Sterols regulate cell membrane fluidity and are precursors for hormone and secondary metabolite production in plants, but plant sterols also have a critical role as nutrients in herbivores. Here we describe the distribution of 78 different sterols from pollen of 295 UK wildflower taxa and use this data to develop an evolutionary rationale for the diversity of sterols in pollen compared to vegetative tissues. The sterolome was a function of plant lineage and conserved in groups as high as subfamily. Insect herbivores are auxotrophic for sterols, and notably bees can not modify them therefore rely on dietary sources, primarily pollen, to meet their metabolic needs. Most pollen in the present study contained high proportions of Δ5 sterols including β-sitosterol, 24-methylenecholesterol and isofucosterol, which are important sterols for bees. The sterols recorded in honey bees occurred in the pollen of only 68% of plant taxa, however, none matched these proportions exactly suggesting they must forage pollen from multiple plant taxa to satisfy their sterol requirements. We conclude that there is evidence for pollen sterol composition being the result of diverse driving forces including plant lineage and pollinator nutritional requirements. ### Competing Interest Statement The authors have declared no competing interest.

Light traps are a key method for monitoring moth populations. A wide variety of light sources are employed for this purpose, differing in brightness and spectrum. Relatively little is known about how this affects the resulting sample. We analyse seven moth trap bulb types using 10 years of records from the Garden Moth Scheme (GMS) to provide the largest and most comprehensive comparison of moth trap bulb types to date. The total abundance of moths caught by a trap is strongly linked to bulb wattage and brightness. We estimate that Heath traps catch fewer moths than Robinson or Skinner‐stye traps. Ordination models indicated that Mercury Vapour bulbs collected a distinct fauna to Actinic bulbs. Species composition also varied between Actinic bulbs which differ in brightness, with brighter Actinic traps tending to collect a larger proportion of large‐winged species. We develop hypotheses whereby large‐winged, strong‐flying moths are more strongly affected by artificial light (arising from moth traps or other sources). We explore how this hypothesised mechanism may result in negative fitness effects for larger, mobile moth species. Our findings have significant consequences for survey design, citizen science projects and understanding the impact of ALAN on the moth community.

Phytosterols regulate cell membrane fluidity and are precursors for plant hormones and secondary metabolites in plants. Insects are auxotrophic for sterols; therefore, they have to consume phytosterols and dealkylate them to cholesterol. Some insects, including bees, which rely on dietary sources, primarily pollen, for sterols, cannot modify them; therefore, they have adapted to use them unmodified as they occur in pollen. Here, using high resolution chemical analysis, we describe the distribution of 78 different pollen sterols from 295 UK wildflower taxa and use this data to develop an evolutionary rationale for the diversity of sterols in pollen compared to vegetative tissues. The sterol occurrence in pollen was a function of plant lineage and conserved in groups as high as subfamily. Most pollen in the present study contained high proportions of Δ5 sterols including β-sitosterol, 24-methylenecholesterol and isofucosterol, which are important sterols for bees. The sterols recorded in honeybees occurred in the pollen of only 68% of plant taxa; however, none matched these proportions exactly, suggesting they must forage pollen from multiple plant taxa to satisfy their sterol requirements. We conclude that there is evidence for pollen sterol composition being the result of diverse driving forces including plant lineage and potentially pollinator nutritional requirements.

Shifts in insect distributions have been reported globally, largely attributed to climate and landscape changes. Communities are being reshaped, with species response traits mediating the effects of changing environments. Using a machine-learning approach we model 1252 insect occupancies across three decades in Great Britain. We combine independent models of nine insect groups (butterflies, moths, odonates, orthopterans, carabids, ladybirds, bees, wasps and hoverflies) to take a high-level view of the trends and key environmental drivers of insect occupancy, as well as to highlight the trait mediations underlying the resulting niches. Across this wide taxonomic range, we identify common trends in insect occupancies, showing no Great Britain-wide decline since 1990, but instead local declines and changes in community compositions. Known drivers of biodiversity loss appear to underlie those changes, notably urban sprawl and landscape simplification. Our approach also highlights the crucial roles of two response traits: habitat breadth, in mediating the effects of changing landscapes diversity and voltinism, in mediating the effects of increasing temperatures on insect life cycles.

