Rethinking the Political Economy of Decentralization: How Elections and Parties Shape the Provision of Local Public Goods

Decentralization is among the most important global trends of the new century, yet there is still no consensus on how to design political institutions to realize its benefits. In this paper, we investigate the political conditions under which decentralization will improve the delivery of public goods. We begin by incorporating insights from political science and economics into a rigorous and formal extension of the “decentralization theorem”. Our extension assumes inter-jurisdictional spillovers and suggests that the interaction of democratic decentralization (popularly elected sub-national governments) and party centralization (the power of national party leaders over subnational office-seekers) will produce the best outcomes for public service delivery. To test this argument empirically, we make use of a new dataset of sub-national political institutions created for this project. Our analyses, which allow us to examine educational outcomes in more than 125 countries across more than 25 years, provide support for our theoretical expectations

Using neutral cline decay to estimate contemporary dispersal: a generic tool and its application to a major crop pathogen

Dispersal is a key parameter of adaptation, invasion and persistence. Yet standard population genetics inference methods hardly distinguish it from drift and many species cannot be studied by direct mark-recapture methods. Here, we introduce a method using rates of change in cline shapes for neutral markers to estimate contemporary dispersal. We apply it to the devastating banana pest Mycosphaerella fijiensis, a wind-dispersed fungus for which a secondary contact zone had previously been detected using landscape genetics tools. By tracking the spatio-temporal frequency change of 15 microsatellite markers, we find that σ, the standard deviation of parent–offspring dispersal distances, is 1.2 km/generation1/2. The analysis is further shown robust to a large range of dispersal kernels. We conclude that combining landscape genetics approaches to detect breaks in allelic frequencies with analyses of changes in neutral genetic clines offers a powerful way to obtain ecologically relevant estimates of dispersal in many species

Eco-evolutionary dynamics in fragmented landscapes

Peer reviewedPostprin

Where is the optimum? Predicting the variation of selection along climatic gradients and the adaptive value of plasticity. A case study on tree phenology

International audienceMany theoretical models predict when genetic evolution and phenotypic plasticity allow adaptation to changing environmental conditions. These models generally assume stabilizing selection around some optimal phenotype. We however often ignore how optimal phenotypes change with the environment, which limit our understanding of the adaptive value of phenotypic plasticity. Here, we propose an approach based on our knowledge of the causal relationships between climate, adaptive traits, and fitness to further these questions. This approach relies on a sensitivity analysis of the process-based model Phenofit, which mathematically formalizes these causal relationships, to predict fitness landscapes and optimal budburst dates along elevation gradients in three major European tree species. Variation in the overall shape of the fitness landscape and resulting directional selection gradients were found to be mainly driven by temperature variation. The optimal budburst date was delayed with elevation, while the range of dates allowing high fitness narrowed and the maximal fitness at the optimum decreased. We also found that the plasticity of the budburst date should allow tracking the spatial variation in the optimal date, but with variable mismatch depending on the species, ranging from negligible mismatch in fir, moderate in beech, to large in oak. Phenotypic plasticity would therefore be more adaptive in fir and beech than in oak. In all species, we predicted stronger directional selection for earlier budburst date at higher elevation. The weak selection on budburst date in fir should result in the evolution of negligible genetic divergence, while beech and oak would evolve counter-gradient variation, where genetic and environmental effects are in opposite directions. Our study suggests that theoretical models should consider how whole fitness landscapes change with the environment. The approach introduced here has the potential to be developed for other traits and species to explore how populations will adapt to climate change

Eco-evolutionary dynamics of dispersal in spatially heterogeneous environments

Evolutionary changes in natural populations are often so fast that the evolutionary dynamics may influence ecological population dynamics and vice versa. Here we construct an eco-evolutionary model for dispersal by combining a stochastic patch occupancy metapopulation model with a model for changes in the frequency of fast-dispersing individuals in local populations. We test the model using data on allelic variation in the gene phosphoglucose isomerase (Pgi), which is strongly associated with dispersal rate in the Glanville fritillary butterfly. Population-specific measures of immigration and extinction rates and the frequency of fast-dispersing individuals among the immigrants explained 40% of spatial variation in Pgi allele frequency among 97 local populations. The model clarifies the roles of founder events and gene flow in dispersal evolution and resolves a controversy in the literature about the consequences of habitat loss and fragmentation on the evolution of dispersal

