Empirical and dynamic approaches for modelling the yield and N content of European grasslands

This work was supported by the Horizon 2020 SFS-01c-2015 project entitled “Innovation of sustainable sheep and goat production in Europe (iSAGE)” [grant number 679302]; and the Rural & Environment Science & Analytical Services Division of the Scottish Government. BC3 is supported by the Basque Government through the BERC 2018–2021 program and by Spanish Ministry of Economy and Competitiveness MINECO through BC3 María de Maeztu excellence accreditation MDM-2017-0714. Agustin del Prado is supported by the Ramon y Cajal Programme. We would like to thank all the people who provided the data which made this work possible. In particular, Professor Wolfgang Schmidt, for data from the Experimental Botanical Garden of Göttingen University. Also the Lawes Agricultural Trust and Rothamsted Research for data from the e-RA database. The Rothamsted Long-term Experiments National Capability (LTE-NCG) is supported by the UK Biotechnology and Biological Sciences Research Council and the Lawes Agricultural Trust.Peer reviewedPublisher PD

Modelling climate change impacts on European grassland-based livestock systems

Climate change is leading to higher temperatures and altered rainfall patterns across Europe. These changes are likely to have major impacts on plant life. This is particularly relevant for livestock production systems which are dependent on grass and forage. Farmers need to know what they can expect in the future so that they can be well prepared and ensure that their livestock will have enough to eat. This thesis aims to quantify the impacts of rising atmospheric CO2 concentrations, higher temperatures and changes in water availability on the yield and protein content of European grasslands. The first approach used was a meta-analysis. Data from experiments in which the climate had been artificially altered was collected and divided according to geographic region (Alpine, Atlantic, continental, northern and southern) and plant type (graminoids, legumes, forbs and shrubs). Using Markov Chain Monte Carlo (MCMC) simulations, mixed models were developed to estimate the expected changes to plant yield and protein (i.e. nitrogen (N)) concentration under different climatic changes. The results showed that areas predicted to become warmer and wetter (i.e. northern Europe and parts of Alpine and continental Europe) will benefit from higher plant yields, but reduced plant N concentration. Areas which will become warmer and drier (i.e. southern Europe and parts of continental Europe) will see decreases in both yield and N concentration. The Atlantic region is the area where climate change is expected to be the least extreme and the effects on plant life will be relatively minor. Shrubs will particularly benefit from rising atmospheric CO2 concentrations, though will also suffer large decreases in N concentration, as will forbs. The next approach considered different methodologies for modelling grassland yield and N yield. One method involved developing a statistical model using data from long-term grassland experiments across Europe. Through stepwise linear regression, equations were developed to model grassland yield and N yield based on various weather and managerial variables. The other method used a pre-existing process-based model (Century), which was applied to six sites across Europe. Both approaches produced reasonable estimates of grassland yield and N yield. The prediction error was lower for the Century model while the regression methodology produced better correlations between observations and predictions. Both models were quite sensitive to uncertainties in weather parameters, particularly precipitation, with little sensitivity to soil properties. Overall, the regression approach was found to be suitable for considering general trends over large spatial scales, while the Century model was more appropriate for local-scale analysis. The two models described above were used to quantify the effects of two different climate change scenarios (one midrange and one more extreme) on the five European regions listed above. The two models generally produced similar predictions, indicating that grassland yields will increase in most areas though there may be slight decreases in southern Europe. Also, plant N concentrations will decrease. Generally permanent grasslands responded more positively to climate change than temporary ones. The impact of climate change tends to be less than the impact of fertiliser, geographic region or grassland type, suggesting that appropriate changes to grassland management practices should be able to mitigate the negative effects of climate change. The modelling described above was all performed using a monthly time-step. This is computationally efficient, but means that short-term extreme weather events are not accounted for. Extreme weather events such as heavy rainfall, droughts and heat waves are predicted to become both more frequent and more intense in the future and it is important to consider the impacts they will have on grasslands and therefore livestock. Two methodologies were used to quantify the effects of extreme weather events on grasslands. The first uses multiple regression analysis and incorporates terms such as ‘number of days in a month with temperature greater than 30°’ to account for weather extremes. The equations developed had a good fit with observed data. They were found to be predominantly sensitive to uncertainties in precipitation rather than in temperature or grassland species composition. Two projected future weather datasets were applied to the equations; both followed the same climate change scenario, but one included extreme events and the other was smoothed to reduce the extremes. Comparing the model outputs from the two datasets showed that smoothing the data increased the predicted yields and N yields, demonstrating that extreme weather events are detrimental to grasslands. In general, the yield of temporary grasslands decreased over time, while for permanent grasslands it increased. There was little change in N yield over time. The other methodology used the pre-existing process-based model DailyDayCent, which is very similar to the Century model, but is based on a daily rather than a monthly time-step. DailyDayCent was applied to six sites across Europe and was found to have reasonably good fit, though struggled to capture inter-annual variability. The model was predominantly sensitive to uncertainties in rainfall measurements rather than temperature. Two climate change datasets, with and without extreme events, were applied to the model for each of the six sites. Predicted yields and N yields were similar to those found with the Century model. The presence or absence of extreme events usually had little effect, but this may have been due to limitations of the model. The exception was for a site in southern Europe, where the presence of extreme events led to increases in yield and N yield in the short-term, but large decreases in the long-term. Overall, grassland yields are expected to increase in the future in response to climate change (except possibly in southern Europe), particularly for permanent grasslands, while plant N concentration will decrease. Increased yields are generally good for livestock, though reduced N concentrations indicate that grazing animals will need to have a higher intake in order to receive the same amount of protein. Extreme weather events are an important consideration, leading to reductions in grassland yield and N yield. Farmers need to be prepared to meet the challenges presented by such events, for example through using more resilient plant species or increasing plant species richness

