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Background On-going global climate change poses a serious threat for natural populations unless they are able to evolutionarily adapt to changing environmental conditions (e.g. increasing average temperatures, occurrence of extreme weather events). A prerequisite for evolutionary change is within-population heritable genetic variation in traits subject to selection. In relation to climate change, mainly phenological traits as well as heat and desiccation resistance have been examined for such variation. Therefore, it is important to investigate adaptive potential under climate change conditions across a broader range of traits. This is especially true for life-history traits and defences against natural enemies (e.g. parasites) since they influence organisms’ fitness both directly and through species interactions. We examined the adaptive potential of fitness-related traits and their responses to heat waves in a population of a freshwater snail, Lymnaea stagnalis. We estimated family-level variation and covariation in life history (size, reproduction) and constitutive immune defence traits [haemocyte concentration, phenoloxidase (PO)-like activity, antibacterial activity of haemolymph] in snails experimentally exposed to typical (15 °C) and heat wave (25 °C) temperatures. We also assessed variation in the reaction norms of these traits between the treatments. Results We found that at the heat wave temperature, snails were larger and reproduced more, while their immune defence was reduced. Snails showed high family-level variation in all examined traits within both temperature treatments. The only negative genetic correlation (between reproduction and antibacterial activity) appeared at the high temperature. However, we found no family-level variation in the responses of most examined traits to the experimental heat wave (i.e. largely parallel reaction norms between the treatments). Only the reduction of PO-like activity when exposed to the high temperature showed family-level variation, suggesting that the cost of heat waves may be lower for some families and could evolve under selection. Conclusion Our results suggest that there is genetic potential for adaptation within both thermal environments and that trait evolution may not be strongly affected by trade-offs between them. However, rare differences in thermal reaction norms across families indicate limited evolutionary potential in the responses of snails to changing temperatures during extreme weather events. BMC Evolutionary Biology, 17 ISSN:1471-2148

