Find research datasets worth reusing

Controls on range shifts of coastal Californian bivalves during the peak of the last interglacial and baseline predictions for today

As the most recent time in Earth history when global temperatures were warmer than at present, the peak of the last interglacial (Marine Isotope Substage [MIS] 5e; ~120,000 years ago) can serve as a pre-anthropogenic baseline for a warmer near-future world. Here we use a new compilation of 22 fossil localities in California that have been reliably dated to Marine Isotope Stage (MIS) 5e to establish baseline expectations for contemporary bivalve species movements by identifying and analyzing bivalve species with "extralimital" ranges, i.e. species that occupied the California region during MIS 5e but are now restricted to adjacent regions. We find that 15% of species (n = 142) found in MIS 5e localities have extralimital ranges and currently occupy warmer waters to the south of the California region. The majority of extralimital occurrences occur in paleo-embayments, suggesting that these sheltered habitats were more suitable habitats for warm-water species than exposed coasts during the MIS 5e. We further find that extralimital species now tend to occur in cooler, more seasonally productive coastal waters and to occupy more offshore islands when compared to the broader species pool immediately south of California. These findings suggest that high dispersal potential and pre-existing tolerances to environmental conditions similar to California's comparatively cool and seasonally productive environments may have enabled extralimital bivalves to colonize the California region during MIS 5e.

Dataset and scripts from: Predicting temperature mortality and selection in natural Drosophila populations

The study develops and validates a theoretical model to predict thermal mortality under natural conditions, based on measurements of mortality performed in the laboratory at multiple constant temperatures. The theoretical model first fits a thermal tolerance landscape, which describes how survival probability is affected by both temperature and exposure time, to the empirical measurements of mortality obtained in the laboratory under controlled conditions. Then, employing a numerical approximation to the analytical solution based on differential calculus, it combines this tolerance landscape with ambient temperature records in natural settings to predict the survival probability curve under these thermal conditions. These predictions were validated by contrasting predicted and observed mortality curves in 11 Drosophila species under three different warming rates, reported in the literature, which were virtually indistinguishable. Having validated the model, the study then examines how mortality should be affected by climate change in a natural population of Drosophila subobscura from Santiago, Chile, employing temperature records for this location during 1984 - 1991 and 2014 - 2018. The cumulative mortality predicted from temperature records closely resemble the periods of population collapse recorded for this population during the Austral summer and, according to the model, warming temperatures in the past 30 years may have advanced this period by almost a month. This methodology is highly general and can in principle be employed to predict temperature mortality in small ectotherms under any varying thermal regime.

opencc-by-4.0Aug 2020View details →

Multiple systems in macaques for tracking prediction errors and other types of surprise

Data and code to reproduce the figures and major analyses in Grohn J, Schüffelgen U, Neubert F-X, Verhagen L, Sallet J, Kolling N, Rushworth MFS. Multiple systems in macaques for tracking prediction errors and other types of surprise. PLOS Biology. 2020.

opennotspecifiedOct 2019View details →

FIGURE 4 in Predicting the potential distribution of Rhaphidophorinae (Orthoptera, Rhaphidophoridae) in China

FIGURE 4. The jackknife test of individual environmental variable importance in the development of MAXENT model relative of all environmental variables

opencc-by-4.0Oct 2021View details →

Relabeling metabolic pathway data with groups to improve prediction outcomes

We include samples of various data types used in the work "Relabeling metabolic pathway data with groups to improve prediction outcomes" More information about the software package and instructions are provided in <a href="https://github.com/hallamlab/reMap">hallamlab/reMap</a>

Invertebrate community structure predicts natural pest control resilience to insecticide exposure

