Predation risk and the evolution of a vertebrate stress response: Parallel evolution of stress reactivity and sexual dimorphism

Predation risk is often invoked to explain variation in stress responses. Yet, the answers to several key questions remain elusive, including the following: (1) how predation risk influences the evolution of stress phenotypes, (2) the relative importance of environmental versus genetic factors in stress reactivity and (3) sexual dimorphism in stress physiology. To address these questions, we explored variation in stress reactivity (ventilation frequency) in a post-Pleistocene radiation of live-bearing fish, where Bahamas mosquitofish (Gambusia hubbsi) inhabit isolated blue holes that differ in predation risk. Individuals of populations coexisting with predators exhibited similar, relatively low stress reactivity as compared to low-predation populations. We suggest that this dampened stress reactivity has evolved to reduce energy expenditure in environments with frequent and intense stressors, such as piscivorous fish. Importantly, the magnitude of stress responses exhibited by fish from high-predation sites in the wild changed very little after two generations of laboratory rearing in the absence of predators. By comparison, low-predation populations exhibited greater among-population variation and larger changes subsequent to laboratory rearing. These low-predation populations appear to have evolved more dampened stress responses in blue holes with lower food availability. Moreover, females showed a lower ventilation frequency, and this sexual dimorphism was stronger in high-predation populations. This may reflect a greater premium placed on energy efficiency in live-bearing females, especially under high-predation risk where females show higher fecundities. Altogether, by demonstrating parallel adaptive divergence in stress reactivity, we highlight how energetic trade-offs may mould the evolution of the vertebrate stress response under varying predation risk and resource availability

When age makes all the difference : Methane production in sediment of contrasting Swedish lakes

Lakes are a significant source of the powerful greenhouse gas methane (CH4) globally. Methaneis produced through microbial processes in anoxic sediments. Methane emission from lakes ishighly variable in space and time. Consequently, is it difficult to predict the methane production rate and at present time it cannot be predicted from sediment characteristics. Therefore, methane production in the sediment of contrasting Swedish lakes was investigated, in order to find out if methane production rate can be related to sediment characteristics, and if a predictive model that recently was developed for Brazilian reservoirs is applicable to Swedish lakes. For this, sediment cores were collected from six lakes, differing in their sediment characteristics and geographical position as well as one river. The sediment cores were sliced into one centimetre thick layers. The different layers were incubated and methane production rate was measured. The sediment layers were also analysed for water content, median grain size, total nitrogen and carbon content as well as age. The influence of sediment age and C:N ratio as predictors for methane production were tested with a mixed linear model and a non-linear model. Both models showed that age had a significant effect on methane production rate (p < 0.001). The C:N ratio also had a statistically significant effect on methane production rate only shown with the non-linear model, however this effect was weak. Applying the recently published predictive model for methane production rate in Brazilian reservoir sediments to this data from the Swedish lakes, provided a good prediction of methane production rate in the nutrient-rich Swedish lakes, however it overestimated the methane production rate of the humic-rich boreal lakes and sediment older than 50 years. In summary, a model using age as predicting factor was developed fitting all the studied Swedish lakes. In addition, the predictive model developed in Brazilian reservoirs for the methane production rate was valid only for the studied nutrient-rich Swedish lakes and the studied oligotrophic Swedish lakes

When age makes all the difference : Methane production in sediment of contrasting Swedish lakes

Lakes are a significant source of the powerful greenhouse gas methane (CH4) globally. Methaneis produced through microbial processes in anoxic sediments. Methane emission from lakes ishighly variable in space and time. Consequently, is it difficult to predict the methane production rate and at present time it cannot be predicted from sediment characteristics. Therefore, methane production in the sediment of contrasting Swedish lakes was investigated, in order to find out if methane production rate can be related to sediment characteristics, and if a predictive model that recently was developed for Brazilian reservoirs is applicable to Swedish lakes. For this, sediment cores were collected from six lakes, differing in their sediment characteristics and geographical position as well as one river. The sediment cores were sliced into one centimetre thick layers. The different layers were incubated and methane production rate was measured. The sediment layers were also analysed for water content, median grain size, total nitrogen and carbon content as well as age. The influence of sediment age and C:N ratio as predictors for methane production were tested with a mixed linear model and a non-linear model. Both models showed that age had a significant effect on methane production rate (p < 0.001). The C:N ratio also had a statistically significant effect on methane production rate only shown with the non-linear model, however this effect was weak. Applying the recently published predictive model for methane production rate in Brazilian reservoir sediments to this data from the Swedish lakes, provided a good prediction of methane production rate in the nutrient-rich Swedish lakes, however it overestimated the methane production rate of the humic-rich boreal lakes and sediment older than 50 years. In summary, a model using age as predicting factor was developed fitting all the studied Swedish lakes. In addition, the predictive model developed in Brazilian reservoirs for the methane production rate was valid only for the studied nutrient-rich Swedish lakes and the studied oligotrophic Swedish lakes

Predicting Methane Formation Rates of Freshwater Sediments in Different Climates

<p>These datasets uploaded here contain:</p> <p>CH4 formation rates of sediment layers incubated from nine Swedish lakes (<a href="https://zenodo.org/api/files/39e74df0-e0c7-41a6-88c6-d37bcc1ffb49/CH4Formation_SwedishLakes.csv">CH4Formation_SwedishLakes.csv</a>),  their sediment characteristics measured in different layers and land use data</p> <p>CH4 formation rates retrieved from Isidorova et al. (2019,<a href="http://urn.kb.se/resolve?urn=urn%3Anbn%3Ase%3Auu%3Adiva-387547">urn:nbn:se:uu:diva-387547</a>). From this dataset we extracted only the maximum CH4 formation rates and are reported in the file <a href="https://zenodo.org/api/files/39e74df0-e0c7-41a6-88c6-d37bcc1ffb49/CH4Formation_BrazilianReservoirs.csv">CH4Formation_BrazilianReservoirs.csv</a></p> <p>CH4 formation rates used to calculate CH4 formation decay rate with age for Swedish lakes (<a href="https://zenodo.org/api/files/39e74df0-e0c7-41a6-88c6-d37bcc1ffb49/CH4Formation_SwedishLakes_forDecayRate.csv">CH4Formation_SwedishLakes_forDecayRate.csv</a>)</p> <p>Extraction of PLS analysis results <a href="https://zenodo.org/api/files/39e74df0-e0c7-41a6-88c6-d37bcc1ffb49/PLS_List.xlsx">PLS_List.xlsx</a></p&gt

Predicting Methane Formation Rates of Freshwater Sediments in Different Biogeographic Regions

These datasets uploaded here contain: CH4 formation rates of sediment layers incubated from nine Swedish lakes (CH4Formation_SwedishLakes.csv), their sediment characteristics measured in different layers and land use data CH4 formation rates retrieved from Isidorova et al. (2019,urn:nbn:se:uu:diva-387547). From this dataset we extracted only the maximum CH4 formation rates and are reported in the file CH4Formation_BrazilianReservoirs.csv CH4 formation rates used to calculate CH4 formation decay rate with age for Swedish lakes (CH4Formation_SwedishLakes_forDecayRate.csv) Supplementary information SupplementaryInfo.pdf related to CH4 formation rates and sediment age Extraction of PLS analysis results PLS_List.xls