinal tract. They are hypothesised to play a key role in microbiota–gut–brain crosstalk and the effect of individual SCFAs or mixtures thereof has been broadly studied. However, studies using fermentation products to evaluate the effect of microbiota-targeted interventions, such as prebiotics, probiotics, or diet, are sparse, particularly in humans. In addition, the complexity of these physiological processes translates as a challenge for their simulation<em> in vitro</em>. In this work, fermentation products of prebiotic-enriched media by bacteria present in primary human faecal samples were tested using an epithelium model based on a Caco-2/HT29-MTX co-culture. The prebiotics raftilose and fructo-oligosaccharides (FOS) were tested and the experimental conditions (contact time and minimal dilution) optimised to avoid cytotoxicity. None of the conditions tested compromised the intestinal epithelium integrity as verified by the TEER and the expression of the tight junction-specific protein – occludin. In addition, none of the fermentation products caused an inflammatory response as determinedby the expression of inflammatory genes by qRT-PCR. The products of fermentation of media enriched with FOS showed a moderate protective effect against the formation of reactive oxygen species. This work provides an important basis for the development of <em>in vitro</em> models using a simple approach to evaluate host-gut microbiota interactions, using co-cultures of intestinal cell lines and products of <em>in vitro</em> fermentations by primary human gut microbiota. </p>
The sensitivity of primary productivity in Disko Bay, a coastal Arctic ecosystem to changes in freshwater discharge and sea ice cover
<p>Data for figure 4 in <a href="https://doi.org/10.5194/egusphere-2022-916">https://doi.org/10.5194/egusphere-2022-916</a></p>
Related data to article "Environmental Drivers of Gross Primary Productivity and Light Use Efficiency of a Temperate Spruce Forest"
<p>Data related to the article "Environmental Drivers of Gross Primary Productivity and Light Use Efficiency of a Temperate Spruce Forest", currently (2022-12-05) under review for publication in JGR:Biogeosciences.</p>
Input-Output Global Hybrid Analysis of Agricultural Primary Production (IO-GHAAP) Database
<p>A commonly used method to examine the relationship between global water consumption and production is input--output analysis. However, between approximately 70% and 90% of freshwater consumption occurs in agricultural primary production, which is often represented by only a small percentage of the total number of sectors in input-output databases. In addition, the assessment of the impact of water consumption is usually carried out at the national level.</p> <p><br> Therefore, the primary objective of the Input-Output Global Hybrid Analysis of Agricultural Primary Production (IO-GHAAP) approach was to improve assessments of water use and its impacts in input-output analysis.</p> <p><br> To achieve this objective, a global spatial model of agricultural primary production <em>MapSPAM</em> (IFPRI, 2019) was integrated into the existing input-output database <em>GLORIA</em> (Lenzen et al., 2017, 2021) via prorating. The resulting IO-GHAAPP approach includes (1) a disaggregated input-output database and novel environmental extensions for freshwater consumption and scarcity. The IO-GHAAPP database consists of 150 categories and 164 regions, resulting in a total of 24,600 region-category combinations. Forty-two of the categories are dedicated to agricultural primary production (28%). In comparison, the source input--output data consist of 120 categories and 164 regions, resulting in a total of 19,680 region-category combinations, of which 14 are dedicated to agricultural primary production (12%).</p> <p> </p> <p><strong>Please cite as:</strong></p> <p>Bunsen, Jonas, Vlad Coroamă, and Matthias Finkbeiner. 2023. ‘Input-Output Global Hybrid Analysis of Agricultural Primary Production (IO-GHAAPP) Database’. <em>Sustainability</em> 15 (2). <a href="https://doi.org/10.3390/su15129351">https://doi.org/10.3390/su15129351</a>.</p> <p> </p> <p><strong>References:</strong></p> <ul> <li>IFPRI. 2019. ‘Global Spatially-Disaggregated Crop Production Statistics Data for 2010 Version 2.0’. Harvard Dataverse. <a href="https://doi.org/10.7910/DVN/PRFF8V">https://doi.org/10.7910/DVN/PRFF8V</a>.</li> <li>Lenzen, Manfred, Arne Geschke, Muhammad Daaniyall Abd Rahman, Yanyan Xiao, Jacob Fry, Rachel Reyes, Erik Dietzenbacher, et al. 2017. ‘The Global MRIO Lab - Charting the World Economy’. <em>Economic Systems Research</em> 29 (2): 158–86. <a href="https://doi.org/10.1080/09535314.2017.1301887">https://doi.org/10.1080/09535314.2017.1301887</a>.</li> <li>Lenzen, Manfred, Arne Geschke, James West, Jacob Fry, Arunima Malik, Stefan Giljum, Llorenç Milà i Canals, et al. 2021. ‘Implementing the Material Footprint to Measure Progress towards Sustainable Development Goals 8 and 12’. <em>Nature Sustainability</em>, December. <a href="https://doi.org/10.1038/s41893-021-00811-6">https://doi.org/10.1038/s41893-021-00811-6</a>.</li> </ul>
