Butterfly abundance in a warming climate: patterns in space and time are not congruent

We present a model of butterfly abundance on transects in England. The model indicates a significant role for climate, but the direction of association is counter to expectation: butterfly population density is higher on sites with a cooler climate. However, the effect is highly heterogeneous, with one in five species displaying a net positive association. We use this model to project the population-level effects of climate warming for the year 2080, using a medium emissions scenario. The results suggest that most populations and species will decline markedly, but that the total number of butterflies will increase as communities become dominated by a few common species. In particular, Maniola jurtina is predicted to make up nearly half of all butterflies on UK Butterfly Monitoring Scheme (UKBMS) transects by 2080. These results contradict the accepted wisdom that most insect populations will grow as the climate becomes warmer. Indeed, our predictions contrast strongly with those derived from inter-annual variation in abundance, emphasizing that we lack a mechanistic understanding about the factors driving butterfly population dynamics over large spatial and temporal scales. Our study underscores the difficulty of predicting future population trends and reveals the naivety of simple space-for-time substitutions, which our projections share with species distribution modelling

Distribution and conservation status of two endemic Tasmanian crustaceans, Allanaspides hickmani and Allanaspides helonomus (Syncarida: anaspididae)

Extant representatives of the ancient crustacean family Anaspididae (Syncarida) are restricted to the island state of Tasmania, Australia. The most recently described species, Allanaspides helonomus Swain, Wilson, Hickman & Ong, 1970 and A. hickmani Swain, Wilson & Ong, 1971, were described from buttongrass moorland in southwestern Tasmania. Large areas of their habitat were subsequently inundated for hydroelectric power generation. We surveyed the extant distributions of A. hickmani and A. helonomus, assessed potential threats to the species, and reviewed their conservation status against state, national and international criteria. A. hickmani is restricted to a single catchment and occurs in a very small number (<10) of highly fragmented subpopulations on the margins of two hydroelectric impoundments. A. helonomus has a substantially larger range and Area of Occupancy spanning three separate catchments, and is now known to also occur in the Lake Pedder hydro-electric impoundment. Both species are listed as vulnerable on the IUCN Red List. This listing appears warranted for A. hickmani based on its restricted Area of Occupancy and the small number of extant subpopulations. However, A. helonomus no longer appears to fulfil the IUCN criterion for vulnerable. Neither species appears to be eligible for listing as vulnerable under the Australian Environment Protection and Biodiversity Conservation Act 1999 and the Tasmanian Threatened Species Protection Act 1995. The current listing of A. hickmani as rare under the Tasmanian Threatened Species Protection Act 1995 appears warranted as extant subpopulations may be at risk of extinction. The level of risk for A. helonomus is considerably lower than is the case for A. hickmani, and A. helonomus may not be eligible for listing as rare. The potential impacts of climate change on buttongrass moorland may present the most serious long-term threat to the two Allanaspides species

A generalised abundance index for seasonal invertebrates

At a time of climate change and major loss of biodiversity, it is important to have efficient tools for monitoring populations. In this context, animal abundance indices play an important role. In producing indices for invertebrates, it is important to account for variation in counts within seasons. Two new methods for describing seasonal variation in invertebrate counts have recently been proposed; one is nonparametric, using generalized additive models, and the other is parametric, based on stopover models. We present a novel generalized abundance index which encompasses both parametric and nonparametric approaches. It is extremely efficient to compute this index due to the use of concentrated likelihood techniques. This has particular relevance for the analysis of data from long-term extensive monitoring schemes with records for many species and sites, for which existing modeling techniques can be prohibitively time consuming. Performance of the index is demonstrated by several applications to UK Butterfly Monitoring Scheme data. We demonstrate the potential for new insights into both phenology and spatial variation in seasonal patterns from parametric modeling and the incorporation of covariate dependence, which is relevant for both monitoring and conservation. Associated R code is available on the journal website

Dynamic models for longitudinal butterfly data

There has been recent interest in devising stochastic models for seasonal insects, which respond rapidly to climate change. Fitted to count data, these models are used to construct indices of abundance, which guide conservation and management. We build upon Dennis et al. (2014, under review) to produce dynamic models, which provide succinct descriptions of data from all years simultaneously. They produce estimates of key life-history parameters such as annual productivity and survival. Analyses for univoltine species, with only one generation each year, extend to bivoltine species, with two annual broods. In the latter case we estimate the productivities of each generation separately, and also devise extended indices which indicate the contributions made from different generations. We demonstrate the performance of the models using count data for UK butterfly species, and compare with current procedures which use generalized additive models. We may incor- orate relevant covariates within the model, and illustrate using northing and measures of temperature. Consistent patterns are demonstrated for multiple species. This generates a variety of hypotheses for further investigation, which have the potential to illuminate features of butterfly phenology and demography which are at present poorly understood

Latitudinal gradients in butterfly population variability are influenced by landscape heterogeneity

