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27 results for “competition for water”
GECCO Industrial Challenge 2017 Dataset: A water quality dataset for the 'Monitoring of drinking-water quality' competition at the Genetic and Evolutionary Computation Conference 2017, Berlin, Germany.
<p>Dataset of the 'Industrial Challenge: Monitoring of drinking-water quality' competition hosted at The Genetic and Evolutionary Computation Conference (GECCO) July 15th-19th 2017, Berlin, Germany</p> <p> </p> <p>The task of the competition was to develop an anomaly detection algorithm for a water- and environmental data set.</p> <p> </p> <p>Included in zenodo: </p> <p>- dataset of water quality data</p> <p>- additional material and descriptions provided for the competition</p> <p> </p> <p>The competition was organized by:</p> <p>M. Friese, J. Stork, A. Fischbach, M. Rebolledo, T. Bartz-Beielstein (TH Köln)</p> <p> </p> <p>The dataset was provided and prepared by:</p> <p>Thüringer Fernwasserversorgung,</p> <p>IMProvT research project (S. Moritz)</p> <p><br> </p> <p>Industrial Challenge: Monitoring of drinking-water quality</p> <p> </p> <p>Description:</p> <p>Water covers 71% of the Earth's surface and is vital to all known forms of life. The provision of safe and clean drinking water to protect public health is a natural aim. Performing regular monitoring of the water-quality is essential to achieve this aim.</p> <p>Goal of the GECCO 2017 Industrial Challenge is to analyze drinking-water data and to develop a highly efficient algorithm that most accurately recognizes diverse kinds of changes in the quality of our drinking-water.</p> <p> </p> <p>Submission deadline:</p> <p>June 30, 2017</p> <p>Official webpage:</p> <p><a href="http://www.spotseven.de/gecco-challenge/gecco-challenge-2017/">http://www.spotseven.de/gecco-challenge/gecco-challenge-2017/</a></p>
GECCO Industrial Challenge 2019 Dataset: A water quality dataset for the 'Internet of Things: Online Event Detection for Drinking Water Quality Control' competition at the Genetic and Evolutionary Computation Conference 2019, Prague, Czech Republic.
<p>Dataset of the 'Internet of Things: Online Event Detection for Drinking Water Quality Control' competition hosted at The Genetic and Evolutionary Computation Conference (GECCO) July 13th-17th 2019, Prague, Czech Republic</p> <p> </p> <p>The task of the competition was to develop an anomaly detection algorithm for a water- and environmental data set.</p> <p> </p> <p>Included in zenodo: </p> <p>1. Original train dataset of water quality data provided to participants (identical to gecco2019_train_water_quality.csv)</p> <p>2. Call for Participation</p> <p>3. Rules and Description of the Challenge</p> <p>4. Resource Package provided to participants</p> <p>5. The complete dataset, consisting of train, test and validation merged together (gecco2019_all_water_quality.csv)</p> <p>6. The test dataset, which was used for creating the leaderboard on the server (gecco2019_test_water_quality.csv)</p> <p>7. The train dataset, which participants had available for training their models (gecco2019_train_water_quality.csv)</p> <p>8. The validation dataset, which was used for the end results for the challenge (gecco2019_valid_water_quality.csv)</p> <p> </p> <p>The challenge required the participants to submit a program for event detection. A training dataset was available to the participants (gecco2019_train_water_quality.csv). During the challenge the participants were able to upload a version of their program to out online platform, where this version was scored against the testing dataset (gecco2019_test_water_quality.csv), thus an intermediate leaderboard was available. To avoid overfitting against this dataset, at the end of the challenge, the end result was created from scoring with the validation dataset (gecco2019_valid_water_quality.csv). </p> <p>Train, Test, Validation dataset are from the same measuring station and are in chronological order. So the timestamps from the test dataset begin directly after the train timestamps, while the validation timestamps begin directly after the test timestamps. </p> <p> </p> <p>The competition was organized by:</p> <p>F. Rehbach, S. Moritz, T. Bartz-Beielstein (TH Köln)</p> <p> </p> <p>The dataset was provided by:</p> <p>Thüringer Fernwasserversorgung and IMProvT research project</p> <p> </p> <p> </p> <p>Internet of Things: Online Event Detection for Drinking Water Quality Control</p> <p> </p> <p>Description:</p> <p>For the 8th time in GECCO history, the SPOTSeven Lab is hosting an industrial challenge in cooperation with various industry partners. This years challenge, based on the 2018 challenge, is held in cooperation with "Thüringer Fernwasserversorgung" which provides their real-world data set. The task of this years competition is to develop an anomaly detection algorithm for the water- and environmental data set. Early identification of anomalies in water quality data is a challenging task. It is important to identify true undesirable variations in the water quality. At the same time, false alarm rates have to be very low.</p> <p><br> Competition Opens: End of January/Start of February 2019<br> Final Submission: 30 June 2019</p> <p>Official webpage:</p> <p><a href="https://www.th-koeln.de/informatik-und-ingenieurwissenschaften/gecco-challenge-2019_63244.php">https://www.th-koeln.de/informatik-und-ingenieurwissenschaften/gecco-challenge-2019_63244.php</a></p> <p> </p>
Male sexual signaling and expected effects of hatchery-induced sperm competition vary with water depth at which whitefish are caught
