Biology subjects

Robinson, R. A.

Publications and source records attributed to Robinson, R. A..

6 recordsLinked to original sources

bioRxiv2026

Repeated and widespread introduction of a mosquito-borne virus, but wildlife impact remains localised in urban area

Mosquito-borne viruses are emerging in new regions with increasing regularity. Shifting climatic envelopes, especially in temperate regions, and altered enzootic cycles are changing likelihoods of persistence, meaning new approaches are required to predict and monitor establishment. Usutu virus (USUV) is a mosquito-borne viral zoonosis, which was first recorded in the United Kingdom in wild birds and mosquitoes in 2020. By developing a multidisciplinary approach, incorporating enhanced passive and active surveillance of wild birds, we discovered previously unrecorded introductions and identified USUV persistence and geographic expansion. By combining molecular and serological testing with citizen science derived datasets, we show an associated marked decline in a common, widespread, and highly susceptible host species (Eurasian Blackbird, Turdus merula). However, the clearest continuous signal of host population decline remains localised to a large urban area, despite the much wider virus distribution. This may be a consequence of an urban heat island effect and associated increase in length of the mosquito active season. Our results indicate that the establishment and impact of future mosquito-borne pathogens in temperate zones, anticipated under climate change, may first be most apparent in urban areas. Consequently, enhanced surveillance efforts in urban areas could provide an efficient mechanism for detecting novel pathogen emergence. The epidemiology of emerging vector-borne diseases, especially in temperate areas, depends on the interplay between climate, land-use and available hosts; therefore, considering each in isolation will not be sufficient to reliably inform surveillance or response planning.

ecology↗

bioRxiv2025

Detection of West Nile Virus via Retrospective Mosquito Arbovirus Surveillance in the United Kingdom

In March 2025, as part of on-going enhanced surveillance for mosquito-borne Orthoflaviviruses, West Nile virus (WNV) RNA was detected in two pools of female Aedes vexans collected in July 2023 in Nottinghamshire, England. Viral RNA detection was achieved via reverse transcription-qPCR. Sequencing and subsequent phylogenetic analysis of a 402 bp fragment indicated that the detections clustered with WNV lineage 1a. The exact origin of this virus remains unclear, but this finding indicates a historic WNV presence in the United Kingdom (UK). Surveillance has not provided evidence of further viral transmission to date.

molecular biology↗

bioRxiv2023

Estimating the distribution of reed Phragmites australis in Britain demonstrates challenges of remotely sensing rare land cover types at large spatial scales

Reed Phragmites australis is important for biodiversity, for ecosystem services, and as a resource for humans. Already one of the mostly widely distributed wetland plants globally, reed has recently expanded outside of its native range, modifying ecosystems. However, like most wetland plant communities, reedbed has rarely been mapped at large geographical scales, restricting the information available to ecologists and resource managers. Using Sentinel-2 data and machine learning in open-source software, we produce the first remotely-sensed reedbed map of Britain. A random forest was trained on 79.2 ha of reedbed and 2,719.2 ha of non-reedbed land cover, using free online imagery. Accuracy was high within the training area (AUC > 0.998); however, field validation accuracy was much lower (AUC = 0.671), with many false positives (commission error of 93.4%). A similar workflow carried out in Google Earth Engine, using nearly an order of magnitude more images, gave a lower commission error but a disproportionately higher omission error. Due to the classification error, our map is more useful for a non-spatial estimate of the overall reedbed extent in Britain, rather than for the spatial location of reedbeds in Britain. Using the known commission and omission error, we estimate that in 2015 - 2017 c. 7800 ha of Britain was reedbed. Our study highlights the issues that present enduring barriers to accurate land cover classification at large spatial scales, perhaps suggesting fruitful areas for technological innovation. Even with a big data approach and even if technological issues are resolved, ecological factors such as confusion land cover types and geographical variation in temporal reflectance function will probably continue to impose upper limits on the size of area for which land cover can be classified accurately, and therefore on the utility of remote sensing to resource managers.

ecology↗

bioRxiv2021

Standardised empirical dispersal kernels emphasise the pervasiveness of long-distance dispersal in European birds