# Bird\_breeding\_productivity\_data [https://doi.org/10.5061/dryad.fxpnvx0zt](https://doi.org/10.5061/dryad.fxpnvx0zt) This folder contains data sets (**Bird_prod_data.csv, Clim_mean_prod_lin.csv, Clim_mean_prod_poly.csv, Clim_trend_PCA_prod_lin.csv, Clim_trend_PCA_prod_poly.csv**), models (.rds files; see below for their naming scheme) and code (**R-script_bird_prod.R**) related to the article: *Climatic predictors of long-distance migratory birds’ breeding productivity across Europe* ## Description of the data and file structure The data is stored in subfolder "Data" **Bird_prod_data.csv** * *Reg*: breeding region; CZP = the Czech Republic, DEG-DKC = Germany and Denmark, ESP = Spain, FRP_N = northern part of France, FRP_S = central & southern part of France, GBT_N = northern parts of Great Britain – Wales and England, Scotland, Northern Ireland – and Ireland, GBT_S = southern parts of Great Britain – England and Wales, HGB = Hungary, NLA = the Netherlands, SFH = Finland, SVS = Sweden - *EURING*: species code * *Year*: year corresponding to breeding season - *Species*: species name (see also Table 3 in the article) * *Site*: site code - *Ad*: number of adults * *Juv*: number of juveniles - *TotalEPR*: water availability in wintering grounds (called ETr in the article) * *Ad_scaled*: Number of adults standardized to mean = 0 and SD = 1 for each species and site - *T3, T4, T5, T6*: temperature in March, April, May, June * *GDD10_3, GDD10_4, GDD10_5, GDD10_6*: growing degree-days in March, April, May, June - *GOD*: green-up onset date * *Rain_anom_3, Rain_anom_4, Rain_anom_5, Rain_anom_6*: precipitation anomaly in March, April, May, June, abbreviated as ΔR in the article - *R10_5, R10_6*: number of heavy rain days in May, June * *R20_5, R20_6*: number of very heavy rain days in May, June - *R1c_5, R1c_6*: number of consecutive rain days 1mm in May, June * *R2c_5, R2c_6*: number of consecutive rain days 2mm in May, June **Clim_mean_prod_lin.csv** * *reg*: breeding region - *clim_var*: abbreviation of climate variable * *mean_val*: mean value of the climate variable - *Est_prod_lin*: estimate of the linear term in the relationship between breeding productivity and climate variable * *SE_prod_lin*: standard error of the estimate of the linear term in the relationship between breeding productivity and climate variable **Clim_mean_prod_poly.csv** * *reg*: breeding region - *clim_var*: abbreviation of climate variable * *mean_val*: mean value of the climate variable - *Est_prod_poly*: estimate of the quadratic term in the relationship between breeding productivity and climate variable * *SE_prod_poly*: standard error of the estimate of the quadratic term in the relationship between breeding productivity and climate variable **Clim_trend_PCA_prod_lin.csv** * *reg*: breeding region - *clim_change*: climate warming variable derived from the first axis of PCA (Principal Component Analysis), for months of March, April, May, June * *Est_trend*: slope of the linear temporal trend of climate warming variable over the study period **Clim_trend_PCA_prod_poly.csv** * reg: breeding region - clim_change: climate warming variable derived from the first axis of PCA (Principal Component Analysis), for months of March, April, May, June * Est_trend: slope of the quadratic temporal trend of climate warming variable over the study period Fitted models (88 files) are stored in subfolder "Models" Naming scheme of the models is: **Hyp2 or Hyp3**: models for testing Hypothesis 2 or Hypothesis 3, respectively **resp1 or resp2**: response variable of the model was derived from the relationship between breeding productivity and the linear term of the climate variable (i.e. *Est_prod_lin*, see above in Clim_mean_prod_lin.csv) or the quadratic term of the climate variable (i.e. *Est_prod_poly*, see above in Clim_mean_prod_poly.csv), respectively **lin or poly**: models employ linear or polynomial (quadratic) terms of climate variables, respectively **T, GDD10, ΔR, GOD**: climate variables used in testing Hypothesis 2 or Hypothesis 3, i.e. temperature, growing degree-days, precipitation anomaly, and green-up onset date, respectively **3, 4, 5, 6**: months of March, April, May, or June **warm_PCA1** (for Hypothesis 3 only): climate warming variable was derived from the first axis of PCA (Principal Component Analysis), suffixes 3, 4, 5 or 6 means months of March, April, May, and June ## Code/Software The code file "R-script_bird_prod.R" is an R script created by version 4.3.1, allowing to run all our analyses. It consists of the following parts: * loading the libraries * loading the data set Bird_prod_data.csv and preparing the variables for testing Hypothesis 1 * fitting the models for testing Hypothesis 1 * performing the model averaging * extraction of the marginal effects of climate variables * calculation of the temporal variance explained by climate variables * loading the data sets Clim_mean_prod_lin.csv and Clim_mean_prod_poly.csv and preparing the variables for testing Hypothesis 2 * fitting the models for testing Hypothesis 2 * extraction of parameters from the fitted models * loading the data sets Clim_trend_PCA_prod_lin.csv and Clim_trend_PCA_prod_poly.csv and preparing the variables for testing Hypothesis 3 * fitting the models for testing Hypothesis 3 * extraction of parameters from the fitted models Ongoing climate changes represent a major determinant of demographic processes in many organisms worldwide. Birds, and especially long-distance migrants, are particularly sensitive to such changes. To better understand these impacts on long-distance migrants’ breeding productivity, we tested three hypotheses focused on (i) the shape of the relationships with different climate variables, including previously rarely tested quadratic responses, and on regional differences in these relationships predicted by (ii) mean climatic conditions and (iii) by the rate of climate change in respective regions ranging from Spain to Finland. We calculated breeding productivity from constant effort ringing sites from 11 European countries covering 34 degrees of latitude, and extracted temperature- and precipitation-related climate variables from E-OBS and NASA MODIS datasets. To test our hypotheses, we fitted GLMM and Bayesian meta-analytic models. We revealed hump-shaped responses of productivity to temperature, growing degree-days, green-up onset date, and precipitation anomaly, and negative responses to intense and prolonged rains across the regions. The effects of March temperature and April growing degree-days were more negative in cold than in warm regions, except that one with the highest accumulated heat, whereas increasing June precipitation anomalies were associated with higher productivity in both dry and wet regions. The rate of climate warming was unrelated to productivity responses to climate. The influence of climate on bird productivity proved to be frequently non-linear, as expected by ecological theory. To explain the differences between regions, the rate of climate change is less important than regional interannual variability in climate (which is predicted to increase), but this may change with the progression of climate change in the future. Productivity declines in long-distance migratory songbirds are particularly expected if out-of-norm water excess increases in frequency or strength.

