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Most people live in urban environments and there is a need to produce abundance indices to assist policy and management of urban greenspaces and gardens. While regional indices are produced, with the exception of birds, studies of the differences between urban and rural areas are rare. We explore these differences for UK butterflies, with the intention to describe changes that are relevant to people living in urban areas, in order to better connect people with nature in support of conservation, provide a measure relevant to human well-being, and assess the biodiversity status of the urban environment.\ud \ud Transects walked under the UK Butterfly Monitoring Scheme are classified as urban or rural, using a classification for urban morphological zones. We use models from the Generalised Abundance Index family to produce urban and rural indices of relative abundance for UK butterfly species. Composite indices are constructed for various subsets of species. For univoltine and bivoltine species, where we are able to fit phenomenological models, we estimate measures of phenology and identify urban/rural differences. Trends in relative abundance over the period 1995–2014 are more negative in urban areas compared to rural areas for 25 out of 28 species. For the composite indices, all trends are negative, and they are significantly more negative for urban areas than for rural areas. Analysis of phenological parameters shows butterflies tend to emerge earlier in urban than in rural areas. In addition, some fly longer in urban than in rural areas, whereas in other cases the opposite is the case, and hypotheses are proposed to account for these features.\ud \ud Investigating new urban/rural indicators has revealed national declines that are stronger for urban areas. For continued monitoring, there is a need for an urban butterfly indicator, and for this to be evaluated and reported annually. We explain how this may be interpreted, and the relevance for other monitoring schemes. The results of this paper, including the phenological findings, shed new light on the potentially deleterious effects of urbanisation and climate change, which require suitable monitoring and reporting to support policy and management, for example of urban greenspaces and gardens.

Appropriate large-scale citizen-science data present important new opportunities for biodiversity modelling, due in part to the wide spatial coverage of information. Recently proposed occupancy modelling approaches naturally incorporate random effects in order to account for annual variation in the composition of sites surveyed. In turn this leads to Bayesian analysis and model fitting, which are typically extremely time consuming. Motivated by presence-only records of occurrence from the UK Butterflies for the New Millennium data base, we present an alternative approach, in which site variation is described in a standard way through logistic regression on relevant environmental covariates. This allows efficient occupancy model-fitting using classical inference, which is easily achieved using standard computers. This is especially important when models need to be fitted each year, typically for many different species, as with British butterflies for example. Using both real and simulated data we demonstrate that the two approaches, with and without random effects, can result in similar conclusions regarding trends. There are many advantages to classical model-fitting, including the ability to compare a range of alternative models, identify appropriate covariates and assess model fit, using standard tools of maximum likelihood. In addition, modelling in terms of covariates provides opportunities for understanding the ecological processes that are in operation. We show that there is even greater potential; the classical approach allows us to construct regional indices simply, which indicate how changes in occupancy typically vary over a species’ range. In addition we are also able to construct dynamic occupancy maps, which provide a novel, modern tool for examining temporal changes in species distribution. These new developments may be applied to a wide range of taxa, and are valuable at a time of climate change. They also have the potential to motivate citizen scientists.

1. Abundance indices generated by the UK Butterfly Monitoring Scheme (UKBMS) have been influential in informing our understanding of environmental change and highlighting UK conservation priorities. Here, we critically evaluate the standard ‘Pollard Walk’ methodology employed by the UKBMS. 2. We consider the systematic sampling biases among different butterfly species and biotopes using distance sampling. We collected over 5000 observations on 17 species using distance sampling at 13 study sites in England and Wales. We fitted detection functions to explore variation in detectability among species and sites. 3. Our results suggest that around one-third of individual butterflies in the Pollard Walk box were missed. However, detectability varies markedly among species and sites. We provide the first species-specific estimates of detectability for converting Pollard Walk data into population densities. A few species show no drop off in detectability and most require only a modest correction factor, but for the least detectable species, we estimate that 3/4 of individuals are not recorded. 4. Much of the variation among sites is explained by substantially higher detectability among sites in England than in Wales, which had different recorders. Biological traits have only limited explanatory power in distinguishing detectable vs undetectable species. 5. The variation in detectability is small compared with the variation in true abundance, such that population density estimates from the Pollard Walk are highly correlated with those derived from distance sampling. 6. These results are used to evaluate the robustness of the Pollard Walk for comparisons of abundance across species, across sites and over time. UKBMS data provide a good reflection of relative abundance for most species and of large-scale trends in abundance. We also consider the practicalities of applying distance sampling to butterfly monitoring in general. Distance sampling is a valuable tool for quantifying bias and imprecision and has a role in surveying species of conservation concern, but is not viable as a wholesale replacement for simpler methods for large-scale monitoring of multispecies butterfly communities by volunteer recorders.