The variability of populations over time is positively associated with their risk of local extinction. Previous work has shown that populations at the high-latitude boundary of species’ ranges show higher inter-annual variability, consistent with increased sensitivity and exposure to adverse climatic conditions. However, patterns of population variability at both high- and low-latitude species range boundaries have not yet been concurrently examined. Here, we assess the inter-annual population variability of 28 butterfly species between 1994 and 2009 at 351 and 18 sites in the United Kingdom and Catalonia, Spain, respectively. Local population variability is examined with respect to the position of the species’ bioclimatic envelopes (i.e. whether the population falls within areas of the ‘core’ climatic suitability or is a climatically ‘marginal’ population), and in relation to local landscape heterogeneity, which may influence these range location – population dynamic relationships. We found that butterfly species consistently show latitudinal gradients in population variability, with increased variability in the more northerly UK. This pattern is even more marked for southerly distributed species with ‘marginal’ climatic suitability in the UK but ‘core’ climatic suitability in Catalonia. In addition, local landscape heterogeneity did influence these range location – population dynamic relationships. Habitat heterogeneity was associated with dampened population dynamics, especially for populations in the UK. Our results suggest that promoting habitat heterogeneity may promote the persistence of populations at high-latitude range boundaries, which may potentially aid northwards expansion under climate warming. We did not find evidence that population variability increases towards southern range boundaries. Sample sizes for this region were low, but there was tentative evidence, in line with previous ecological theory, that local landscape heterogeneity may promote persistence in these retracting low-latitude range boundary populations

Entangled Polymer Rings in 2D and Confinement

The statistical mechanics of polymer loops entangled in the two-dimensional array of randomly distributed obstacles of infinite length is discussed. The area of the loop projected to the plane perpendicular to the obstacles is used as a collective variable in order to re-express a (mean field) effective theory for the polymer conformation. It is explicitly shown that the loop undergoes a collapse transition to a randomly branched polymer with $R\propto lN^\frac{1}{4}$.Comment: 17 pages of Latex, 1 ps figure now available upon request, accepted for J.Phys.A:Math.Ge

Topological interactions in systems of mutually interlinked polymer rings

The topological interaction arising in interlinked polymeric rings such as DNA catenanes is considered. More specifically, the free energy for a pair of linked random walk rings is derived where the distance $R$ between two segments each of which is part of a different ring is kept constant. The topology conservation is imposed by the Gauss invariant. A previous approach (M.Otto, T.A. Vilgis, Phys.Rev.Lett. {\bf 80}, 881 (1998)) to the problem is refined in several ways. It is confirmed, that asymptotically, i.e. for large $R\gg R_G$ where $R_G$ is average size of single random walk ring, the effective topological interaction (free energy) scales $\propto R^4$.Comment: 16 pages, 3 figur

Predicting resilience of ecosystem functioning from co‐varying species' responses to environmental change

Understanding how environmental change affects ecosystem function delivery is of primary importance for fundamental and applied ecology. Current approaches focus on single environmental driver effects on communities, mediated by individual response traits. Data limitations present constraints in scaling up this approach to predict the impacts of multivariate environmental change on ecosystem functioning. We present a more holistic approach to determine ecosystem function resilience, using long‐term monitoring data to analyze the aggregate impact of multiple historic environmental drivers on species' population dynamics. By assessing covariation in population dynamics between pairs of species, we identify which species respond most synchronously to environmental change and allocate species into “response guilds.” We then use “production functions” combining trait data to estimate the relative roles of species to ecosystem functions. We quantify the correlation between response guilds and production functions, assessing the resilience of ecosystem functioning to environmental change, with asynchronous dynamics of species in the same functional guild expected to lead to more stable ecosystem functioning. Testing this method using data for butterflies collected over four decades in the United Kingdom, we find three ecosystem functions (resource provisioning, wildflower pollination, and aesthetic cultural value) appear relatively robust, with functionally important species dispersed across response guilds, suggesting more stable ecosystem functioning. Additionally, by relating genetic distances to response guilds we assess the heritability of responses to environmental change. Our results suggest it may be feasible to infer population responses of butterflies to environmental change based on phylogeny—a useful insight for conservation management of rare species with limited population monitoring data. Our approach holds promise for overcoming the impasse in predicting the responses of ecosystem functions to environmental change. Quantifying co‐varying species' responses to multivariate environmental change should enable us to significantly advance our predictions of ecosystem function resilience and enable proactive ecosystem management

Evaluating public involvement in research design and grant development: Using a qualitative document analysis method to analyse an award scheme for researchers

Background A regional Research Design Service, funded by the National Institute for Health Research, introduced a small grant in 2008, to support public involvement (often known as patient and public involvement [PPI]) activities during the development of applications for research funding. Successful applicants are requested to submit a report detailing how the grant money was used, including a description of the aims and outcomes of the public involvement activities. The purpose of this study was to analyse the content of these reports. We aimed to find out what researcher views and experiences of public involvement activities were, and what lessons might be learned. Methods We used an innovative method of data analysis, drawing on group participatory approaches, qualitative content analysis, and Framework Analysis to sort and label the content of the reports. We developed a framework of categories and sub-categories (or themes and sub-themes) from this process. Results Twenty five documents were analysed. Four main themes were identified in the data: the added value of public involvement; planning and designing involvement; the role of public members; and valuing public member contributions. Within these themes, sub-themes related to the timing of involvement (prior to the research study/intended during the research study), and also specific benefits of public involvement such as: validating ideas; ensuring appropriate outcomes; ensuring the acceptability of data collection methods/tools and advice regarding research processes. Other sub-themes related to: finding and approaching public members; timing of events; training/support; the format of sessions; setting up public involvement panels: use of public contributors in analysis and interpretation of data; and using public members to assist with dissemination and translation into practice. Conclusions The analysis of reports submitted by researchers following involvement events provides evidence of the value of public involvement during the development of applications for research funding, and details a method for involving members of the public in data analysis which could be of value to other researchers The findings of the analysis indicate recognition amongst researchers of the variety in potential roles for public members in research, and also an acknowledgement of how involvement adds value to studies