The Hyrcanian forests of Iran are mainly managed with the single-selection silvicultural technique. Despite significant ecological benefits associated with selection cutting, this type of forest management leads towards more challenging situations where it is difficult to maintain and practice successful forestry than in even-aged systems. Therefore, this study provides relevant management tools in the form of models to estimate low growth levels in Hyrcanian forests. In the present study, estimation of the population growth rate and then the allowable cut rate of these forests using a matrix model have been calculated in the Gorazbon district. For this purpose, the data of 256 permanent sample plots measured during the years between 2003 and 2012, as well as the data recorded about the trees harvested according to the forestry plan, have been used. As a first step, the most frequently occurring tree species were divided into four groups (beech, hornbeam, chestnut-leaved oak, and other species). Compartments of the district were divided into two groups of logged and unlogged compartments. The purpose of this division was to estimate the allowable cut and compare its volume with the volumes of observed and predicted allowable cuts obtained from forestry plans. The results showed that the total operated allowable cut (OAC) in logged compartments was more than the estimated allowable cut (EAC). In unlogged compartments, the total predicted allowable cut (PAC) was more than EAC. A comparison of EAC and OAC showed that hornbeam has been harvested more than its potential. However, chestnut-leaved oak and other species group have depicted opposite trends. Our models provide important advancements for estimating allowable cut that can enhance the goal of practicing sustainable forestry.

The social confinement resulting from the COVID-19 crisis temporarily reduced greenhouse gas emissions. Although experts contend that the decrease in pollution rates was not drastic, some surveys detect growth in social concern about the climate. In this new climate-conscious environment, municipalities and local governments are promoting a new way of living and caring for cities, even before they can regain national and international freedom of movement. This work analyzes the connections between new climate awareness arising from the COVID-19 crisis, proposals of sustainable citizenship around the world, and its communication on Twitter to educate the new eco-conscious audience. The methodology mixes quantitative and qualitative analysis, using the Twitonomy Premium tool and the Twitter research tool with data extracted at the end of December 2020. Among the top ten most influential and active accounts, the results show educational institutions, local institutions, companies, neighborhoods, associations, and influencers. The impossibility of living in the city has not prevented citizen education and commitment to make real change for when that city and its citizens return to normality. However, this new normality must be different: more ecological, more responsible, more sustainable, and practiced from early childhood.

Micro hydro power plants (µHPP) are typically used to supply electric energy to microgrids outside the national power grids taking care of the frequency control of the isolated system. A conventional way to maintain the load balance in the system is to use thyristor switched AC-AC converters controlled dump loads. A disadvantage of the AC-AC converters is their reactive power consumption decreasing the power factor at the generator output. To avoid this problem the authors have earlier proposed two converter topologies utilizing symmetrical switching scheme resulting to zero reactive power consumption. The objective of this paper is to evaluate the frequency regulation loop performance of the dump load controlled single generator system by using the symmetrically switched converter structures. Evaluation is carried out by analyzing the performances of different converter structures in a simulator representing the operation of a Cuban µHPP “Los Gallegos”. The results showed that the frequency regulation loop performance using each proposed converter structure satisfied the Cuban standard of frequency regulation, but with the symmetrically switched structures reactive power consumption was reduced resulting to reduced losses and improved effective current delivery capacity of the generator.

Abstract Agricultural practice is facing multiple challenges under volatile commodity markets, inevitable climate change, mounting pest pressure and various other environment-related constraints. The objective of this research is to present a dynamic optimization model of crop rotations and farm management and show its suitability for economic analysis over a 30 year time period. In this model, we include management practices such as fertilization, fungicide treatment and liming, and apply it in a region in Southwestern Finland. Results show that (i) growing pest pressure favours the cultivation of wheat-oats and wheat-oilseeds combinations, while (ii) market prices largely determine the crops in the rotation plan and the specific management practices adopted. The flexibility of our model can also be utilized in evaluating the value of other management options such as new cultivars under different projections of future climate and market conditions.

Baseline and future (2036-2065) river water levels and discharges at 4 gauging stations along the Cambodian Mekong (Kratie, Kampong Cham, Chrouy Changva, and Neak Loeung) under different scenarios of climate change (RCP 4.5 and 8.5) and infrastructural developments. Average depth and duration flood maps are also included for each scenario. A full description of the methods and results can be found in the article: Alexander J. Horton, Nguyen V. K. Triet, Long P. Hoang, Sokchhay Heng, Panha Hok, Sarit Chung, Jorma Koponen, and Matti Kummu. (2022). The Cambodian Mekong floodplain under future development plans and climate change. Nat. Hazards Earth Syst. Sci.