Dataset for: Immediate and carry-over effects of late-spring frost and growing season drought on forest gross primary productivity capacity in the Northern Hemisphere
<p>Forests are increasingly exposed to extreme global warming-induced climatic events. However, the immediate and carry-over effects of extreme events on forests are still poorly understood. Gross primary productivity (GPP) capacity is regarded as a good proxy of the ecosystem's functional stability, reflecting its physiological response to its surroundings. Using eddy covariance data from 34 forest sites in the Northern Hemisphere, we analyzed the immediate and carry-over effects of late-spring frost (LSF) and growing season drought on needle-leaf and broadleaf forests. Path analysis was applied to reveal the plausible reasons behind the varied responses of forests to extreme events. The results show that LSF had clear immediate effects on the GPP capacity of both needle-leaf and broadleaf forests. However, GPP capacity in needle-leaf forests was more sensitive to drought than in broadleaf forests. There was no interaction between LSF and drought in either needle-leaf or broadleaf forests. Drought effects were still visible when LSF and drought coexisted in needle-leaf forests. Path analysis further showed that the response of GPP capacity to drought differed between needle-leaf and broadleaf forests, mainly due to the difference in the sensitivity of canopy conductance. Moreover, LSF had a more severe and long-lasting carry-over effect on forests than drought. These results enrich our understanding of the mechanisms of forest response to extreme events across forest types.</p>
Improving gross primary production estimation accuracy on the Qinghai-Tibet Plateau considering the effect of atmospheric CO2 fertilization
<p>This GPP dataset was generated by the improved GPP estimation model which introduced atmospheric CO<sub>2</sub> fertilization effect and canopy-to-leaf CO<sub>2</sub> concentration gradients into the CASA model. The dataset was provided in TIF format at a month interval. The valid value ranges from 0 to 1000, and the background filled value is set to NoData. The scale factor of the data is 1. Each TIF file represents a month GPP at a daily cumulative value (unit: g C m<sup>-2</sup> month<sup>-1</sup>).</p>
Top-down vs. bottom-up: Grazing and upwelling regime alter patterns of primary productivity in a warm-temperate system
<p>Community structure is driven by biological interactions and physical processes that can vary across environmental gradients and spatial scales. Early ecological models focused on the role of resource availability (i.e. bottom-up effects), predicting that the strength of top-down control varied along gradients of primary productivity and that local species interactions determined community structure. However, the role of regional scale oceanographic processes in determining species interactions and community structure is now widely recognized, with bottom-up effects such as coastal upwelling driving regional scale patterns of resource availability. Such nutrient subsidies can significantly alter primary production and drive changes in algae-herbivore interactions in rocky intertidal habitats. However, despite the potential for upwelling to alter these interactions, studies investigating the effects of upwelling and grazing pressure are scarce, particularly for warm-temperate systems, and generally cover narrow geographical ranges. Using in-situ herbivore exclusion experiments replicated across multiple upwelling regimes, we investigated the effects of both grazing pressure and upwelling, as well as their interactions, on the sessile invertebrate community and primary production of macroalgal communities in a warm-temperate system. Invertebrate cover remained consistently low at upwelling sites and was reduced at non-upwelling sites when grazers were excluded. Macroalgal cover was greater at upwelling sites when grazers were excluded and there was a strong effect of succession throughout the experimental period. Grazing pressure was greater at upwelling sites, particularly during winter months. There was a non-significant trend towards greater grazing pressure on early than later successional stages. Our results show that the positive impacts of bottom-up effects of nutrient supply on algal production do not overwhelm top-down control in this warm-temperate system. We speculate that global increases in air and sea-surface temperatures in warm-temperate systems will promote top-down effects in upwelling regions by increasing herbivore metabolic and growth rates.</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.