<div> <div> <div> <div> <p>Salmonids like whitefish (<em>Coregonus</em> spp.) are often propagated in supportive breeding. Spawners are caught from their spawning locations, their gametes mixed, and the resulting offspring reared in a protected environment before being released into the wild. This procedure can affect sexual selection, for example, by enhancing the importance of sperm competition or by reducing the relevance of sexual signals. While it is often unclear how sperm competitiveness is affected by a male's overall genetic quality, there is accumulating evidence that sexual signals reveal good genes and that mate choice based on such signals can increase offspring viability (Auld et al. 2019). Therefore, supportive breeding may affect the genetic variance and the mean genetic quality of next generations. We sampled whitefish from various locations along a depth gradient to test how male characteristics that are likely to affect sexual selection under natural conditions correlate with characteristics that affect hatchery-induced sperm competition. Whitefish are external fertilizers, and multi-male spawning and hence sperm competition is common under natural conditions. Mate choice is not sufficiently understood but could be based on breeding tubercles. These are small conical structures that grow on scales before the breeding sea- son and fall off shortly afterwards. The size of breeding tubercles varies much among males and has repeatedly been found to correlate positively with offspring viability (Wedekind et al. 2001; Keka ̈la ̈inen et al. 2010). Male dominance is typically depend- ent on body size (Auld et al. 2019) and could also be relevant in whitefish. Body size itself can reflect individual inbreeding coefficients (Su et al. 1996) and be an indicator of heritable genetic quality in small or structured populations (Neff and Pitcher 2008). In another fish with a somewhat comparable mating system, the size of breeding tubercles and male size was not correlated but could both be used to predict male reproductive success under close to natural conditions (Jacob et al. 2009). We study whitefish from Lake Hallwil (Switzerland). This lake has suffered so much from anthropogenic eutrophication that it is being artificially aerated since 1985. Three hatcheries around the lake are likely to have played a key role in maintaining the whitefish population, as concluded also from a recent mark–recapture experiment (Vonlanthen 2015). However, eutrophication combined with possible hybridization in hatcheries can have led to a speciation reversal (Vonlanthen et al. 2012) and may thereby have destroyed any genetic structure linked to water depth. Hatchery protocols now focus on maintaining over-all genetic variance by pooling milt of many males before adding the mix to eggs of multiple females. Milt volume varies among sires, for example, because males often lose milt when being pulled up from deep locations (Figure 1), an effect that likely depends on how much the swim bladder is inflated by the change in pressure. This variance in milt volume is likely to affect the genetic variance that, in combination with the average genetic quality, may then affect the long-term survival of a population. The extent to which hatchery protocols affect genetic quality can be estimated by the correlations between male quality indicators and traits that affect hatchery-induced sperm competition, that is, sperm number, velocity, and longevity (summarized here as "milt potency," see also Supplementary Material). Many breeding protocols are likely to promote genetic quality if male attractiveness or dominance are positively correlated to milt potency. If there are no such correlations or negative ones because of life-history trade-offs, hatchery-induced sperm competition is likely to reduce the average genetic quality in future generations. We sampled fish from various depths and determined their age, size, breeding ornamentation, and milt potency (see methods in the Supplementary Material) to test whether and how different male characteristics affect reproductive success in supportive breeding in a heavily managed population.</p> </div> </div> </div> </div>
Male sexual signaling and expected effects of hatchery-induced sperm competition vary with water depth at which whitefish are caught
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Data from: Plant water use affects competition for nitrogen: why drought favors invasive species in California
Classic resource competition theory typically treats resource supply rates as independent; however, nutrient supplies can be affected by plants indirectly, with important consequences for model predictions. We demonstrate this general phenomenon by using a model in which competition for nitrogen is mediated by soil moisture, with competitive outcomes including coexistence and multiple stable states as well as competitive exclusion. In the model, soil moisture regulates nitrogen availability through soil moisture dependence of microbial processes, leaching, and plant uptake. By affecting water availability, plants also indirectly affect nitrogen availability and may therefore alter the competitive outcome. Exotic annual species from the Mediterranean have displaced much of the native perennial grasses in California. Nitrogen and water have been shown to be potentially limiting in this system. We parameterize the model for a Californian grassland and show that soil moisture–mediated competition for nitrogen can explain the annual species' dominance in drier areas, with coexistence expected in wetter regions. These results are concordant with larger biogeographic patterns of grassland invasion in the Pacific states of the United States, in which annual grasses have invaded most of the hot, dry grasslands in California but perennial grasses dominate the moister prairies of northern California, Oregon, and Washington.
