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In het Klimaatakkoord zijn afspraken gemaakt om in 2030 de uitstoot van CO 2 in de veenweidegebieden van Nederland te verlagen. In deze gebieden wordt het veen drooggelegd, zodat het geschikt is voor landbouw. Door veengebieden droog te leggen, daalt de bodem en komt er CO2 vrij. Dat komt doordat het veen wordt blootgesteld aan zuurstof en langzaam verbrandt (oxidatie).Nieuwe drainagetechnieken kunnen ervoor zorgen dat er minder CO 2vrijkomt. Een voorbeeld is drukdrainage op landbouwpercelen aan te leggen. Met een ondergronds buizenstelsel kan de grondwaterstand van landbouwpercelen beter worden verhoogd en verlaagd. Door in droge perioden de grondwaterstand te verhogen, komt het veen minder in contact met zuurstof, daalt de bodem minder en komt er minder CO2 vrij.De Alblasserwaard-Vijfheerenlanden is een gebied met bijna 15.000 hectare veenweidegebied. In dit gebied zoekt de provincie Zuid-Holland naar een nieuwe balans tussen landbouw, bodemdaling en CO 2-uitstoot.Het RIVM heeft uitgerekend of de voordelen van drukdrainage in dit gebied opwegen tegen de kosten. Dit blijkt op bijna 4.000 hectare van de Alblasserwaard-Vijfheerenlanden zo te zijn. De bodemdaling vermindert daar door drukdrainage met 50 tot 75 procent, net als de CO2-uitstoot. Ook maakt de maatregel het gebied aantrekkelijker voor weidevogels, zoals grutto's, kieviten en schol-eksters. Drukdrainage heeft meer voordelen, zoals minder kosten voor waterzuivering en waterbeheer. Een nadeel van de hogere grondwaterstand is dat er minder gras kan worden geproduceerd.Het RIVM heeft op basis van de analyse een kaart gemaakt die per landbouwperceel aangeeft wat de voordelen van drukdrainage zijn. De provincie wil als proef 250–500 hectare drukdrainage in het veenweidegebied gaan aanleggen. Op basis van deze kaart kunnen percelen worden gekozen waar dat het beste kan. De grootste onzekerheden in de berekeningen zijn de prijs die in de toekomst voor CO2 wordt berekend en de kosten om de drainage aan te leggen en

1. Agriculture benefits from ecosystem services provided by mobile agents, such as biological pest control by natural enemies and pollination by bees. However, methods that can generate spatially explicit predictions and maps of these ecosystem services based on empirical data are still scarce. 2. Here we propose a generic statistical model to derive kernel functions to characterize the spatial distribution of ecosystem services provided by mobile agents. The model is similar in spirit to a generalized linear model, and uses data of landscape composition and ecosystem services assessed at target sites to estimate parameters of the kernel. The approach is tested in a simulation study and illustrated by an empirical case study on parasitism rates of the diamondback moth Plutella xylostella. 3. The simulation study shows that the scale parameter of the exponential power kernel can be estimated with limited bias, whereas estimation of the shape parameter is difficult. For the case study the model provides biologically relevant estimates for the kernel associated with parasitism of Plutella xylostella. These estimates can be used to generate ecosystem service maps for existing or planned landscapes. The case study reveals that predictions can be sensitive to the parameter values for the width and shape of the kernel, and to the link function used in the statistical model. 4. In the last two decades numerous empirical studies assessed ecosystem services at target sites and related these to the surrounding landscape. Our method can take advantage of these data by estimating underlying kernels that can be used to map the spatial distribution of ecosystem services. However, empirical data that can discriminate between alternative kernel shapes remain critical.