O_LIDispersal is a key life-history trait for most species and essential to ensure connectivity and gene flow between populations and facilitate population viability in variable environments. Despite the increasing importance of range shifts due to global change, dispersal has proved difficult to quantify, limiting empirical understanding of this phenotypic trait and wider synthesis. C_LIO_LIHere we aim to estimate and compare empirical dispersal kernels for European breeding birds considering average dispersal, natal (before first breeding) and breeding dispersal (between subsequent breeding attempts), and test whether different dispersal properties are phylogenetically conserved. C_LIO_LIWe standardised and analysed data from an extensive volunteer-based bird ring-recoveries database in Europe (EURING) by accounting for biases related to different censoring thresholds in reporting between countries and to migratory movements. Then, we fitted four widely used probability density functions in a Bayesian framework to compare and provide the best statistical descriptions of the average, the natal and the breeding dispersal kernels for each bird species. C_LIO_LIThe dispersal movements of the 234 European bird species analysed were statistically best explained by heavy-tailed kernels, meaning that while most individuals disperse over short distances, long-distance dispersal is a feature in almost all bird species. The overall phylogenetic signal in both median and long dispersal distances was low (Pagels {lambda} < 0.40), implying a high degree of taxonomic generality in our findings. As expected in birds, natal dispersal was 5 Km greater as an average than breeding dispersal for most species (88% species analysed). C_LIO_LIOur comprehensive analysis of empirical kernels indicates that long-distance dispersal is common among European breeding bird species and across life stages. The dispersal estimates offer a first guide to selecting appropriate dispersal kernels in range expansion studies and provide new avenues to improve our understanding of the mechanisms and rules underlying dispersal events. C_LI

ecology↗

bioRxiv2021

Integrating structured and unstructured citizen science data to improve wildlife population monitoring

Accurate and robust population trend assessments are key to successful biodiversity conservation. Citizen science surveys have provided good evidence of biodiversity declines whilst engaging people with them. Citizen scientists are also collecting opportunistic biodiversity records at unprecedented scales, vastly outnumbering records gathered through structured surveys. Opportunistic records exhibit spatio-temporal biases and heterogeneity in observer effort and skill, but their quantity offers a rich source of information. Data integration, the combination of multiple information sources in a common analytical framework, can potentially improve inferences about populations compared to analysing either in isolation. We combine count data from a structured citizen science survey and detection-nondetection data from an opportunistic citizen science programme. Population trends were modelled using dynamic N-mixture models to integrate both data sources. We applied this approach to two different inferential challenges arising from sparse data: (i) the estimation of population trends for an area smaller than a structured survey stratum, and (ii) the estimation of national population trends for a rare but widespread species. In both cases, data integration yielded population trajectories similar to those estimated from structured survey data alone but had higher precision when the density of opportunistic records was high. In some cases this allowed inferences about population trends where indices derived from single data sources were too uncertain to assess change. However, there were differences in the trend magnitude between the integrated and the standard survey model. We show that data integration of large-scale structured and unstructured data is feasible and offers potential to improve national and regional wildlife trend estimates, although a need to independently validate trends remains. Smaller gains are achieved in areas where uptake of opportunistic recording is low. The integration of opportunistic records from volunteer-selected locations alone may therefore not adequately address monitoring gaps for management and policy applications. To achieve the latter, scheme organisers should consider providing incentives for achieving representative coverage of target areas in both structured and unstructured recording schemes.

ecology↗

bioRxiv2017

Trait correlates of climatic niche tracking in British birds

Growing evidence indicates that species respond idiosyncratically when exposed to the same changes in climate. As a result, understanding the potential influence of biological traits on species distributional responses is a research priority. Yet, empirical support for hypothesised influences of traits on climate change responses remains equivocal.\n\nIn this paper, we developed a novel approach to determine whether biological traits predict the degree of climatic niche tracking of British breeding birds in response to recent climate change. First, we quantified how well predicted positive and negative changes in probability of presence from climate-based species distribution models agreed with observed local gains and losses in species occupancy - our measure of climatic niche tracking. Second, we examined whether the degree of climatic niche tracking could be predicted by species ecological and life-history traits, as well as phylogenetic relationships.\n\nOverall, British breeding birds displayed a low degree of climatic niche tracking over the period of our study, though this varied substantially among species. Models incorporating traits and phylogeny explained a low proportion of the variation in climatic niche tracking. Nevertheless, we did find statistical evidence that species with lower lifespans tracked their climatic niches more closely, whilst species with a mixed diet displayed a lower degree of climatic niche tracking.\n\nWe present here a tractable approach for quantifying the degree to which observed local range gains and losses can be related to climate redistribution and apply it to British breeding birds. Although we do not find strong evidence that traits predict the degree of climatic niche tracking, we discuss why this is likely to be a consequence of the features of our study system rather than the approach itself. We believe this approach may prove to be useful as datasets of temporal changes in species distributions become increasingly available.

ecology↗