Agricultural intensification drives insect declines, including that of parasitoids, through landscape simplification and extensive use of synthetic pesticides. Spatially heterogeneous agricultural landscapes are potentially important biodiversity reservoirs where non‐crop habitats may support populations providing ecosystem services to farming. However, there is a need to find methods to support this transition to more sustainable farming and support the progressive concept of biosphere reserves. We focus here on the relationship between apple orchards and sclerophyllous natural fynbos vegetation in the megadiverse Kogelberg Biosphere Reserve, Cape Floristic Region, South Africa. We established patches of floral resources within apple orchards, which are embedded in landscapes, equivalent to the transition zone of the Kogelberg Biosphere Reserve (KBR), with varying proportions of natural habitat in a 500‐m radius around orchards. We assessed the role of these enhanced floral resources for supporting parasitoid abundance, species richness and diversity inside orchards and compare these metrics to those in ruderal vegetation around orchards and in nearby natural vegetation. Further, we assessed the effect of semi‐natural vegetation in the surrounding landscape mosaic on parasitoids in orchards. Floral enhancement improved parasitoid abundance and influenced assemblage composition within apple orchards. However, non‐crop ruderal habitat immediately adjacent to orchards supported greater abundance and richness of parasitoid species, while natural fynbos supported even richer parasitoid assemblages. Vegetation within orchards and landscape complexity enhanced parasitoid assemblages inside and surrounding the orchards. Our study shows that increasing floral resources within orchards improves local diversity of parasitoids within agroecosystems in the Biosphere Reserve. In doing so, this improves levels of biodiversity and increases parasitoid richness within the biosphere transition zone, supporting a shift from conventional production to a more biodiversity‐friendly agroecological approach.

Biodiversity in human-dominated landscapes is declining, but evidence-based conservation targets to guide international policies for such landscapes are lacking. We present a framework for informing habitat conservation policies based on the enhancement of habitat quantity and quality and define thresholds of habitat quantity at which it becomes effective to also prioritize habitat quality. We applied this framework to insect pollinators, an important part of agroecosystem biodiversity, by synthesizing 59 studies from 19 countries. Given low habitat quality, hoverflies had the lowest threshold at 6% semi-natural habitat cover, followed by solitary bees (16%), bumble bees (18%), and butterflies (37%). These figures represent minimum habitat thresholds in agricultural landscapes, but when habitat quantity is restricted, marked increases in quality are required to reach similar outcomes.

Nectar and pollen are the two main floral resources consumed by bees, hoverflies and some other flower‐visiting insects. However, most existing datasets on floral resources focus on nectar production, and pollen is usually overlooked. We quantified pollen production for 168 common plant species found in the UK. Our dataset consists of pollen volume per flower, calculated from the number of pollen grains and the volume of a pollen grain. Detailed data collection protocols are presented. Practical implication. This pollen dataset provides a means to identify the high pollen producing species for pollinator conservation purposes, and to estimate pollen production at larger spatial scales when combined with field surveys.

Context: In the face of dual challenges of sustainable food production and biodiversity conservation, the knowledge gaps of farmers about biodiversity, pests, and their natural enemies can become a crucial barrier to adopting sustainable land management practices. Objective: The study aimed to assess farmers ' knowledge and understanding of crop pest and natural enemy diversity and their impacts, and whether the adoption Climate -Smart or Conservation Agriculture (CSA here onwards) was associated with this knowledge. Methods: We conducted questionnaire -based interviews and showed biodiversity images, including crop pests and beneficial insects, to understand farmers knowledge of biodiversity on their farms. A comparison was drawn between farmers practising CSA and non-CSA farmers to understand the role of CSA in enhancing biodiversity knowledge. Results and conclusions: Farmers facing greater yield losses were aware of pests, but they were less knowledgeable about their natural enemies, and they used fewer conservation management practices. CSA farmers, however, showed more biodiversity knowledge, especially of natural enemies, and they employed a wider range CS management practices. Farmers ' age, experience, education, and training were positively correlated with biodiversity knowledge, leading to better natural enemy conservation and pest management practices. Significance: The findings underscore the need for biodiversity-focused capacity building in sustainable agricultural programs, targeting less knowledgeable farming groups. It emphasises the crucial role of farmers ' knowledge in developing sustainable and biodiversity-friendly food production systems. Africa, East Usambara Mountains, Food security, Biodiversity conservation, Invertebrates, Crop pests, Climate -Smart Agriculture, Farmer education.