Understanding the relationship between an insect's developmental rate and temperature is crucial to forecast insect phenology under climate change. In the winter moth Operophtera brumata timing of egg-hatching has severe fitness consequences on growth and reproduction as egg-hatching has to match bud burst of the host tree. In the winter moth, as in many insect species, egg development is strongly affected by ambient temperatures. Here we use laboratory experiments to show for the first time that the effect of temperature on developmental rate depends on the stage of development of the eggs. Building on this experimental finding, we present a novel physiological model to describe winter moth egg development in response to temperature. Our model, a modification of the existing Sharpe−Schoolfield biophysical model, incorporates the effect of developmental stage on developmental rate. Next we validate this model using a 13-year data-set from winter moth eggs kept under ambient conditions and compared this validation with a degree day model and with the Sharpe−Schoolfield model, which lacks the interaction between temperature and developmental stage on developmental rate. We show that accounting for the interaction between temperature and developmental stage improved the predictive power of the model and contributed to our understanding of annual variation in winter moth egg phenology. As climate change leads to unequal changes in temperatures throughout the year, a description of insect development in response to realistic patterns of temperature rather than an invariable degree-day approach will help us to better predict future responses of insect phenology, and thereby insect fitness, to climate change.

Populations need to adapt to sustained climate change, which requires micro-evolutionary change in the long term. A key question is how the rate of this micro-evolutionary change compares with the rate of environmental change, given that theoretically there is a ‘critical rate of environmental change’ beyond which increased maladaptation leads to population extinction. Here, we parametrize two closely related models to predict this critical rate using data from a long-term study of great tits (Parus major). We used stochastic dynamic programming to predict changes in optimal breeding time under three different climate scenarios. Using these results we parametrized two theoretical models to predict critical rates. Results from both models agreed qualitatively in that even ‘mild’ rates of climate change would be close to these critical rates with respect to great tit breeding time, while for scenarios close to the upper limit of IPCC climate projections the calculated critical rates would be clearly exceeded with possible consequences for population persistence. We therefore tentatively conclude that micro-evolution, together with plasticity, would rescue only the population from mild rates of climate change, although the models make many simplifying assumptions that remain to be tested., Populations need to adapt to sustained climate change, which requires micro-evolutionary change in the long term. A key question is how the rate of this micro-evolutionary change compares with the rate of environmental change, given that theoretically there is a ‘critical rate of environmental change’ beyond which increased maladaptation leads to population extinction. Here, we parametrize two closely related models to predict this critical rate using data from a long-term study of great tits (Parus major). We used stochastic dynamic programming to predict changes in optimal breeding time under three different climate scenarios. Using these results we parametrized two theoretical models to predict critical rates. Results from both models agreed qualitatively in that even ‘mild’ rates of climate change would be close to these critical rates with respect to great tit breeding time, while for scenarios close to the upper limit of IPCC climate projections the calculated critical rates would be clearly exceeded with possible consequences for population persistence. We therefore tentatively conclude that micro-evolution, together with plasticity, would rescue only the population from mild rates of climate change, although the models make many simplifying assumptions that remain to be tested.

