Invasive alien species (IAS) are considered one of the greatest threats to biodiversity, particularly through their interactions with other drivers of change. Horizon scanning, the systematic examination of future potential threats and opportunities, leading to prioritization of IAS threats is seen as an essential component of IAS management. Our aim was to consider IAS that were likely to impact on native biodiversity but were not yet established in the wild in Great Britain. To achieve this, we developed an approach which coupled consensus methods (which have previously been used for collaboratively identifying priorities in other contexts) with rapid risk assessment. The process involved two distinct phases: Preliminary consultation with experts within five groups (plants, terrestrial invertebrates, freshwater invertebrates, vertebrates and marine species) to derive ranked lists of potential IAS.Consensus-building across expert groups to compile and rank the entire list of potential IAS.Five hundred and ninety-one species not native to Great Britain were considered. Ninety-three of these species were agreed to constitute at least a medium risk (based on score and consensus) with respect to them arriving, establishing and posing a threat to native biodiversity. The quagga mussel, Dreissena rostriformis bugensis, received maximum scores for risk of arrival, establishment and impact; following discussions the unanimous consensus was to rank it in the top position. A further 29 species were considered to constitute a high risk and were grouped according to their ranked risk. The remaining 63 species were considered as medium risk, and included in an unranked long list. The information collated through this novel extension of the consensus method for horizon scanning provides evidence for underpinning and prioritizing management both for the species and, perhaps more importantly, their pathways of arrival. Although our study focused on Great Britain, we suggest that the methods adopted are applicable globally.

Here, we determine annual estimates of occupancy and species trends for 5,293 UK bryophytes, lichens, and invertebrates, providing national scale information on UK biodiversity change for 31 taxonomic groups for the time period 1970 to 2015. The dataset was produced through the application of a Bayesian occupancy modelling framework to species occurrence records supplied by 29 national recording schemes or societies (n = 24,118,549 records). In the UK, annual measures of species status from fine scale data (e.g. 1 × 1 km) had previously been limited to a few taxa for which structured monitoring data are available, mainly birds, butterflies, bats and a subset of moth species. By using an occupancy modelling framework designed for use with relatively low recording intensity data, we have been able to estimate species trends and generate annual estimates of occupancy for taxa where annual trend estimates and status were previously limited or unknown at this scale. These data broaden our knowledge of UK biodiversity and can be used to investigate variation in and drivers of biodiversity change.

We present two new avian molecular sexing techniques for nonpasserine and passerine birds (Neognathae), which are more suitable for use with museum specimens than earlier methods. The technique for nonpasserines is based on a new primer (M5) which, in combination with the existing P8 primer, targets a smaller amplicon in the CHD1 sex-linked gene than previously. Primers targeting ATP5A1, an avian sex-linked gene not previously used for sex identification, were developed for passerines. Comprehensive testing across species demonstrated that both primer pairs sex a range of different species within their respective taxonomic groups. Rigorous evaluation of each method within species showed that these permitted sexing of specimens dating from the 1850s. For corn bunting museum specimens, the ATP5A1 method sexed 98% of 63 samples (1857-1966). The M5/P8 CHD1 method was similarly successful, sexing 90% of 384 moorhen specimens from six different museum collections (1855-2001). In contrast, the original P2/P8 CHD1 sexing method only identified the sex of less than half of 111 museum moorhen samples. In addition to dried skin samples, these methods may be useful for other types of material that yield degraded or damaged DNA, and are hence potential new sexing tools for avian conservation genetics, population management and wildlife forensics.

Climate has been widely regarded as the main determinant of the geographical distribution of species. Biotic interactions between co‐occurring species, however, are an important additional influence. We review the importance of interactions with food and nectar plants (as resources) in determining the distribution of phytophagous and pollinating insects (as consumers). We use biological recording datasets for seven taxonomic groups to quantify the relationship between the geographical distributions within Britain of 1265 phytophagous insects and their associated food plants, representing 9128 interactions in total. We find a consistent pattern across taxonomic groups in that individual phytophagous insect species rarely utilize the full range of their food plants and the relationship between the range sizes of insects and their food plants is not a simple linear one. For a small selection of phytophagous species where data are available, we highlight an association between changes in range and interactions with associated food plant species. Climate‐driven range expansion may be constrained through disruption of trophic relationships between phytophagous insects and their food plants if they respond differently to abiotic drivers. By contrast, range expansion may be facilitated by temporary escape from natural enemies and/or exploitation of novel food plants that enable a broader set of habitats to be utilized. In a changing environment, some existing interactions will be disrupted but opportunities for novel interactions will also emerge, producing new assemblages and changes in distributions that will be dynamic yet hard to predict. © 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, ●●, ●●–●●.