Biological pest control has become one of the central principles of ecological intensification in agriculture. However, invertebrate natural enemies within agricultural ecosystems are exposed to a myriad of different pesticides at both lethal and sub-lethal doses, that may limit their capacity to carry out pest control. An important question is how underlying diversity in invertebrate predator species, linked to their unique susceptibility to insecticides, can act to increase the resilience of natural pest control. We explore this issue by assessing the effects of sub-lethal insecticide exposure on the predation rates of 12 generalist predators feeding on the aphid Sitobion avenae (Aphididae). Predation rates within a 24 hr period were assessed (predation assessment) for each species after receiving one of the following treatments: 1) no prior deltamethrin exposure before the predation assessment (control); 2) deltamethrin exposure immediately before the predation assessment (resistance); and 3) deltamethrin exposure five days before the predation assessment (recovery). Extrapolating from these species-specific measures of resistance and recovery, we predicted the resilience of community level predation to insecticide exposure for predator communities associated with 256 arable fields in the UK. There was large variation in sub-lethal effects of the insecticide between even closely related species. This ranged from species showing no change in predation rates following sub-lethal insecticide exposure (high resistance), species showing only immediate depressed feeding rates after 24 hrs (high recovery), or those with depressed feeding rates after five days (low resistance and recovery). The community level analysis showed that resistance and recovery of natural pest control was predicted by both community phylogenetic diversity (positively) and weighted mean body mass (negatively). However, the removal of numerically dominant species from the analysis modified these effects. Synthesis and applications. Our results highlight the role of community diversity in maintaining the resilience of natural pest control following insecticide use. Importantly, less diverse assemblages dominated by predator species that show low resilience to insecticide exposure, may show a greater depression in pest control than diverse assemblages under insecticide based farmland management.

Analytic dataset informing prediction of subterranean cave and mine ambient temperatures

Caves and other subterranean features provide unique environments for many species. The importance of cave microclimate is particularly relevant at temperate latitudes where bats make seasonal use of caves for hibernation. White-nose syndrome (WNS), a fungal disease that has devastated populations of hibernating bats across eastern and central North America, has brought renewed interest in bat hibernation and hibernaculum conditions. A recent review synthesized current understanding of cave climatology, exploring the qualitative relationship between cave and surface climate with implications for hibernaculum suitability. However, a more quantitative understanding of the conditions in which bats hibernate and how they may promote or mediate WNS impacts is required. We compiled subterranean temperatures from caves and mines across the western United States and Canada to: a) quantify the hypothesized relationship between mean annual surface temperature (MAST) and subterranean temperature and how it is influenced by measurable site attributes, and b) use readily available gridded data to predict and continuously map the range of temperatures that may be available in caves and mines. Our analysis supports qualitative predictions that subterranean winter temperatures are correlated with MAST, that temperatures are warmer and less variable farther from the surface, and that even deep within caves temperatures tend to be lower than MAST. Effects of other site attributes (e.g., topography, vegetation, precipitation) on subterranean temperatures were not detected. We then assessed the plausibility of model-predicted temperatures using knowledge of winter bat distributions and preferred hibernaculum temperatures. Our model unavoidably simplifies complex subterranean environments, and is not intended to explain all variability in subterranean temperatures. Rather, our results offer researchers and managers improved broad-scale estimates of the geographic distribution of potential hibernaculum conditions compared to reliance on MAST alone. We expect this information to better support range-scale estimation of winter bat distributions and projection of likely WNS impacts across the West. We suggest that our model predictions should serve as hypotheses to be further tested and refined as additional data become available.

opencc-by-4.0Aug 2020View details →

Cantemist Silver Standard: Participant predictions in SEPLN IberLEF2020 - Spanish oncology clinical cases coded in ICD-O

