Frédéric Barraquand

Connecting people and ideas from around the world: global innovation platforms for next-generation ecology and beyond

We present a case for using Global Community Innovation Platforms (GCIPs), an approach to improve innovation and knowledge exchange in international scientific communities through a common and open online infrastructure. We highlight the value of GCIPs by focusing on recent efforts targeting the ecological sciences, where GCIPs are of high relevance given the urgent need for interdisciplinary, geographical, and cross-sector collaboration to cope with growing challenges to the environment as well as the scientific community itself. Amidst the emergence of new international institutions, organizations, and meetings, GCIPs provide a stable international infrastructure for rapid and long-term coordination that can be accessed by any individual. This accessibility can be especially important for researchers early in their careers. Recent examples of early-career GCIPs complement an array of existing options for early-career scientists to improve skill sets, increase academic and social impact, and broaden career opportunities. We provide a number of examples of existing early-career initiatives that incorporate elements from the GCIPs approach, and highlight an in-depth case study from the ecological sciences: the International Network of Next-Generation Ecologists (INNGE), initiated in 2010 with support from the International Association for Ecology and 20 member institutions from six continents.

Scaling up predator–prey dynamics using spatial moment equations

Summary Classical models of predator–prey dynamics, commonly used in community and evolutionary ecology to explain population cycles, species coexistence, the effects of enrichment, or predict the evolution of behavioural traits, are often based on the mass-action assumption. This means encounter rates between predators and prey are expressed as a product of predator and prey landscape densities; as if the system was well-mixed. While mass-action may occur at small spatial scales, spatial variances and covariances in prey and predator densities affect encounter rates at large spatial scales. In the context of host–parasitoid interactions, this has been incorporated into theory for some time, but for predators, well-mixed or other ad hoc models are often used despite empirical evidence for intricate spatial variation in predator and prey numbers. We review the classical models and concepts, their strengths and weaknesses, and we present two recent spatial moment approaches that scale up predator–prey population dynamics from the individual or patch level to large spatial scales. Both methods include descriptors of spatial structure as corrections to encounter rates, but differ in whether or not these descriptors have dynamics that are explicit functions of movements, births and deaths. We describe how these spatial moment techniques work, what new results they have so far produced, and provide some suggestions to improve the connection of predator–prey theoretical models to empirical studies.

Demographic responses of a site-faithful and territorial predator to its fluctuating prey: long-tailed skuas and arctic lemmings

Environmental variability, through interannual variation in food availability or climatic variables, is usually detrimental to population growth. It can even select for constancy in key life-history traits, though some exceptions are known. Changes in the level of environmental variability are therefore important to predict population growth or life-history evolution. Recently, several cyclic vole and lemming populations have shown large dynamical changes that might affect the demography or life-histories of rodent predators. Skuas constitute an important case study among rodent predators, because of their strongly saturating breeding productivity (they lay only two eggs) and high degree of site fidelity, in which they differ from nomadic predators raising large broods in good rodent years. This suggests that they cannot capitalize on lemming peaks to the same extent as nomadic predators and might be more vulnerable to collapses of rodent cycles. We develop a model for the population dynamics of long-tailed skuas feeding on lemmings to assess the demographic consequences of such variable and non-stationary prey dynamics, based on data collected in NE Greenland. The model shows that populations of long-tailed skua sustain well changes in lemming dynamics, including temporary collapses (e.g. 10 years). A high floater-to-breeder ratio emerges from rigid territorial behaviour and a long-life expectancy, which buffers the impact of adult abundances decrease on the population reproductive output. The size of the floater compartment is affected by changes in both mean and coefficient of variation of lemming densities (but not cycle amplitude and periodicity per se). In Greenland, the average lemming density is below the threshold density required for successful breeding (including during normally cyclic periods). Due to Jensens inequality, skuas therefore benefit from lemming variability; a positive effect of environmental variation. Long-tailed skua populations are strongly adapted to fluctuating lemming populations, an instance of demographic lability in the reproduction rate. They are also little affected by poor lemming periods, if there are enough floaters, or juveniles disperse to neighbouring populations. The status of Greenland skua populations therefore strongly depends upon floater numbers and juvenile movements, which are not known. This reveals a need to intensify colour-ringing efforts on the long-tailed skua at a circumpolar scale.

