Marjolein E. Lof

Adaptive phenological mismatches of birds and their food in a warming world

AbstractClimate 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 directly. This makes experimental studies on laying date, which can determine whether the mismatch is adaptive, of crucial importance.ZusammenfassungAdaptive phänotypische Fehlanpassungen zwischen Vögeln und ihrer Nahrung in Zeiten der Erderwärmungn Der Klimawandel hat tiefgreifende Auswirkungen auf die Ökologie von Vögeln, wobei der deutlichste Effekt eine Verschiebung des Timings, oder der Phänologie, der Fortpflanzung ist. Um die Konsequenzen einer solchen Verlagerung zu untersuchen haben wir eine Literatursuche durchgeführt und die Rate der phänologischen Veränderung im Brutverhalten der Vögel mit denen der Nestlingsnahrung verglichen. Während in manchen Fällen die Veränderungsraten der Vögel und Nahrungsquelle ähnlich waren gab es auch Nahrungsketten in denen die Rate der Vögel hinter der ihrer Nahrung zurückblieb. Daraus resultiert eine phänologische Fehlabstimmung (mismatch), die die Fitness der Brut beeinträchtigt. Zwei Hypothesen können erklären warum der Klimawandel zu dieser zeitlichen Fehlabstimmung im Timing der Fortpflanzung führt: Entweder die verwendeten Signale sagen nicht mehr akkurat den Zeitpunkt maximaler Nahrungsabundanz voraus (cues-Hypothese), oder aber die Fitness-Kosten einer ausreichend frühen Eiproduktion und/oder Inkubation sind im frühen Frühjahr so beträchtlich, dass sie nicht ausreichend durch die Fitness-Gewinne einer gut getimten Fortpflanzung ausgeglichen werden (constraints-Hypothese). Im letzten Fall ist eine phänologische Fehlabstimmung adaptiv. Wir stellen hier ein einfaches mathematisches Modell vor, welches verdeutlicht, dass dies der Fall sein könnte, wenn es Fitness-Kosten der Eiproduktion und/oder Inkubation unter kalten Temperaturbedingungen gibt und wenn die Temperaturen, die den Höhepunkt der Nahrungsabundanz beeinflussen, stärker ansteigen als die Temperaturen, die die Kosten der Eiproduktion und Inkubation bestimmen, wie es in den Niederlanden der Fall ist. Ob eine phänologische Fehlabstimmung adaptiv ist hat bedeutende Auswirkungen auf die natürliche Selektion des Fortpflanzungs-Timings. Bei einer nichtadaptiven Fehlabstimmung steht das Timing unter direkter natürlicher Selektion, andernfalls findet Selektion auf die Kosten der Eiproduktion statt, möglicherweise auch auf die Eigröße oder Größe der adulten Vögel. In jedem Fall wird erwartet, dass eine zeitliche Fehlabstimmung negative Auswirkungen auf die Population hat, und besonders wenn diese Fehlabstimmung adaptiv ist, können Konsequenzen nicht durch eine direkte Reaktion auf die natürliche Selektion des Timings reduziert werden. Diese Tatsache unterstreicht die Bedeutung experimenteller Studien von Legedaten, welche aufklären können, ob eine Fehlabstimmung adaptiv ist.

Predicting demographically sustainable rates of adaptation: can great tit breeding time keep pace with 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.

Timing in a fluctuating environment: environmental variability and asymmetric fitness curves can lead to adaptively mismatched avian reproduction

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 effect of chemical information on the spatial distribution of fruit flies: I Model results.

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.

Odor mediated aggregation enhances the colonization ability of Drosophila melanogaster

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 mate choice and protection against natural enemies, balanced by the costs of limiting resources and intraspecific competition. Many insects use chemical information to find conspecifics and to form aggregations. In this study, we describe a spatio-temporal simulation model designed to explore and quantify the effects of the strength of chemical attraction, on the colonization ability of a fruit fly (Drosophila melanogaster) population. We found that the use of infochemicals is crucial for colonizing an area. Fruit flies subject to an Allee effect that are unable to respond to chemical information could not successfully colonize the area and went extinct within four generations. This was mainly caused by very high mortality due to the Allee effect. Even when the Allee effect did not play a role, the random dispersing population had more difficulties in colonizing the area and is doomed to extinction in the long run. When fruit flies had the ability to respond to chemical information, they successfully colonized the orchard. This happened faster, for stronger attraction to chemical information. In addition, more fruit flies were able to find the resources and the settlement on the resources was much higher. This resulted in a reduced mortality due to the Allee effect for fruit flies able to respond to chemical information. Odor-mediated aggregation thus enhances the colonization ability of D. melanogaster. Even a weak attraction to chemical information paved the way to successfully colonize the orchard.