Competition for waterborne food resources among tropical shallow-water sponges
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Data from: Plant water use affects competition for nitrogen: why drought favors invasive species in California
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Data from: Disentangling the effect of competition, CO2 and climate on intrinsic water-use efficiency and tree growth
1. Climate change scenarios forecast rising temperatures for the Mediterranean region, which could enhance vulnerability to drought stress in forest ecosystems. The long-term effects of climate forcing on tree performance can be, however, modulated by other environmental factors, such as competition and rising atmospheric CO2 concentrations. 2. We assessed the concomitant effect of competition, climate and CO2 concentrations on the tree-ring δ13C-derived intrinsic water-use efficiency (iWUE) and basal area increments (BAI) of species with different drought tolerance: two Mediterranean deciduous species (Quercus faginea Lam. and Quercus pyrenaica Willd.) and one conifer (Pinus sylvestris L.). Additionally, given that competition may be managed to mitigate the effect of increasing drought stress, we further examined the influence of this variable on iWUE and growth using data compiled from the literature, providing the first review on the response of iWUE to competition. 3. Competition had no significant effect on iWUE in any of the three species studied, whereas, as expected, growth rates were significantly higher under low competition levels. This was consistent with the literature review, which showed that shifts in iWUE with competition changes are rare; supporting the hypothesis that leaf-level gas exchange tends to be a homeostatic trait. In the long term, the three species exhibited a significant increasing trend in iWUE due to the combined effect of increased CO2 concentration, climate and age. Growth, however, was mostly affected by competition and climate and in most cases was not enhanced as a result of the increase in iWUE. 4. Synthesis. Regardless of their functional response to drought, trees respond to reduced competition through structural shifts such as increased radial growth rather than leaf-level gas exchange adjustments. CO2 and climate are, therefore, the main drivers of iWUE variability, rather than competition. Thus, if temperature-induced drought becomes limiting, reducing competition for resources may not offset the detrimental effect of increasing drought stress on tree physiology and growth decline may occur without a CO2 fertilization effect.
Data from: Parental environmental effects due to contrasting watering adapt competitive ability, but not drought tolerance, in offspring of a semi-arid annual Brassicaceae
1. Parental effects (PE) can be adaptive and improve offspring performance when parents and offspring experience similar environmental conditions. However, it is unknown whether adaptive PE exist also in habitats where such similarity is unlikely due to strong temporal variation. In particular, we do not know whether PE can adapt offspring to fluctuating levels of neighbour competition in such habitats. 2. Here, we tested for adaptive PE in terms of two key environmental factors in a semi-arid annual system, competition and drought. While rainfall was stochastic in the study site, the competitive environment was partly predictable: higher plant densities followed after favourable (rainy) years due to high seed production. We therefore expected PE to adapt the offspring's competitive ability to these (predictable) fluctuations in plant densities, rather than to adapt the offspring's drought tolerance to the (unpredictable) occurrence of intensified drought. 3. Parental plants of Biscutella didyma, an annual Brassicaceae, were raised under favourable watering and under drought conditions. Offspring performance was then tested under a full-factorial combination of two neighbour regimes and six watering levels in the glasshouse. 4. Offspring of parents grown under favourable conditions were stronger competitors. This was associated with a small shift in phenology but not with higher parental seed provisioning. Offspring from parents grown under drought showed no improved drought tolerance. Moreover, no PE were detectable when offspring were grown without neighbours. 5. Our results suggest a novel path of adaptive PE: higher competitive ability was induced in offspring that were more likely to experience high neighbour densities. Together with the lack of adaptive PE towards drought tolerance, this emphasizes that a correlation between parental and offspring environment is crucial for adaptive PE to evolve. Our results also call for the inclusion of competitive effects in future PE studies. 6. Synthesis. This study demonstrates the important role of adaptive PE for plant fitness (regarding competition) but also their limits (regarding drought) in temporally variable environments, based on the predictability of the respective environmental factor.