Ambulatory dispersal in Tetranychus urticae: an artificial selection experiment on propensity to disperse yields no response

Dispersal to new hosts is an important process for an invasive herbivore, such as the two-spotted spider mite. A recent study, using artificial selection experiments, has suggested that genetic variation and genetic trade-offs are present for propensity to disperse in this species. However, due to the experimental setup alternative explanations for the response to selection could not be ruled out. Using an altered setup, we investigated whether the propensity for ambulatory dispersal differs genetically between individuals and whether genetic correlations with life-history traits exist. Upward and downward selection on propensity to leave the colony was performed for seven generations in four replicate artificial selection experiments and the results were compared to control lines. No consistent responses to selection were found and no significant effect on life-history traits (oviposition rate, juvenile survival, development rate and number of adult offspring) or sex ratio was present across the replicates. The data suggest that our base population of spider mites harbours at best a low amount of additive genetic variation for this behaviour

Darwin’s wind hypothesis: does it work for plant dispersal in fragmented habitats?

Using the wind-dispersed plant Mycelis muralis, we examined how landscape fragmentation affects variation in seed traits contributing to dispersal. Inverse terminal velocity (Vt−1) of field-collected achenes was used as a proxy for individual seed dispersal ability. We related this measure to different metrics of landscape connectivity, at two spatial scales: in a detailed analysis of eight landscapes in Spain and along a latitudinal gradient using 29 landscapes across three European regions. In the highly patchy Spanish landscapes, seed Vt−1 increased significantly with increasing connectivity. A common garden experiment suggested that differences in Vt−1 may be in part genetically based. The Vt−1 was also found to increase with landscape occupancy, a coarser measure of connectivity, on a much broader (European) scale. Finally, Vt−1 was found to increase along a south–north latitudinal gradient. Our results for M. muralis are consistent with ‘Darwin’s wind dispersal hypothesis’ that high cost of dispersal may select for lower dispersal ability in fragmented landscapes, as well as with the ‘leading edge hypothesis’ that most recently colonized populations harbour more dispersive phenotypes.

Evolution of predator dispersal in relation to spatio-temporal prey dynamics : how not to get stuck in the wrong place!

Peer reviewedPublisher PD

Influence of learning on range expansion and adaptation to novel habitats

Learning has been postulated to ‘drive’ evolution, but its influence on adaptive evolution in heterogeneous environments has not been formally examined. We used a spatially explicit individual-based model to study the effect of learning on the expansion and adaptation of a species to a novel habitat. Fitness was mediated by a behavioural trait (resource preference), which in turn was determined by both the genotype and learning. Our findings indicate that learning substantially increases the range of parameters under which the species expands and adapts to the novel habitat, particularly if the two habitats are separated by a sharp ecotone (rather than a gradient). However, for a broad range of parameters, learning reduces the degree of genetically-based local adaptation following the expansion and facilitates maintenance of genetic variation within local populations. Thus, in heterogeneous environments learning may facilitate evolutionary range expansions and maintenance of the potential of local populations to respond to subsequent environmental changes

Scale-free memory model for multiagent reinforcement learning. Mean field approximation and rock-paper-scissors dynamics

A continuous time model for multiagent systems governed by reinforcement learning with scale-free memory is developed. The agents are assumed to act independently of one another in optimizing their choice of possible actions via trial-and-error search. To gain awareness about the action value the agents accumulate in their memory the rewards obtained from taking a specific action at each moment of time. The contribution of the rewards in the past to the agent current perception of action value is described by an integral operator with a power-law kernel. Finally a fractional differential equation governing the system dynamics is obtained. The agents are considered to interact with one another implicitly via the reward of one agent depending on the choice of the other agents. The pairwise interaction model is adopted to describe this effect. As a specific example of systems with non-transitive interactions, a two agent and three agent systems of the rock-paper-scissors type are analyzed in detail, including the stability analysis and numerical simulation. Scale-free memory is demonstrated to cause complex dynamics of the systems at hand. In particular, it is shown that there can be simultaneously two modes of the system instability undergoing subcritical and supercritical bifurcation, with the latter one exhibiting anomalous oscillations with the amplitude and period growing with time. Besides, the instability onset via this supercritical mode may be regarded as "altruism self-organization". For the three agent system the instability dynamics is found to be rather irregular and can be composed of alternate fragments of oscillations different in their properties.Comment: 17 pages, 7 figur