Synchrony of butterfly populations across species' geographic ranges

Population synchrony indicates functional connectivity in a threatened sedentary butterfly

Dispersal is a key influence on species' persistence, particularly in the context of habitat fragmentation and environmental change. Previously, residual population synchrony has been demonstrated to be an effective proxy for dispersal in mobile butterflies (Powney et al. 2012). Here, we highlight the utility and limitations of population synchrony as an indicator of functional connectivity and persistence, at a range of spatial scales, in a specialist, sedentary butterfly. While at the local scale, population synchrony is likely indicative of dispersal in the pearl-bordered fritillary, Boloria euphrosyne, over larger scales, habitat is likely to influence population dynamics. Although declines in local-scale synchrony conformed to typical movement in this species, synchrony showed no significant trend with distance when studied at larger (between-site) scales. By focusing on specific site comparisons, we draw the conclusion that heterogeneity in habitat successional stage drives asynchrony between sites at larger distances and is, therefore, likely to be a more important driver of population dynamics over large distances than dispersal. Within-site assessments of synchrony highlight differences in dispersal based on habitat type, with movement shown to be most inhibited between transect sections with contrasting habitat permeability. While synchrony has implications for metapopulation stability and extinction risk, no significant difference was found in average site synchrony between sites that had gone extinct during the study period and those remaining occupied. We demonstrate that population synchrony may be used to assess local-scale movement between sedentary populations, as well as to understand barriers to dispersal and guide conservation management.

Climatic Niche Model for Overwintering Monarch Butterflies in a Topographically Complex Region of California

We use climatic conditions that are associated with known monarch butterfly overwintering groves in California to build a Maxent model, and focus on the fine scale probability of overwintering grove occurrence in a topographically complex region of the state (Santa Barbara County). Grove locations are known from recent and historical surveys and a long-term citizen science database. The climatic niche model performs well, predicting that overwintering habitat is most likely to occur along the coast and at low elevations, as shown by empirical data. We then use climatic variables in conjunction with climate change scenarios to model the future location of overwintering habitat, and find a substantial shift in the predicted distribution. Under a plausible scenario, the probability of occurrence of overwintering habitat directly reflects elevation, with coastal regions having a reduced probability relative to today, and higher elevation sites increasing in probability. Under a more extreme scenario, high probability sites are only located along ridgelines and in mountaintop regions of the county. This predicted shift in distribution is likely to have management implications, as sites that currently lack monarchs may become critical to conservation in the future. Our results suggest that estimating the size of the western overwintering population in the future will be problematic, unless annual counts compensate for a shift in the distribution and a potential change in the number and location of occupied sites.

Synchronous population dynamics in California butterflies explained by climatic forcing

A long-standing challenge for population biology has been to understand why some species are characterized by populations that fluctuate in size independently, while populations of other species fluctuate synchronously across space. The effects of climatic variation and dispersal have been invoked to explain synchronous population dynamics, however an understanding of the relative influence of these drivers in natural populations is lacking. Here we compare support for dispersal- versus climate-driven models of interspecific variation in synchrony using 27 years of observations of 65 butterfly species at 10 sites spanning 2750 m of elevation in Northern California. The degree of spatial synchrony exhibited by each butterfly species was used as a response in a unique approach that allowed us to investigate whether interspecific variation in response to climate or dispersal propensity was most predictive of interspecific variation in synchrony. We report that variation in sensitivity to climate explained 50% of interspecific variation in synchrony, whereas variation in dispersal propensity explained 23%. Sensitivity to the El Niño Southern Oscillation, a primary driver of regional climate, was the best predictor of synchrony. Combining sensitivity to climate and dispersal propensity into a single model did not greatly increase model performance, confirming the primacy of climatic sensitivity for driving spatial synchrony in butterflies. Finally, we uncovered a relationship between spatial synchrony and population decline that is consistent with theory, but small in magnitude, which suggests that the degree to which populations fluctuate in synchrony is of limited use for understanding the ongoing decline of the Northern California butterfly fauna.