Cognitive abilities of a central place forager interact with prey spatial aggregation in their effect on intake rate

When foraging in a landscape, predators choose travelling directions according to their immediate knowledge of prey distribution within their perceptual fields and, when appropriate, to their past foraging experience. A substantial part of foraging theory is based on patch use in spatially implicit domains, and rarely has it considered foraging paths involving directional choices driven by memory and perception. Using a model mixing directed and random movements of a predator, we investigated how perception range and duration of spatial memory influence the long-term intake rate of a central place forager depending on prey spatial distribution. We found that intake rate increased and eventually saturated with increasing perception range regardless of prey spatial distribution. In contrast, the effect of spatial memory duration was mediated by the level of prey spatial aggregation. Assuming that an increase in memory or perception abilities has a cost, we found that it was not beneficial to possess simultaneously a wide perception range and a long-term spatial memory when prey distribution was aggregated. Moreover, when looking at the functional response of predators with different ‘cognitive strategies’, we found that those relying mainly on memory were limited by the prey global densities while those relying mainly on perception were limited by the level of prey aggregation. These results suggest that cognitive strategies might have evolved as a response to the prey spatial distribution and that prey spatial aggregation, not only prey global density, should be considered an important component of the functional response.

Intense or spatially heterogeneous predation can select against prey dispersal

Dispersal theory generally predicts kin competition, inbreeding, and temporal variation in habitat quality should select for dispersal, whereas spatial variation in habitat quality should select against dispersal. The effect of predation on the evolution of dispersal is currently not well-known: because predation can be variable in both space and time, it is not clear whether or when predation will promote dispersal within prey. Moreover, the evolution of prey dispersal affects strongly the encounter rate of predator and prey individuals, which greatly determines the ecological dynamics, and in turn changes the selection pressures for prey dispersal, in an eco-evolutionary feedback loop. When taken all together the effect of predation on prey dispersal is rather difficult to predict. We analyze a spatially explicit, individual-based predator-prey model and its mathematical approximation to investigate the evolution of prey dispersal. Competition and predation depend on local, rather than landscape-scale densities, and the spatial pattern of predation corresponds well to that of predators using restricted home ranges (e.g. central-place foragers). Analyses show the balance between the level of competition and predation pressure an individual is expected to experience determines whether prey should disperse or stay close to their parents and siblings, and more predation selects for less prey dispersal. Predators with smaller home ranges also select for less prey dispersal; more prey dispersal is favoured if predators have large home ranges, are very mobile, and/or are evenly distributed across the landscape.

The intensity of horizontal and vertical search in a diving forager: the harbour seal

BackgroundFree ranging foraging animals can vary their searching intensity in response to the profitability of the environment by modifying their movements. Marine diving animals forage in a three dimensional space and searching intensity can be varied in both the horizontal and vertical planes. Therefore understanding the relationship between the allocation of searching effort in these two spaces can provide a better understanding of searching strategies and a more robust identification of foraging behaviour from the multitude of foraging indices (FIs) available. We investigated the movement of a widespread marine coastal predator, the harbour seal (Phoca vitulina), and compared two sets of foraging indices reflecting searching intensity respectively in the horizontal plane (displacement speed, extensive vs. intensive movement types, residence time) and in the vertical dimension (time at the bottom of a dive). We then tested how several factors (dive depth, direction of the trip with respect to haul-out site, different predatory tactics, the presence of factors confounding the detection of foraging, and temporal resolution of the data) affected their relationships.ResultsOverall the indices only showed a very weak positive correlation across the two spaces. However controlling for various factors strengthened the relationships. Resting at sea, a behaviour intrinsically static in the horizontal plane, was found to be strongly negatively related to the time spent at the bottom of the dives, indirectly weakening the relationship between horizontal and vertical foraging indices. Predatory tactic (benthic vs. pelagic) was found to directly affect the relationship. In benthic (as opposed to pelagic) foraging a stronger positive relationship was found between vertical and horizontal indices.ConclusionsOur results indicated that movement responses, leading to an intensification of search, are similar in the two spaces (positive relationship), but additional factors need to be taken into account for this relationship to emerge. Foraging indices measuring residence in the horizontal plane tend to be inflated by resting events at sea, while vertical indices tend to distinguish mainly between periods of activity and inactivity, or of benthic and pelagic foraging. The simultaneous consideration of horizontal and vertical movements, as well as topographic information, allows additional behavioural states to be inferred, providing greater insight into the interpretation of foraging activity.