Hedgerows are a semi-natural habitat that supports farmland biodiversity by providing food, shelter, and habitat connectivity. Hedgerow planting goals have been set across many countries in Europe and agri-environment schemes (AES) play a key role in reaching these targets. Passive acoustic monitoring using automated vocalisation identification (automated PAM), offers a valuable opportunity to assess biodiversity changes following AES implementation using simple, community-level metrics, such as vocal activity of birds and bats. To evaluate whether vocal activity could be used to indicate the effectiveness of AES following hedgerow planting in future result-based or hybrid schemes, we surveyed twenty-four hedgerows in England classified into a chrono-sequence of three age categories (New, Young, Old). We recorded 4466 h over the course of 30 days and measured bird and bat vocal activity using BirdNET for birds and Kaleidoscope for bats. Vocal activity of all birds, farmland birds, and bats were modelled with age and predictors of hedgerow, habitat, and weather conditions to assess changes occurring from hedgerow planting to maturity. We show an increase of vocal activity in Young and Old hedgerows compared to New ones and highlight elements of the surrounding landscape that should be considered when evaluating AES implementation on bird and bat communities. We found high BirdNET precision in community-level vocal activity and low precision of species-level observations, and we argue that vocal activity may be used in novel AES to link a result-based payment component to automated PAM results, incentivising biodiversity effective hedgerow planting and management by farmers and landowners.

There is strong evidence that landscape-scale factors such as habitat diversity, composition and configuration are important drivers of declines in pollinators and pollination services. However, context and species-specific responses make it challenging to draw general conclusions about the most important components of landscapes that support diverse and abundant pollinator communities. In this study, we took a functional-traits approach to community assembly and tested the hypothesis that landscape properties act most strongly on pollinators indirectly, through their influence on flowering plant communities. Using plant and pollinator data from 96 landscapes in Britain, we tested the associations between plant and pollinator communities and local environmental factors, such as habitat cover and configuration, using path analysis based on Mantel and partial Mantel statistics. When all pollinators were considered, we found that the environmental factors had stronger links to the composition of flowering plant communities than to the composition of pollinator communities. Further, the flowering plant community was strongly linked to the pollinator community suggesting a mediating role between land use and pollinators. When separating the pollinator community into taxonomic groups, we found the same result for hoverflies, but wild bees were linked to both environmental factors and flowering plants. We further explored these links with structural equation models using the response-effect trait framework as a guiding principle. We found strong evidence that land-use composition and configuration influence the trait distribution and functional diversity of the pollinator community via plant community composition. These findings suggest that the indirect effect of land use on pollinators via flowering plants should be considered in informing the design of pollinator friendly landscapes and in future research of the effects of land use and management on wild pollinators.Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog.image

Code in support of "Population links between an insectivorous bird and moths disentangled through national scale monitoring data" Luke Christopher Evans, Malcolm D. Burgess, Simon G. Potts, William E. Kunin, Tom H. Oliver

Global biodiversity declines require a step change in monitoring frameworks to properly track and diagnose population trends. National weather surveillance radar (WSR) networks offer high spatial (ca. 1-10 km) and temporal (5-10 min) resolution data collected over regional and decadal scales, with well-supported infrastructure that holds great promise for the study of biodiversity. However, WSR datasets pose new challenges for ecologists due to their format, volume, and three-dimensional spatial structure. Here, we define a novel approach to the processing of WSR data to produce a product that can be used to interrogate trends in aerial biodiversity (abundance or diversity) at and across individual ground-level sites. From the full volume of WSR data collected approximately every six minutes we extract vertical columns of WSR observations above sites to compare against standardised nocturnal macro-moth monitoring data at ground level. The results show that there is strong agreement between the WSR-derived proxy of biodiversity in the air column and ground-level measurements of abundance and diversity in nocturnal moth communities. The columnar product operates on a biologically relevant scale with a diameter of 5 km, although column dimensions can easily be customised, and can be deployed at any site within a WSR's observable range. These findings have the potential to unlock past and present WSR observations for widespread application to existing and novel ecological questions and can be applied to weather radar networks around the world.