Climate change has profound ecological effects in birds, with the clearest effect a shift in timing, or phenology, of avian reproduction. To assess the consequences of these shifts, we performed a literature search and compared the rates of phenological change in the reproduction of birds with that of the food for their offspring. While in some areas the rate of change of the birds and their food was similar, there were also areas where the birds’ shift lagged behind that of their food. In these cases, this will lead to a phenological mismatch, which will affect the fitness of the brood. There are two hypotheses explaining why climate change leads to mismatched reproduction: either the cues used no longer accurately predict the peak in food abundance (the cues hypothesis) or the fitness costs of egg production and/or incubation of laying early enough to match reproduction are substantial in early spring and are not compensated by the fitness benefits of a better matched reproduction (constraint hypothesis). In the latter case, the phenological mismatch is adaptive. We present a simple mathematical model to show that this may be the case if there are fitness costs of egg laying and/or incubation under cold conditions and if the temperatures that determine the peak in food abundance increase stronger than the temperatures affecting the costs of egg laying and incubation, as is the case in the Netherlands. Whether or not a phenological mismatch is adaptive has important consequences for natural selection acting on timing of reproduction. If the mismatch is not adaptive, timing of reproduction will be under direct natural selection, while, if the mismatch is adaptive, selection is likely to be on the costs of egg production, possibly on egg size or adult size. In all cases, a mismatch is expected to have negative population consequences and, especially when the mismatch is adaptive, these consequences cannot be reduced by a response to natural selection on timing direct, Climate change has profound ecological effects in birds, with the clearest effect a shift in timing, or phenology, of avian reproduction. To assess the consequences of these shifts, we performed a literature search and compared the rates of phenological change in the reproduction of birds with that of the food for their offspring. While in some areas the rate of change of the birds and their food was similar, there were also areas where the birds’ shift lagged behind that of their food. In these cases, this will lead to a phenological mismatch, which will affect the fitness of the brood. There are two hypotheses explaining why climate change leads to mismatched reproduction: either the cues used no longer accurately predict the peak in food abundance (the cues hypothesis) or the fitness costs of egg production and/or incubation of laying early enough to match reproduction are substantial in early spring and are not compensated by the fitness benefits of a better matched reproduction (constraint hypothesis). In the latter case, the phenological mismatch is adaptive. We present a simple mathematical model to show that this may be the case if there are fitness costs of egg laying and/or incubation under cold conditions and if the temperatures that determine the peak in food abundance increase stronger than the temperatures affecting the costs of egg laying and incubation, as is the case in the Netherlands. Whether or not a phenological mismatch is adaptive has important consequences for natural selection acting on timing of reproduction. If the mismatch is not adaptive, timing of reproduction will be under direct natural selection, while, if the mismatch is adaptive, selection is likely to be on the costs of egg production, possibly on egg size or adult size. In all cases, a mismatch is expected to have negative population consequences and, especially when the mismatch is adaptive, these consequences cannot be reduced by a response to natural selection on timing direct

Adaptation in dynamic environments depends on the grain, magnitude and predictability of ecological fluctuations experienced within and across generations. Phenotypic plasticity is a well-studied mechanism in this regard, yet the potentially complex effects of stochastic environmental variation on optimal mean trait values are often overlooked. Using an optimality model inspired by timing of reproduction in great tits, we show that temporal variation affects not only optimal reaction norm slope, but also elevation. With increased environmental variation and an asymmetric relationship between fitness and breeding date, optimal timing shifts away from the side of the fitness curve with the steepest decline. In a relatively constant environment, the timing of the birds is matched with the seasonal food peak, but they become adaptively mismatched in environments with temporal variation in temperature whenever the fitness curve is asymmetric. Various processes affecting the survival of offspring and parents influence this asymmetry, which collectively determine the ‘safest’ strategy, i.e. whether females should breed before, on, or after the food peak in a variable environment. As climate change might affect the (co)variance of environmental variables as well as their averages, risk aversion may influence how species should shift their seasonal timing in a warming world., Adaptation in dynamic environments depends on the grain, magnitude and predictability of ecological fluctuations experienced within and across generations. Phenotypic plasticity is a well-studied mechanism in this regard, yet the potentially complex effects of stochastic environmental variation on optimal mean trait values are often overlooked. Using an optimality model inspired by timing of reproduction in great tits, we show that temporal variation affects not only optimal reaction norm slope, but also elevation. With increased environmental variation and an asymmetric relationship between fitness and breeding date, optimal timing shifts away from the side of the fitness curve with the steepest decline. In a relatively constant environment, the timing of the birds is matched with the seasonal food peak, but they become adaptively mismatched in environments with temporal variation in temperature whenever the fitness curve is asymmetric. Various processes affecting the survival of offspring and parents influence this asymmetry, which collectively determine the ‘safest’ strategy, i.e. whether females should breed before, on, or after the food peak in a variable environment. As climate change might affect the (co)variance of environmental variables as well as their averages, risk aversion may influence how species should shift their seasonal timing in a warming world.

