Quantifying the effectiveness of agri-environment schemes for a grassland butterfly using individual-based models

Models of bee responses to land use and land cover changes in agricultural landscapes - a review and research agenda

Predictive modelling tools can be used to support the design of agricultural landscapes to promote pollinator biodiversity and pollination services. Despite the proliferation of such modelling tools in recent decades, there remains a gap in synthesising their main characteristics and representation capacities. Here, we reviewed 42 studies that developed non-correlative models to explore the impact of land use and land cover changes on bee populations, and synthesised information about the modelled systems, modelling approaches, and key model characteristics like spatiotemporal extent and resolution. Various modelling approaches are employed to predict the biodiversity of bees and the pollination services they provide, with a prevalence of models focusing on wild populations compared to managed ones. Of these models, landscape indicators and distance decay models are relatively simple, with few parameters. They allow mapping bee visitation probabilities using basic land cover data and considering bee foraging ranges. Conversely, mechanistic or agent-based models delineate, with varying degrees of complexity, a multitude of processes that characterise, among others, the foraging behaviour and population dynamics of bees. The reviewed models collectively encompass 38 ecological, agronomic, and economic processes, producing various outputs including bee abundance, habitat visitation rate, and crop yield. To advance the development of predictive modelling tools aimed at fostering pollinator biodiversity and pollination services in agricultural landscapes, we highlight future avenues for increasing biophysical realism in models predicting the impact of land use and land cover changes on bees. Additionally, we address the challenges associated with balancing model complexity and practical usability.

Ditch control and land reclamation promote vegetation recovery in Loess Plateau

This study aimed to assess the impact of land consolidation projects and climate change on changes in vegetation in the Loess Plateau during 2012-2021. The study also explored the impacts of human activities and climate change on the ecological quality of the Loess Plateau during this period. The spatial and temporal normalized difference combined meteorological monitoring data, project data, and normalized difference vegetation index (NDVI) data that was used to create the vegetation index dataset spanning from 2012-2021. The study discussed and assessed the effectiveness of the project, revealing the following results: 1) A significant increase was observed in the vegetation index of the Loess Plateau region from 2012 to 2021, with an upward trend of 0.0024 per year (P < 0.05). 2) Contributions to changes in vegetation attributed to climatic factors and the anthropogenic factors of the ditch construction project were 82.74 and 17.62%, respectively, with climatic factors dominating and the degree of response of the ditch construction project increasing annually. 3) In the Loess Plateau, climatic variables dominated changes in vegetation. However, land consolidation projects in vegetation factors played a key role in changes in vegetation, and the degree of influence was gradually increasing.

The expanding role of movement behavior in insect conservation ecology

Insect conservation will rely on incorporating behavior into management. Dispersal behavior is one such vital behavior for conservation, but it is generally poorly understood at the species level. We reviewed recent literature to identify intricacies that complicate including dispersal behavior in conservation management. Many previous theories used to predict the need to disperse do not explicitly address successful dispersal. Additionally, we found identifying barriers to dispersal as a possible way to improve conservation management, but it is necessary to consider multiple parts of dispersal (emigration, matrix navigation, immigration). Species' dispersal is context-specific. Therefore, to effectively incorporate dispersal behavior into conservation, more research is necessary on individual species' responses to their environment, how they navigate to optimal sites, and their fitness after dispersal events.

The importance of including habitat-specific behaviour in models of butterfly movement

Dispersal is a key process affecting population persistence and major factors affecting dispersal rates are the amounts, connectedness and properties of habitats in landscapes. We present new data on the butterfly Maniola jurtina in flower-rich and flower-poor habitats that demonstrates how movement and behaviour differ between sexes and habitat types, and how this effects consequent dispersal rates. Females had higher flight speeds than males, but their total time in flight was four times less. The effect of habitat type was strong for both sexes, flight speeds were ~ 2.5 × and ~ 1.7 × faster on resource-poor habitats for males and females, respectively, and flights were approximately 50% longer. With few exceptions females oviposited in the mown grass habitat, likely because growing grass offers better food for emerging caterpillars, but they foraged in the resource-rich habitat. It seems that females faced a trade-off between ovipositing without foraging in the mown grass or foraging without ovipositing where flowers were abundant. We show that taking account of habitat-dependent differences in activity, here categorised as flight or non-flight, is crucial to obtaining good fits of an individual-based model to observed movement. An important implication of this finding is that incorporating habitat-specific activity budgets is likely necessary for predicting longer-term dispersal in heterogeneous habitats, as habitat-specific behaviour substantially influences the mean (> 30% difference) and kurtosis (1.4 × difference) of dispersal kernels. The presented IBMs provide a simple method to explicitly incorporate known activity and movement rates when predicting dispersal in changing and heterogeneous landscapes.

Behavior underpins the predictive power of a trait-based model of butterfly movement

Dispersal ability is key to species persistence in times of environmental change. Assessing a species' vulnerability and response to anthropogenic changes is often performed using one of two methods: correlative approaches that infer dispersal potential based on traits, such as wingspan or an index of mobility derived from expert opinion, or a mechanistic modeling approach that extrapolates displacement rates from empirical data on short-term movements.Here, we compare and evaluate the success of the correlative and mechanistic approaches using a mechanistic random-walk model of butterfly movement that incorporates relationships between wingspan and sex-specific movement behaviors.The model was parameterized with new data collected on four species of butterfly in the south of England, and we observe how wingspan relates to flight speeds, turning angles, flight durations, and displacement rates.We show that flight speeds and turning angles correlate with wingspan but that to achieve good prediction of displacement even over 10 min the model must also include details of sex- and species-specific movement behaviors.We discuss what factors are likely to differentially motivate the sexes and how these could be included in mechanistic models of dispersal to improve their use in ecological forecasting.

Data on the movement behaviour of four species of grassland butterfly

This Data in Brief article describes data on the movement behaviour of four species of grassland butterflies collected over three years and at four sites in southern England. The datasets consist of the movement tracks of Maniola jurtina, Aricia agestis, Pyronia tithonus, and Melanargia galathea, recorded using standard methods and presented as steps distances and turning angles. Sites consisted of nectar-rich field margins, meadows, and mown short turf grasslands with minimal flowers. In total, 783 unique movement tracks were collected. The data were used for analysing the movement behaviour of the species and for parameterising individual-based movement models.