Colonisation credit refers to the temporal lag between positive conservation actions and species' responses and may be one of the reasons we fail to meet short‐term conservation targets. This is particularly evident in woodlands which take decades to develop and harbour slow colonising species. Given global objectives to increase woodland cover, it is important to know the timeframe within which colonisation credit will be fulfilled. The colonisation of woodland plants was examined in recent woodlands, created between 15 and 80 years ago, and located adjacent or isolated from existing ancient woodlands. Colonisation credit was calculated as the proportion of understory woodland plant species in the nearest ancient woodland which had not colonised recent woodlands. Looking at individual species traits also allowed us to tease apart their impact on the species colonisation and establishment ability. Spatial adjacency between created and ancient woodland reduced colonisation credit by an average of 28%, and more mature created woodlands (50–80 years old) had fulfilled 24% more of their colonisation credit on average than younger created woodlands (15–21 years old). However, mature woodlands created adjacent to ancient woodlands had still only been colonised by an average of 72% of the available species pool. Plants which had reached adjacent created woodlands were dispersed by a range of mechanisms, where those that had reached more isolated sites were largely dispersed by birds or mammals. Low community weighted mean shade tolerance, high community weighted nutrient affiliation, and the dominance of Hedera helix suggest that competition from dominant natives may be preventing certain species establishing in new woodlands. This research demonstrates the need to account for appropriate time‐lags when setting biodiversity targets, with most sites still displaying colonisation credit decades after they were created. The results also indicate that spatially targeting woodland creation adjacent to species‐rich mature woodlands should be prioritised. Still, poor local habitat conditions may lead to the dominance of specific competitors which prevent a range of other species from establishing. Local management interventions such as translocations and tree thinning may ameliorate this but further research is needed.

1. Colonisation credit refers to the temporal lag between positive conservation actions and species' responses and may be one of the reasons we fail to meet short-term conservation targets. This is particularly evident in woodlands which take decades to develop and harbour slow colonising species. Given global objectives to increase woodland cover, it is important to know the timeframe within which colonisation credit will be fulfilled.2. The colonisation of woodland plants was examined in recent woodlands, created between 15 and 80 years ago, and located adjacent or isolated from existing ancient woodlands. Colonisation credit was calculated as the proportion of understory woodland plant species in the nearest ancient woodland which had not colonised recent woodlands. Looking at individual species traits also allowed us to tease apart their impact on the species colonisation and establishment ability.3. Spatial adjacency between created and ancient woodland reduced colonisation credit by an average of 28%, and more mature created woodlands (50-80 years old) had fulfilled 24% more of their colonisation credit on average than younger created woodlands (15-21 years old). However, mature woodlands created adjacent to ancient woodlands had still only been colonised by an average of 72% of the available species pool.4. Plants which had reached adjacent created woodlands were dispersed by a range of mechanisms, where those that had reached more isolated sites were largely dispersed by birds or mammals. Low community weighted mean shade tolerance, high community weighted nutrient affiliation, and the dominance of Hedera helix suggest that competition from dominant natives may be preventing certain species establishing in new woodlands.5. This research demonstrates the need to account for appropriate time-lags when setting biodiversity targets, with most sites still displaying colonisation credit decades after they were created. The results also indicate that spatially targeting woodland creation adjacent to species-rich mature woodlands should be prioritised. Still, poor local habitat conditions may lead to the dominance of specific competitors which prevent a range of other species from establishing. Local management interventions such as translocations and tree thinning may ameliorate this but further research is needed.

Ecological processes are often spatially and temporally structured, potentially leading to autocorrelation either in environmental variables or species distribution data. Because of that, spatially-biased in-situ samples or predictors might affect the outcomes of ecological models used to infer the geographic distribution of species and diversity. There is a vast heterogeneity of methods and approaches to assess and measure spatial bias; this paper aims at addressing the spatial component of data-driven biases in species distribution modelling, and to propose potential solutions to explicitly test and account for them. Our major goal is not to propose methods to remove spatial bias from the modelling procedure, which would be impossible without proper knowledge of all the processes generating it, but rather to propose alternatives to explore and handle it. In particular, we propose and describe three main strategies that may provide a fair account of spatial bias, namely: (i) how to represent spatial bias; (ii) how to simulate null models based on virtual species for testing biogeographical and species distribution hypotheses; and (iii) how to make use of spatial bias - in particular related to sampling effort - as a leverage instead of a hindrance in species distribution modelling. We link these strategies with good practice in accounting for spatial bias in species distribution modelling.