Data from: The shift from plant–plant facilitation to competition under severe water deficit is spatially explicit
The stress-gradient hypothesis predicts a higher frequency of facilitative interactions as resource limitation increases. Under severe resource limitation, it has been suggested that facilitation may revert to competition, and identifying the presence as well as determining the magnitude of this shift is important for predicting the effect of climate change on biodiversity and plant community dynamics. In this study, we perform a meta-analysis to compare temporal differences of species diversity and productivity under a nurse plant (Retama sphaerocarpa) with varying annual rainfall quantity to test the effect of water limitation on facilitation. Furthermore, we assess spatial differences in the herbaceous community under nurse plants in situ during a year with below-average rainfall. We found evidence that severe rainfall deficit reduced species diversity and plant productivity under nurse plants relative to open areas. Our results indicate that the switch from facilitation to competition in response to rainfall quantity is nonlinear. The magnitude of this switch depended on the aspect around the nurse plant. Hotter south aspects under nurse plants resulted in negative effects on beneficiary species, while the north aspect still showed facilitation. Combined, these results emphasize the importance of spatial heterogeneity under nurse plants for mediating species loss under reduced precipitation, as predicted by future climate change scenarios. However, the decreased water availability expected under climate change will likely reduce overall facilitation and limit the role of nurse plants as refugia, amplifying biodiversity loss.
Data from: Tree-to-tree competition in mixed European beech-Scots pine forests has different impacts on growth and water-use efficiency depending on site conditions
1. Mixed conifer-hardwood forests can be more productive than pure forests and they are increasingly considered as ecosystems that could provide adaptation strategies in the face of global change. However, the combined effects of tree-to-tree competition, rising atmospheric CO2 concentrations and climate on such mixtures remain poorly characterized and understood. 2. To fill this research gap, we reconstructed 34-year series (1980-2013) of growth (basal area increment, BAI) and intrinsic water-use efficiency (iWUE) of Scots pine (Pinus sylvestris L.) – European beech (Fagus sylvatica L.) mixed stands at two climatically contrasting sites located in the southwestern Pyrenees. We also gathered data on tree-to-tree competition and climate variables in order to test the hypotheses that (i) radial growth will be greater when inter-specific competition exceeds intra-specific competition, i.e. when species complementarity occurs, and (ii) enhanced iWUE could be linked to improved stem radial growth. 3. Growth of both species was reduced when intra-specific competition increased. Species complementarity was linked to improved growth of Scots pine at the continental site, whilst competition overrode any complementarity advantage at the drought-prone Mediterranean site. Beech growth did not show any significant response to pine admixture likely due to shade tolerance and the highly competitive nature of this species. Increasing inter-specific competition drove recent iWUE changes, which increased in Scots pine but decreased in European beech. The iWUE enhancement did not involve any growth improvement in Scots pine. However, the positive BAI-iWUE relationship found for beech suggests an enhanced beech growth in drought-prone sites due to improved water use. 4. Synthesis. Complementarity may enhance growth in mixed forests. However, water scarcity can constrict light-related complementarity for shade intolerant species (Scots pine) in drought-prone sites. BAI-iWUE relationships were negative for Scots pine and positive for European beech. These contrasting behaviours have got implications for coping with the expected increasing drought events in Scots pine-European beech mixtures located near the ecological limit of the two species. Complementarity effects between tree species should be considered to avoid overestimating the degree of future carbon uptake by mixed conifer-broadleaf forests.