Introduction Predictions in the background set of Cantemist participants.   Zip structure One directory per Cantemist subtask. Within each Cantemist subtask directory, there is one directory per team that contains the prediction runs.   Format The text documents are distributed in plain text files, UTF-8 encoding. The CodiEsp Silver Standard annotations have the following format: For the sub-tracks Cantemist-NER and Cantemist-Norm, the files are in Brat format. For the sub-track Cantemist-Coding files have the following fields: <pre>articleID ICDO-code </pre>   Resources: <ul> <li><a href="https://temu.bsc.es/cantemist/">Web</a></li> <li>Citation: Miranda-Escalada, A., Farré, E., & Krallinger, M. (2020). Named entity recognition, concept normalization and clinical coding: Overview of the cantemist track for cancer text mining in spanish, corpus, guidelines, methods and results. In Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2020), CEUR Workshop Proceedings.</li> <li><a href="https://doi.org/10.5281/zenodo.3773228">Gold Standard corpus</a></li> <li><a href="https://doi.org/10.5281/zenodo.3878178">Annotation guidelines</a></li> <li><a href="https://www.youtube.com/playlist?list=PL5uSCzf1azhC24g5dsp5eVMp8BZFWCraX">YouTube presentations</a></li> <li><a href="https://temu.bsc.es/cantemist/?p=4606">Participant codes</a></li> </ul>   All credit to Cantemist participants.    For more information, visit the track webpage: <a href="http://temu.bsc.es/cantemist/">http://temu.bsc.es/cantemist/</a> or email us at encargo-pln-life@bsc.es

Adjacency matrices and nodal attributes for prestige and homophily predict network structure for social learning of medicinal plant knowledge

Human subsistence societies have thrived in environmental extremes while maintaining biodiversity through social learning of ecological knowledge, such as techniques to prepare food and medicine from local resources. However, there is limited understanding of which processes shape social learning patterns and configuration in ecological knowledge networks, or how these processes apply to resource management and biological conservation. In this study, we test the hypothesis that the prestige (rarity or exclusivity) of knowledge shapes social learning networks. In addition, we test whether people tend to select who to learn from based on prestige (knowledge or reputation), and homophily (e.g., people of the same age or gender). We used interviews to assess five types of medicinal plant knowledge and how 303 people share this knowledge across four villages in Solomon Islands. We developed exponential random graph models (ERGMs) to test whether hypothesized patterns of knowledge sharing based on prestige and homophily are more common in the observed network than in randomly simulated networks of the same size. We found that prestige predicts five hypothesized network configurations and all three hypothesized learning patterns, while homophily predicts one of three hypothesized network configurations and five of the seven hypothesized learning patterns. These results compare the strength of different prestige and homophily effects on social learning and show how cultural practices such as intermarriage can affect certain aspects of prestige and homophily. By advancing our understanding of how prestige and homophily affect ecological knowledge networks, we identify which social learning patterns have the largest effects on biocultural conservation of ecological knowledge.

opencc-by-4.0Aug 2020View details →

Data from: Monitoring and predictive mapping of floristic biodiversity along a climatic gradient in ENSO's terrestrial core region, NW Peru

This is the data from the publication "Monitoring and predictive mapping of floristic biodiversity along a climatic gradient in ENSO's terrestrial core region, NW Peru" (<a href="http://onlinelibrary.wiley.com/doi/10.1111/ecog.05091/abstract">http://onlinelibrary.wiley.com/doi/10.1111/ecog.05091/abstract</a>). The code (including figures, appendices and the manuscript) can be found directly in the <a href="https://github.com/jannes-m/2020-enso-tdf">GitHub repository</a>. Data sources and description Column descriptions for all tables can be found in variable_description.ods. Following tables are stored in tables.gpkg: <ol> <li>plot_species_matrix_2011: Plot species matrix recorded in 2011</li> <li>plot_species_matrix_2012: Plot species matrix recorded in 2012.</li> <li>plot_species_matrix_2016: Plot species matrix recorded in 2016.</li> <li>plot_species_matrix_2017: Plot species matrix recorded in 2017.</li> <li>lifeform: Lifeforms of the recorded species</li> <li>plot_variables: Variables specific to the plots such as height of the first tree layer, cover of dead wood, etc.</li> <li>soil: Edaphic variables.</li> <li>topography: Topographic variables.</li> <li>streets: Streets and dirt tracks in the study area.</li> <li>towns: Polygons displaying the outline of the cities Paita, Piura and Chulucanas.</li> <li>rivers: Lines displaying the major rivers in the study area.</li> <li>study_area: Outline of the study area.</li> <li>peru: Outline of Peru.</li> <li>neighbors: Outline of Peru's neighbors (Bolivia, Brazil, Chile, Colombia, Ecuador).</li> <li>coast: Coastal strip of and close to the study area.</li> <li>precipitation: Precipitation measured at the three climatic stations (Paita, Piura, Chulucanas).</li> <li>experiment_count: species counted per visit (irrigation-fertilization experiment).</li> <li>experiment_irrigation: Rain input by time during the irrigation-fertilization experiment.</li> <li>experiment_cover: Cover of each plant species per visit and per experimental plot (irrigation-fertilization experiment).</li> </ol>