Creating native woodland is a policy goal globally, and one strategy to maximize woodland creation benefits in limited space is to target efforts to extend existing woodlands. There is evidence to support spatially targeting habitat creation for biodiversity, however, there is little evidence of how this affects a habitat's structural development. Here, a space‐for‐time study using light detection and ranging (LiDAR) data assesses how the structure of recently created woodlands, are affected by the presence of an adjacent older woodland. Recently created native woodlands were identified across the Isle of Wight UK using historical maps and satellite imagery. Canopy height and foliage height diversity were derived for all woodlands from LiDAR data collected at two different time points (2011 and 2021), and linear models were used to test for any differences in these structural metrics between sites with an adjacent older woodland, and those without. The percentage change in woodland height between the two time points was also tested. In woodlands created adjacent to older woodlands, canopy height was found to be higher by an average of nearly 2 m, and foliage height diversity was found to be on average 4.7% higher, using the 2021 data. Growth rates between 2011 and 2021 were not significantly different between the groups, although young adjacent woodlands grew the most on average. This research shows that creating woodlands adjacent to existing older woodlands reduces the time taken to create tall and to a lesser extent structurally diverse habitat, which may lead to early biodiversity benefits.

Species distribution models (SDMs) are key tools in biodiversity and conservation, but assessing their reliability in unsampled locations is difficult, especially where there are sampling biases. We present a spatially-explicit sensitivity analysis for SDMs - SDM profiling - which assesses the leverage that unsampled locations have on the overall model by exploring the interaction between the effect on the variable response curves and the prevalence of the affected environmental conditions. The method adds a 'pseudo-presence' and 'pseudo-absence' to unsampled locations, re-running the SDM for each, and measuring the difference between the probability surfaces of the original and new SDMs. When the standardised difference values are plotted against each other (a 'profile plot'), each point's location can be summarized by four leverage measures, calculated as the distances to each corner. We explore several applications: visualization of model certainty; identification of optimal new sampling locations and redundant existing locations; and flagging potentially erroneous occurrence records.

Geographic range size is the most commonly implemented criterion of species’ extinction risk used in IUCN Red List assessments, especially for poorly-recorded species. IUCN applies two contrasting range size measures to capture different facets of a species’ distribution: Extent of Occurrence (EOO; Criterion B1) is the area bounding all known occurrences and is a proxy for the spatial autocorrelation of risk, while the Area of Occupancy (AOO; Criterion B2) is the area occupied within this boundary and is related to population size at finer grains. Various methods have been proposed to measure both EOO and AOO. We evaluate the impact of applying four methods for each of Criterion B1 and of B2, as well as key parameter choices, on the Red List status of 227 poorly-recorded neotropical pteridophyte species. Between 2 and 100% of species would be considered threatened depending on methodology. The minimum convex polygon method of estimating EOO was relatively robust to sampling effort for all but the least-recorded species. The IUCN-recommended method for estimating AOO of summing occupied 2 × 2 km grid cells was very strongly correlated with the total number of records. It is likely that only a small fraction of species can be adequately assessed using this method, and we recommend caution applying the method to poorly-recorded species in particular, where models predicting occupancy in unsampled areas (e.g. species distribution models) may provide more accurate assessments. It is vital that methodological information is retained with assessments, and comparisons should only be made between assessments utilising equivalent methods.

Species response traits mediate environmental effects on species distribution. Traits are used in joint and multispecies distribution models (JSDMs and MSDMs) to enable community‐wide shared parameters that characterise niche filtering along environmental gradients. Multispecies machine learning SDMs, however, do not use traits as their inclusion requires an additional taxonomic dimension that is incompatible with their usual tabular inputs. This has confined trait mediation in SDMs to hierarchical Bayesian models. Here we provide a novel artificial neural network (ANN) architecture that solves this dimensionality problem. Our ANN includes species traits (via a time distributed layer) and is therefore able to identify not only species‐specific responses to the environment, but also shared responses across the community that are mediated by species traits. Model performance evaluated at the species level not only quantifies the reliability of species predictions, but also their departure from an average response dictated by traits only. We apply our model to two unique long‐term spatio‐temporal of butterfly and moth datasets collected across the United Kingdom between 1990 and 2019. In addition to species traits, predictors include numerous metrics derived from weather, land‐cover and topology data. For butterflies and moths we show convincing model performance for classifying species occupancy. We use SHAP (Shapley Additive exPlanations) to explain the ANN and show how trait‐mediated and species‐specific responses can be approximated, hence yielding ecological insights on the key drivers of species distribution. We highlight a range of drivers of change that determine occupancy, including wind, temperature as well as habitat type. We demonstrate that a trait‐based approach can be encoded as an ANN by using a time distributed layer. This brings ANNs unmatched predictive capabilities to the field of MSDMs, at the same time of lifting their reputed drawback of poor explainability.