The Effect of Chemical Information on the Spatial Distribution of Fruit Flies: II Parameterization, Calibration, and Sensitivity

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 saturation effect) can be adapted to the use of two different but interrelated stimuli (food odors and aggregation pheromone). Although we use all available information for its parameterization, this model is still overparameterized. Third, the spatio-temporal dispersion of infochemicals is hard to model: Modeling turbulent dispersal on a length scale of 10 m is notoriously difficult. Moreover, we have to reduce this inherently three-dimensional physical process to two dimensions in order to fit in the two-dimensional model for the insects. We investigate the consequences of this dimension reduction, and we demonstrate that it seriously affects the parameterization of the model for the infochemicals.In the second part of this paper, we present the results of a sensitivity analysis. This sensitivity analysis can be used in two manners: firstly, it tells us how general the simulation results are if variations in the parameters are allowed, and secondly, we can use it to infer which parameters need more precise quantification than is available now. It turns out that the short term outcome of our model is most sensitive to the food odor production rate and the fruit fly dispersivity. For the other parameters, the model is quite robust.The dependence of the model outcome with respect to the qualitative model choices cannot be investigated with a parameter sensitivity analysis. We conclude by suggesting some experimental setups that may contribute to answering this question.

Achieving Durable Resistance Against Plant Diseases: Scenario Analyses with a National-Scale Spatially Explicit Model for a Wind-Dispersed Plant Pathogen

Genetic resistance in crops is a cornerstone of disease management in agriculture. Such genetic resistance is often rapidly broken due to selection for virulence in the pathogen population. Here, we ask whether there are strategies that can prolong the useful life of plant resistance genes. In a modeling study, we compared four deployment strategies: gene pyramiding, sequential use, simultaneous use, and a mixed strategy. We developed a spatially explicit model for France and parameterized it for the fungal pathogen Puccinia striiformis f. sp. tritici (causing wheat yellow rust) to test management strategies in a realistic spatial setting. We found that pyramiding two new resistance genes in one variety was the most durable solution only when the virulent genotype had to emerge by mutation. Deploying single-gene-resistant varieties concurrently with the pyramided variety eroded the durability of the gene pyramid. We found that continuation of deployment of varieties with broken-down resistance prolonged t...Genetic resistance in crops is a cornerstone of disease management in agriculture. Such genetic resistance is often rapidly broken due to selection for virulence in the pathogen population. Here, we ask whether there are strategies that can prolong the useful life of plant resistance genes. In a modeling study, we compared four deployment strategies: gene pyramiding, sequential use, simultaneous use, and a mixed strategy. We developed a spatially explicit model for France and parameterized it for the fungal pathogen Puccinia striiformis f. sp. tritici (causing wheat yellow rust) to test management strategies in a realistic spatial setting. We found that pyramiding two new resistance genes in one variety was the most durable solution only when the virulent genotype had to emerge by mutation. Deploying single-gene-resistant varieties concurrently with the pyramided variety eroded the durability of the gene pyramid. We found that continuation of deployment of varieties with broken-down resistance prolonged the useful life of simultaneous deployment of four single-gene-resistant varieties versus sequential use. However, when virulence was already present in the pathogen population, durability was low and none of the deployment strategies had effect. These results provide guidance on effective strategies for using resistance genes in crop protection practice.

Exploitation of Chemical Signaling by Parasitoids: Impact on Host Population Dynamics

Chemical information mediates species interactions in a wide range of organisms. Yet, the effect of chemical information on population dynamics is rarely addressed. We designed a spatio-temporal parasitoid—host model to investigate the population dynamics when both the insect host and the parasitic wasp that attacks it can respond to chemical information. The host species, Drosophila melanogaster, uses food odors and aggregation pheromone to find a suitable resource for reproduction. The larval parasitoid, Leptopilina heterotoma, uses these same odors to find its hosts. We show that when parasitoids can respond to food odors, this negatively affects fruit fly population growth. However, extra parasitoid responsiveness to aggregation pheromone does not affect fruit fly population growth. Our results indicate that the use of the aggregation pheromone by D. melanogaster does not lead to an increased risk of parasitism. Moreover, the use of aggregation pheromone by the host enhances its population growth and enables it to persist at higher parasitoid densities.

Modelling mobile agent‐based ecosystem services using kernel‐weighted predictors

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.

Effects of land use on infestation and parasitism rates of cabbage seed weevil in oilseed rape: Landscape effects on Ceutorhynchus obstrictus infestation and parasitism rates

BACKGROUNDnThis study investigated how infestation rates of an important oilseed rape pest, the cabbage seed weevil (Ceutorhynchus obstrictus) and rates of parasitization by its parasitoids are affected by land use, up to 1000 m from 18 focal fields.nnnRESULTSnThe mean proportion of C. obstrictus-infested pods per plant was 8% (2-19.5%). Infestation rates were higher if the adjacent habitat was a herbaceous semi-natural habitat than if it was either another crop or a woody habitat. Infestation rates were positively related to the area of herbaceous semi-natural vegetation, permanent grassland and wheat (which followed oilseed rape in the crop rotation) at a spatial scale of at least 1 km. The mean parasitism rate of C. obstrictus larvae was 55% (8.3-87%), sufficient to provide efficient biocontrol. Parasitism rates were unrelated to adjacent habitats, however, they were positively related to the presence of herbaceous linear elements in the landscape and negatively related to permanent grasslands at a spatial scale of 200 m.nnnCONCLUSIONnProximity of herbaceous elements increased both infestation rates and parasitism, while infestation was also related to landscape factors at larger distances. The findings provide an empirical basis for designing landscapes that suppress C. obstrictus, at both field and landscape scales.