Landscape level associations between birds, mosquitoes and microclimates:possible consequences for disease transmission?

Background: Mosquito-borne diseases are on the rise. While climatic factors have been linked to disease occurrences, they do not explain the non-random spatial distribution in disease outbreaks. Landscape-related factors, such as vegetation structure, likely play a crucial but hitherto unquantified role. Methods: We explored how three critically important factors that are associated with mosquito-borne disease outbreaks: microclimate, mosquito abundance and bird communities, vary at the landscape scale. We compared the co-occurrence of these three factors in two contrasting habitat types (forest versus grassland) across five rural locations in the central part of the Netherlands between June and September 2021. Results: Our results show that forest patches provide a more sheltered microclimate, and a higher overall abundance of birds. When accounting for differences in landscape characteristics, we also observed that the number of mosquitoes was higher in isolated forest patches. Conclusions: Our findings indicate that, at the landscape scale, variation in tree cover coincides with suitable microclimate and high Culex pipiens and bird abundance. Overall, these factors can help understand the non-random spatial distribution of mosquito-borne disease outbreaks. </p

Distribution of Culex pipiens life stages across urban green and grey spaces in Leiden, The Netherlands

Abstract Background There is an urgent need for cities to become more climate resilient; one of the key strategies is to include more green spaces in the urban environment. Currently, there is a worry that increasing green spaces might increase mosquito nuisance. As such, this study explores a comprehensive understanding of how mosquitoes utilise contrasting grey and green habitats at different life stages and which environmental factors could drive these distributions. Methods We used a setup of six paired locations, park (green) vs. residential (grey) areas in a single model city (Leiden, The Netherlands), where we sampled the abundances of different mosquito life stages (eggs, larvae, adults) and the local microclimatic conditions. In this study, we focused on Culex pipiens s.l., which is the most common and abundant mosquito species in The Netherlands. Results Our results show that while Cx. pipiens ovipositioning rates (number of egg rafts) and larval life stages were far more abundant in residential areas, adults were more abundant in parks. These results coincide with differences in the number of suitable larval habitats (higher in residential areas) and differences in microclimatic conditions (more amenable in parks). Conclusions These findings suggest that Cx. pipiens dispersal may be considerably more important than previously thought, where adult Cx. pipiens seek out the most suitable habitat for survival and breeding success. Our findings can inform more targeted and efficient strategies to mitigate and reduce mosquito nuisance while urban green spaces are increased, which make cities more climate resilient. Graphical Abstrac