The study of the role of chemical information in species interactions has been mostly restricted to studies at the level of individual organisms. The central question in this thesis is how intraspecific chemical information conveyance and exploitation thereof by a natural enemy affects the spatial population dynamics of a species. To answer this question, I developed a spatio-temporal model where both host and parasitoid can respond to infochemicals. Our model system consists of the fruit fly Drosophila melanogaster, and its natural enemy, the larval parasitoid Leptopilina heterotoma. D. melanogaster uses its aggregation pheromone in combination with odours from fermenting fruits to localise suitable resources for reproduction. L. heterotoma uses these same odours to localise its host. For D. melanogaster, aggregation on a resource can be beneficial when a population is small and has to overcome negative effects associated with low population densities. Such negative effects, known as the Allee effect, can for instance be caused by difficulties in resource exploitation or in finding a mate. Aggregation also involves costs. Individuals within an aggregation frequently experience more severe competition for food, space and mates than they would experience when being on their own. Furthermore, I investigated which behavioural decisions enhance the ability to find - and distinguish between – odour sources that differ in their suitability for reproduction. On the individual level, this research showed that, like real fruit flies, the modelled fruit flies need to have a preference for the presence of both aggregation pheromone and food odours, over food odours alone, to be able to distinguish between the two types of odour sources. The results show that this stronger preference does not have to be innate. As long as fruit flies are able to remember and adjust their current preference based on the odour concentrations that they perceive, more fruit flies find the more attr

In a companion paper (Lof et al., in Bull. Math. Biol., 2008), we describe a spatio-temporal model for insect behavior. This model includes chemical information for finding resources and conspecifics. As a model species, we used Drosophila melanogaster, because its behavior is documented comparatively well. We divide a population of Drosophila into three states: moving, searching, and settled. Our model describes the number of flies in each state, together with the concentrations of food odor and aggregation pheromone, in time and in two spatial dimensions. Thus, the model consists of 5 spatio-temporal dependent variables, together with their constituting relations. Although we tried to use the simplest submodels for the separate variables, the parameterization of the spatial model turned out to be quite difficult, even for this well-studied species. In the first part of this paper, we discuss the relevant results from the literature, and their possible implications for the parameterization of our model. Here, we focus on three essential aspects of modeling insect behavior. First, there is the fundamental discrepancy between the (lumped) measured behavioral properties (i.e., fruit fly displacements) and the (detailed) properties of the underlying mechanisms (i.e., dispersivity, sensory perception, and state transition) that are adopted as explanation. Detailed quantitative studies on insect behavior when reacting to infochemicals are scarce. Some information on dispersal can be used, but quantitative data on the transition between the three states could not be found. Second, a dose-response relation as used in human perception research is not available for the response of the insects to infochemicals; the behavioral response relations are known mostly in a qualitative manner, and the quantitative information that is available does not depend on infochemical concentration. We show how a commonly used Michaelis¿Menten type dose-response relation (incorporating a satur

Animal aggregation is a general phenomenon in ecological systems. Aggregations are generally considered as an evolutionary advantageous state in which members derive the benefits of protection and mate choice, balanced by the costs of limiting resources and competition. In insects, chemical information conveyance plays an important role in finding conspecifics and forming aggregations. In this study, we describe a spatio-temporal simulation model designed to explore and quantify the effects of these infochemicals, i.e., food odors and an aggregation pheromone, on the spatial distribution of a fruit fly (Drosophila melanogaster) population, where the lower and upper limit of local population size are controlled by an Allee effect and competition. We found that during the spatial expansion and strong growth of the population, the use of infochemicals had a positive effect on population size. The positive effects of reduced mortality at low population numbers outweighed the negative effects of increased mortality due to competition. At low resource densities, attraction toward infochemicals also had a positive effect on population size during recolonization of an area after a local population crash, by decreasing the mortality due to the Allee effect. However, when the whole area was colonized and the population was large, the negative effects of competition on population size were larger than the positive effects of the reduction in mortality due to the Allee effect. The use of infochemicals thus has mainly positive effects on population size and population persistence when the population is small and during the colonization of an area.