Data from: Mite load predicts the quality of sexual color and locomotor performance in a sexually dichromatic lizard

Since Darwin, the maintenance of bright sexual colors has recurrently been linked to mate preference. However, the mechanisms underpinning such preferences for bright colors would not be resolved for another century. Likely, the idea of selection for colors that could decrease the chances of survival (e.g. flashy colors that can inadvertently attract predators) was perceived as counterintuitive. It is now widely-accepted that these extreme colors often communicate to mates the ability to survive despite a 'handicap' and act as honest signals of individual quality when they are correlated with the quality of other traits that are directly linked to individual fitness. Sexual colors in males are frequently perceived as indicators of infection resistance, in particular. Still, there remains considerable discord among studies attempting to parse the relationships between the variables associating sexual color and infection resistance, such as habitat type and body size. This discord may arise from complex interactions between these variables. Here, we ask if sexual color in male Florida scrub lizards (Sceloporus woodi) is an honest signal of resistance to chigger mite infection. To this end, we use linear modeling to explore relationships between mite load, different components of sexual color, ecological performance, body size, and habitat type. Our data show that that the brightness of sexual color in scrub lizards is negatively associated with the interaction between mite load and body size, and scrub lizards suffer decreased endurance capacity with increases in mite load. Our data also indicate that mite load, performance, and sexual color in male scrub lizards can vary between habitat types. Collectively these results suggest that sexual color in scrub lizards is an honest indicator of individual quality and further underscore the importance of considering multiple factors when testing hypotheses related to the maintenance of sexual color.

Efficient weighting methods for genomic best linear unbiased prediction (BLUP) adaption to the genetic architectures of quantitative traits

<a name="_Hlk19877414"></a>Genomic best linear unbiased prediction (GBLUP) assumes equal variance for all marker effects, which is suitable for traits that conform to the infinitesimal model. For traits controlled by major genes, Bayesian methods with shrinkage priors or genome-wide association study (GWAS) methods can be used to identify <a name="_Hlk24974556">causal variants</a> effectively. The information from Bayesian/GWAS methods can be used to construct the weighted genomic relationship matrix (G). However, it remains unclear which methods perform best for traits varying in genetic architecture. Therefore, we developed several methods to <a name="_Hlk23592218">optimize</a> the performance of weighted GBLUP and compare them with other available methods using simulated and real datasets. First, two types of methods (marker effects with local-shrinkage or normal prior) were used to obtain test statistics and estimates for each marker effect. Second, three weighted G matrices were constructed based on the marker information from the first step: (1) the genomic-feature weighted G (GFWG), (2) the estimated marker-variance weighted G (EVWG), and (3) the absolute value of estimated marker-effect weighted G (AEWG). Following the above process, six different weighted GBLUP methods (local-shrinkage/normal prior GF/EV/AE-WGBLUP) were proposed for genomic prediction. Analyses with both simulated and real data demonstrated that these options offer flexibility for optimizing the weighted GBLUP for traits with a broad spectrum of genetic architectures. The advantage of weighting methods over GBLUP in terms of accuracy were trait dependent, ranging from 14.8% to marginal for simulated traits and from 44% to marginal for real traits. Local-shrinkage prior EVWGBLUP is superior for traits mainly controlled by loci of large effect. Normal prior AEWGBLUP performs well for traits mainly controlled by loci of moderate effect. For traits controlled by some loci with large effects (<a name="_Hlk49869847">explain 25%~50% genetic variance</a>) and a range of loci with small effects, GFWGBLUP has advantages. In conclusion, the optimal weighted GBLUP method for genomic selection should take both the genetic architecture and number of QTLs of traits into consideration carefully.