Lack of quantitative training among early-career ecologists: a survey of the problem and potential solutions

Proficiency in mathematics and statistics is essential to modern ecological science, yet few studies have assessed the level of quantitative training received by ecologists. To do so, we conducted an online survey. The 937 respondents were mostly early-career scientists who studied biology as undergraduates. We found a clear self-perceived lack of quantitative training: 75% were not satisfied with their understanding of mathematical models; 75% felt that the level of mathematics was “too low” in their ecology classes; 90% wanted more mathematics classes for ecologists; and 95% more statistics classes. Respondents thought that 30% of classes in ecology-related degrees should be focused on quantitative disciplines, which is likely higher than for most existing programs. The main suggestion to improve quantitative training was to relate theoretical and statistical modeling to applied ecological problems. Improving quantitative training will require dedicated, quantitative classes for ecology-related degrees that contain good mathematical and statistical practice.

Evolutionarily stable consumer home range size in relation to resource demography and consumer spatial organization

There is a large variation in home range size within species, yet few models relate that variation to demographic and life-history traits. We derive an approximate deterministic population dynamics model keeping track of spatial structure, via spatial moment equations, from an individual-based spatial consumer-resource model; where space-use of consumers resembles that of central place foragers. Using invasion analyses, we investigate how the evolutionarily stable home range size of the consumer depends on a number of ecological and behavioral traits of both the resource and the consumer. We show that any trait variation leading to a decreased overall resource production or an increased spatial segregation between consumer and resource acts to increase consumer home range size. In this way, we extend theoretical predictions on optimal territory size to a larger range of ecological scenarios where home ranges overlap and population dynamics feedbacks are possible. Consideration of spatial traits such as dispersal distances also generates new results: (1) consumer home range size decreases with increased resource dispersal distance, and (2) when consumer agonistic behavior is weak, more philopatric consumers have larger home ranges. Finally, our results emphasize the role of the spatial correlation between consumer and resource distributions in determining home range size, and suggest resource dispersion is less important.

Overcompensation and phase effects in a cyclic common vole population: between first and second‐order cycles

Population cycles in voles are often thought to be generated by one-year delayed density dependence on the annual population growth rate. In common voles, however, it has been suggested by Turchin (2003) that some populations exhibit first-order cycles, resulting from strong overcompensation (i.e. carrying capacity overshoots in peak years, with only an effect of the current year abundance on annual growth rates). We focus on a common vole (Microtus arvalis) population from western France that exhibits 3-year cycles. Several overcompensating nonlinear models for populations dynamics are fitted to the data, notably those of Hassell, and Maynard-Smith and Slatkin. Overcompensating direct density dependence (DD) provides a satisfactory description of winter crashes, and one-year delayed density dependence is not responsible for the crashes, thus these are not classical second-order cycles. A phase-driven modulation of direct density dependence maintains a low-phase, explaining why the cycles last three years instead of two. Our analyses suggest that some of this phase dependence can be expressed as one-year delayed DD, but phase dependence provides a better description. Hence, modelling suggests that cycles in this population are first-order cycles with a low phase after peaks, rather than fully second-order cycles. However, based on the popular log-linear second-order autoregressive model, we would conclude only that negative delayed density dependence exists. The additive structure of this model cannot show when delayed DD occurs (here, during lows rather than peaks). Our analyses thus call into question the automated use of second-order log-linear models, and suggests that more attention should be given to non-(log)linear models when studying cyclic populations. From a biological viewpoint, the fast crashes through overcompensation that we found suggest they might be caused by parasites or food rather than predators, though predators might have a role in maintaining the low phase and spatial synchrony.

When can environmental variability benefit population growth? Counterintuitive effects of nonlinearities in vital rates

Using models for unstructured populations, we investigate the effect of environmental variability on population growth when the environment affects vital rates through nonlinear functions. We focus here especially on interannual variation in food resources availability, for which sigmoid functions are relevant. Considering first unregulated populations in stochastic environments, we show that classic sigmoid annual growth rates cannot lead to positive effects of increased environmental variability on population growth. This is true even when the temporal average of food availability is low, and Jensens inequality predicts an increased arithmetic mean of the annual growth rate. The result is due to the log-concavity of many sigmoid (and other accelerating) functions, as convexity of the logarithm of the annual growth rate is needed for positive effects of variability to appear. Then, separating the effects of a food availability variable on reproduction and survival rates, we show that populations with less sensitive survival rate to food are more likely to benefit from food variability-as opposed to populations that have survival rates accelerating with food availability, which is rather counterintuitive given Jensens inequality. Again, this is explained by log-convexity properties of nonlinear functions. We further extend these results to regulated populations, in which similar positive effects of food variability can affect average population size. Positive variability effects seem however more likely to occur in regulated populations. Finally, we extend our results to stage-structured populations. We connect to the previous work showing positive effects of environmental variability with matrix models, and show that these effects are well captured by simpler unstructured models.