Dynamic Models for Longitudinal Butterfly Data

We present models which provide succinct descriptions of longitudinal seasonal insect count data. This approach produces, for the first time, estimates of the key parameters of brood productivities. It may be applied to univoltine and bivoltine species. For the latter, the productivities of each brood are estimated separately, which results in new indices indicating the contributions from different generations. The models are based on discrete distributions, with expectations that reflect the underlying nature of seasonal data. Productivities are included in a deterministic, auto-regressive manner, making the data from each brood a function of those in the previous brood. A concentrated likelihood results in appreciable efficiency gains. Both phenomenological and mechanistic models are used, including weather and site-specific covariates. Illustrations are provided using data from the UK Butterfly Monitoring Scheme, however the approach is perfectly general. Consistent associations are found when estimates of productivity are regressed on northing and temperature. For instance, for univoltine species productivity is usually lower following milder winters, and mean emergence times of adults for all species have become earlier over time, due to climate change. The predictions of fitted dynamic models have the potential to improve the understanding of fundamental demographic processes. This is important for insects such as UK butterflies, many species of which are in decline. Supplementary materials for this article are available online.

Population fluctuations and synchrony of grassland butterflies in relation to species traits

Population fluctuations and synchrony influence population persistence; species with larger fluctuations and more synchronised population fluctuations face higher extinction risks. Here, we analyse the effect of diet specialisation, mobility, length of the flight period, and distance to the northern edge of the species’ distribution in relation to between-year population fluctuations and synchrony of butterfly species. All butterfly species associated with grasslands were surveyed over five successive years at 19 grassland sites in a forest-dominated landscape (50 km²) in southern Sweden. At both the local and regional level, we found larger population fluctuations in species with longer flight periods. Population fluctuations were more synchronous among localities in diet specialists. Species with a long flight period might move more to track nectar resources compared to species with shorter flight period, and if nectar sources vary widely between years and localities it may explain that population fluctuations increase with increasing flight length. Diet generalists can use different resources (in this case host plants) at different localities and this can explain the lower synchrony in population fluctuations among generalist species. Higher degree of synchrony is one possible explanation for the higher extinction risks that have been observed for more specialised species. Therefore, diet specialists are more often threatened and require more conservation efforts than generalists.

Geographical variation in the spatial synchrony of a forest-defoliating insect: isolation of environmental and spatial drivers

Despite the pervasiveness of spatial synchrony of population fluctuations in virtually every taxon, it remains difficult to disentangle its underlying mechanisms, such as environmental perturbations and dispersal. We used multiple regression of distance matrices (MRMs) to statistically partition the importance of several factors potentially synchronizing the dynamics of the gypsy moth, an invasive species in North America, exhibiting outbreaks that are partially synchronized over long distances (approx. 900 km). The factors considered in the MRM were synchrony in weather conditions, spatial proximity and forest-type similarity. We found that the most likely driver of outbreak synchrony is synchronous precipitation. Proximity played no apparent role in influencing outbreak synchrony after accounting for precipitation, suggesting dispersal does not drive outbreak synchrony. Because a previous modelling study indicated weather might indirectly synchronize outbreaks through synchronization of oak masting and generalist predators that feed upon acorns, we also examined the influence of weather and proximity on synchrony of acorn production. As we found for outbreak synchrony, synchrony in oak masting increased with synchrony in precipitation, though it also increased with proximity. We conclude that precipitation could synchronize gypsy moth populations directly, as in a Moran effect, or indirectly, through effects on oak masting, generalist predators or diseases.

Species-area relationships are controlled by species traits

The species-area relationship (SAR) is one of the most thoroughly investigated empirical relationships in ecology. Two theories have been proposed to explain SARs: classical island biogeography theory and niche theory. Classical island biogeography theory considers the processes of persistence, extinction, and colonization, whereas niche theory focuses on species requirements, such as habitat and resource use. Recent studies have called for the unification of these two theories to better explain the underlying mechanisms that generates SARs. In this context, species traits that can be related to each theory seem promising. Here we analyzed the SARs of butterfly and moth assemblages on islands differing in size and isolation. We tested whether species traits modify the SAR and the response to isolation. In addition to the expected overall effects on the area, traits related to each of the two theories increased the model fit, from 69% up to 90%. Steeper slopes have been shown to have a particularly higher sensitivity to area, which was indicated by species with restricted range (slope  = 0.82), narrow dietary niche (slope  = 0.59), low abundance (slope  = 0.52), and low reproductive potential (slope  = 0.51). We concluded that considering species traits by analyzing SARs yields considerable potential for unifying island biogeography theory and niche theory, and that the systematic and predictable effects observed when considering traits can help to guide conservation and management actions.