opencc-by-4.0Jul 2020View details →

Multi-label Pathway Prediction based on Active Dataset Subsampling

We include samples of various data types used in the work "Multi-label Pathway Prediction based on Active Dataset Subsampling" (under-review) More information about the software package and instructions are provided in <a href="https://github.com/hallamlab/leADS">hallamlab/leADS</a>

Predicting patch occupancy reveals the complexity of host range expansion

Specialized plant-insect interactions are a defining feature of life on earth, yet we are only beginning to understand the factors that set limits on host ranges in herbivorous insects. To better understand the recent adoption of alfalfa as a host plant by the Melissa blue butterfly, we quantified arthropod assemblages and plant metabolites across a wide geographic region, while controlling for climate and dispersal inferred from population genomic variation. The presence of the butterfly is successfully predicted by direct and indirect effects of plant traits and interactions with other species. Results are consistent with the predictions of a theoretical model of parasite host range in which specialization is an epiphenomenon of the many barriers to be overcome rather than a consequence of trade-offs in developmental physiology.

opencc-by-4.0Sep 2019View details →

MOLI: multi-omics late integration with deep neural networks for drug response prediction

Harmonized data used in "MOLI: multi-omics late integration with deep neural networks for drug response prediction", 2019, Bioinformatics <a href="https://academic.oup.com/bioinformatics/article/35/14/i501/5529255">https://academic.oup.com/bioinformatics/article/35/14/i501/5529255</a>.  CNA.tar.gz contains CNA profiles with non-integer estimates of copy number, e.g. log-ratios. Please use binarized CNA profiles (CNA_binary.tar.gz) to replicate the results described in the paper.  All raw data were obtained from open sources: - https://www.cancerrxgene.org/ - ArrayExpress https://www.ebi.ac.uk/arrayexpress/ - Firehose Broad GDAC http://gdac.broadinstitute.org/runs/stddata__2016_01_28/data/ - Supplementary of Gao et al., 2015 https://www.nature.com/articles/nm.3954 Gene symbols were mapped to Entrez Gene IDs. Data preprocessing is described in detail in supplementary materials. The code is available at <a href="https://github.com/hosseinshn/MOLI/tree/master/preprocessing_scr">https://github.com/hosseinshn/MOLI/tree/master/preprocessing_scr</a>.

opencc-by-4.0Sep 2020View details →

Data from Koch et al. 2020 Evolution: Genetic variance in fitness and its cross-sex covariance predict adaptation during experimental evolution.