Data related to: Global land-water competition and synergy between solar energy and agriculture
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Data from: Interspecific interference competition at the resource patch scale: do large herbivores spatially avoid elephants while accessing water?
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Data from: No influence of water limitation on the outcome of competition between diploid and tetraploid Chamerion angustifolium (Onagraceae)
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Data from: Parental environmental effects due to contrasting watering adapt competitive ability, but not drought tolerance, in offspring of a semi-arid annual Brassicaceae
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Data from: Tree-to-tree competition in mixed European beech-Scots pine forests has different impacts on growth and water-use efficiency depending on site conditions
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Data from: Disentangling the effect of competition, CO2 and climate on intrinsic water-use efficiency and tree growth
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Data from: The shift from plant–plant facilitation to competition under severe water deficit is spatially explicit
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GECCO Industrial Challenge 2018 Dataset: A water quality dataset for the 'Internet of Things: Online Anomaly Detection for Drinking Water Quality' competition at the Genetic and Evolutionary Computation Conference 2018, Kyoto, Japan.
<p>Dataset of the 'Internet of Things: Online Anomaly Detection for Drinking Water Quality' competition hosted at The Genetic and Evolutionary Computation Conference (GECCO) July 15th-19th 2018, Kyoto, Japan</p> <p> </p> <p>The task of the competition was to develop an anomaly detection algorithm for a water- and environmental data set.</p> <p> </p> <p>Included in zenodo: </p> <p>- dataset of water quality data</p> <p>- additional material and descriptions provided for the competition</p> <p> </p> <p>The competition was organized by:</p> <p>F. Rehbach, M. Rebolledo, S. Moritz, S. Chandrasekaran, T. Bartz-Beielstein (TH Köln)</p> <p> </p> <p>The dataset was provided by:</p> <p>Thüringer Fernwasserversorgung and IMProvT research project</p> <p> </p> <p>GECCO Industrial Challenge: 'Internet of Things: Online Anomaly Detection for Drinking Water Quality'</p> <p>Description:</p> <p>For the 7th time in GECCO history, the SPOTSeven Lab is hosting an industrial challenge in cooperation with various industry partners. This years challenge, based on the 2017 challenge, is held in cooperation with "Thüringer Fernwasserversorgung" which provides their real-world data set. The task of this years competition is to develop an anomaly detection algorithm for the water- and environmental data set. Early identification of anomalies in water quality data is a challenging task. It is important to identify true undesirable variations in the water quality. At the same time, false alarm rates have to be very low.<br> Additionally to the competition, for the first time in GECCO history we are now able to provide the opportunity for all participants to submit 2-page algorithm descriptions for the GECCO Companion. Thus, it is now possible to create publications in a similar procedure to the Late Breaking Abstracts (LBAs) directly through competition participation!</p> <p> </p> <p>Accepted Competition Entry Abstracts<br> - Online Anomaly Detection for Drinking Water Quality Using a Multi-objective Machine Learning Approach (Victor Henrique Alves Ribeiro and Gilberto Reynoso Meza from the Pontifical Catholic University of Parana)<br> - Anomaly Detection for Drinking Water Quality via Deep BiLSTM Ensemble (Xingguo Chen, Fan Feng, Jikai Wu, and Wenyu Liu from the Nanjing University of Posts and Telecommunications and Nanjing University)<br> - Automatic vs. Manual Feature Engineering for Anomaly Detection of Drinking-Water Quality (Valerie Aenne Nicola Fehst from idatase GmbH)</p> <p>Official webpage:</p> <p><a href="http://www.spotseven.de/gecco/gecco-challenge/gecco-challenge-2018/">http://www.spotseven.de/gecco/gecco-challenge/gecco-challenge-2018/</a></p>
Dataset associated to "Unraveling the relative role of light and water competition between lianas and trees in tropical forests: A vegetation model analysis"
<p>This dataset includes all the codes necessary to reproduce the simulations presented in the paper "Unraveling the relative role of light and water competition between lianas and trees in tropical forests: A vegetation model analysis" published in Journal of Ecology. More precisely, it includes the version of the codes used to generate the results for the vegetation model (ED2), the analysis platform (PEcAn), as well as the meterological drivers (Drivers) and the initial conditions (IC) of the model and the priors and posterior parameter distributions.</p>
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