Abstract In presence of rapid environmental changes, it is of particular importance to assess the adaptive potential of populations, which is mostly determined by the additive genetic variation (VA) in fitness. In this study we used Tribolium castaneum (red flour beetles) to investigate its adaptive potential in three new environmental conditions (Dry, Hot, Hot-Dry). We tested for potential constraints that might limit adaptation, including negative genetic covariance between female and male fitness.  Based on VA estimates for fitness, we expected the highest relative fitness increase in the most stressful condition Hot-Dry and similar increases in single stress conditions Dry and Hot. High adaptive potential in females in Hot was reduced by a negative covariance with male fitness. We tested adaptation to the three conditions after 20 generations of experimental evolution and found that observed adaptation mainly matched our predictions. Given that body size is commonly used as a proxy for fitness, we also tested how this trait and its genetic variance (including non-additive genetic variance) were impacted by environmental stress. In both traits, variances were sex and condition dependent, but they differed in their variance composition, cross-sex and cross-environment genetic covariances, as well as in the environmental impact on VA.   Method Strain and environmental conditions We used the Tribolium castaneum Cro1 strain collected from a wild population in 2010 and adapted to lab standard conditions (33°C, 70% relative humidity) for more than 20 generations. Beetles were kept in 24h darkness on organic wheat flour mixed with 10% organic baker's yeast. We sterilized flour and yeast by heating them for 12h at 80°C before use. To test for adaptation to new environmental conditions we used replicate lines and exposed them to three treatments and Control conditions. The conditions in the treatments were: Dry: 33°C and 30% relative humidity; Hot: 37°C and 70% r. h.; Hot-Dry: 37°C and 30% r. h.   Crossing, fitness assay and measurement of body size In order to be able to estimate genetic variances, we applied a split-brood paternal half-sib breeding design.  We produced 147 half-sib families by mating virgin males to three virgin females. Half- as well as full-sib families were split across all conditions. Male and female offspring (four females and two males per full-sib family and condition) were separated at the pupal stage and transferred to 10 mL tubes with 1 g of medium and remained there until they were used for the fitness assay eight weeks later. To estimate fitness, we mated each virgin male with two unrelated virgin females from the same condition in 15mL tube with 1g medium. The male was removed after 24h and females transferred into two separate tubes. Females were removed from the tubes after one week of egg laying, and 9g medium was added to provide food for the developing offspring. After five weeks the number of adult offspring was counted. While we conducted the matings for the fitness assay, we followed a specific crossing design and always crossed two pairs of full-sib families. Individuals resulting from these crosses (the F2 genaration) were double first cousins. Body size was measured in the F2, i.e. in the offspring of beetles that were used for the fitness assay. To estimate body size, we used the centroid size of the abdominal segment IV as proxy for total size since it can be measured more accurately than dry weight in very small insects and shows a high correlation with body mass.   Experimental evolution We used ten replicate lines per condition originating from the same ancestral population (Cro1) and let them adapt for 20 generations. Each new generation was set up by randomly selecting 120 pupae and placing them into a new vial with 70g medium. One selection line in Dry became extinct. Adult beetles of generation 20 from all selection lines were transferred to control conditions, in which they stayed for one week to mate and lay eggs. After removal of the adults, we waited until their offspring had reached the pupal stage and separated males and females. These individuals (generation 21) developed completely in control conditions. When they had reached the adult stage, each virgin male was mated with a virgin female of the same selection line and their offspring was transferred to all four conditions in the egg stage, resulting in full-sib families split across all conditions . As soon as these offspring (generation 22) had reached the pupal stage, males and females were separated. To compare fitness of different selection lines and test for adaptation, a virgin male and a virgin female of the same selection line in the same condition, but from different families were mated and the number of adult offspring produced within four days of mating and egg laying was used as a fitness estimate.     Files This data publication contains the following files: Fitness_data.txt: Fitness data (offspring number) of the first generation in new environmental conditions. ANIMAL: ID of female individuals; male: ID of mating partner, father of the offspring; fitness: number of adult offspring per female produced within one week of egg laying; condition: condition under which the individuals grew up, mated, reproduced (CTL: control, D: dry, H: hot, HD: hot-dry, see Methods for details); MOTHER: mother of the female; Batch: samples where fitness assay was started on the same day   Size_data.txt: Centroid size of abdominal segment IV. ANIMAL: ID of measured individuals; condition: condition under which the individuals grew up (CT: control, D: dry, H: hot, HD: hot-dry, see Methods for details); sex: sex of individuals (f: female, m: male); AS: centroid size [Pixel] of abdominal segment IV; Mother: ID of their mother; batch: Batches represent individuals that grew up at the same time, and thus accounts for variations in the medium or lab temperature   Pedigree.txt: Pedigree of measured individuals. ANIMAL: individual ID ; MOTHER: mother ID; FATHER: father ID   Transplant_data.txt: Offspring number of different selection lines under different conditions after 20 generations of experimental evolution. Line: Selection-line ID; Selection: condition, in which the selection-line spent 20 generations (CT: Control; D: Dry; Hot; HD: Hot-Dry); Fam: each selection line consisted of several families; Treatment: condition, in which offspring number was measured; offspring: number of adult offspring that a female produced within four days of egg-laying

Data from: Light availability predicts mortality probability of conifer saplings in Swiss mountain forests better than radial growth and tree size

Radial and height growth rates are suitable indicators of impending tree mortality risk of adult trees, but their applicability to saplings remains unknown. We compared radial growth of living and dead saplings of different heights and quantified the effects of light availability, growth and tree size on mortality. We sampled an equal number of living and dead saplings of four coniferous tree species (Pinus cembra, Larix decidua, Picea abies, Abies alba) in nine forests along an elevational gradient of the Swiss Alps. Based on tree-ring widths reconstructed from stem disks at multiple tree heights, we calculated radial growth rates. We observed a divergent pattern in radial growth of living and dead saplings, with reduced growth of dead saplings starting several years prior to death. By matching living and dead saplings of similar ages, we tested whether mortality probabilities of saplings were influenced by light availability, recent growth rates and diameter. Mortality of coniferous saplings in mountain forests was mainly influenced by light availability, with changing effects along the elevational gradient. Recent radial growth rate and tree size were only weakly associated with sapling mortality. Our study establishes the importance of long-term predisposing factors for the mortality probability of conifer saplings in mountain forests, thus extending well-established findings from the adult stage to saplings, which represent a critical stage of forest dynamics.

opencc-zeroOct 2020View details →

Using genomic prediction to detect microevolutionary change of a quantitative trait

Detecting microevolutionary responses to natural selection by observing temporal changes in individual breeding values is challenging. The collection of suitable datasets can take many years and disentangling the contributions of the environment and genetics to phenotypic change is not trivial. Furthermore, pedigree-based methods of obtaining individual breeding values have known biases. Here, we apply a genomic prediction approach to estimate breeding values of adult weight in a 35-year dataset of Soay sheep (Ovis aries). Comparisons are made with a traditional pedigree-based approach. During the study period adult body weight decreased, but the underlying genetic component of body weight increased, at a rate that is unlikely to be attributable to genetic drift. Thus cryptic microevolution of greater adult body weight has probably occurred. Genomic and pedigree-based approaches gave largely consistent results. Thus, using genomic prediction to study microevolution in wild populations can remove the requirement for pedigree data, potentially opening up new study systems for similar research.

opencc-zeroFeb 2020View details →

Data for: Maternal glucocorticoid levels during incubation predict breeding success, but not reproductive investment, in a free-ranging bird

The hormone corticosterone (CORT) has been hypothesized to be linked with fitness, but the directionality of the relationship is unclear. The "CORT-fitness hypothesis" proposes that high levels of CORT arise from challenging environmental conditions, resulting in lower reproductive success (a negative relationship). In contrast, the "CORT-adaptation hypothesis" suggests that, during energetically demanding periods, CORT will mediate physiological or behavioural changes that result in increased reproductive investment and success (a positive relationship). During two breeding seasons, we experimentally manipulated circulating CORT levels in female tree swallows (Tachycineta bicolor) prior to egg laying, and measured subsequent reproductive effort, breeding success, and maternal survival. When females were recaptured during egg incubation and again during the nestling stage, the CORT levels were similar among individuals in each treatment group, and maternal treatment had no effect on indices of fitness. By considering variation among females, we found support for the "CORT-adaptation hypothesis"; there was a significant positive relationship between CORT levels during incubation and hatching and fledging success. During the nestling stage CORT levels were unrelated to any measure of investment or success. Within the environmental context of our study, relationships between maternal glucocorticoid levels and indices fitness vary across reproductive stages.

Experimental evidence of warming-induced disease emergence and its prediction by a trait-based mechanistic model

Predicting the effects of seasonality and climate change on the emergence and spread of infectious disease remains difficult, in part because of poorly understood connections between warming and the mechanisms driving disease. Trait-based mechanistic models combined with thermal performance curves arising from the Metabolic Theory of Ecology (MTE) have been highlighted as a promising approach going forward; however, this framework has not been tested under controlled experimental conditions that isolate the role of gradual temporal warming on disease dynamics and emergence. Here, we provide experimental evidence that a slowly warming host – parasite system can be pushed through a critical transition into an epidemic state. We then show that a trait-based mechanistic model with MTE functional forms can predict the critical temperature for disease emergence, subsequent disease dynamics through time, and final infection prevalence in an experimentally warmed system of Daphnia and a microsporidian parasite. Our results serve as a proof of principle that trait-based mechanistic models using MTE sub-functions can predict warming-induced disease emergence in data-rich systems – a critical step towards generalizing the approach to other systems.