Spatial modelling of insect-delivered ecosystem services

Insects are integral to many ecosystem services, including pollination of crops by insect pollinators and control of pests by natural enemies (i.e. predators and parasites). These beneficial insects are suffering widespread declines, partly due to agricultural expansion and intensification. We must therefore change the management of agricultural landscapes to preserve these ecosystem services and the resilience of the systems that depend on them. To make such changes, we first need to understand the relationships between landscapes, beneficial insect communities and the delivery of the services they provide. This thesis focuses on analysing novel combinations of large-scale spatial datasets to explore these relationships. Firstly, a ten-year time-series of wheat yield data was analysed in conjunction with satellite�derived land cover data to explore national-scale relationships between crop yield resilience and landscape structure. Whilst relative yield was highest in landscapes dominated by arable land, stability and resistance were promoted by semi-natural habitats. Secondly, data from biological recording schemes were used to construct potential plant-pollinator networks across Great Britain and explore relationships between network structure and land cover. Networks were most robust to simulated extinctions in highly agricultural landscapes, because they supported distinctive, generalist pollinator communities. Finally, data on land cover and cropping patterns were used to develop a range of scenarios of agricultural change. These were linked to beneficial insect richness and functional diversity using species distribution models based on biological records. Scenarios involving restoration of semi-natural grasslands increased the richness and functional diversity of beneficial insects, even if cropped land remained intensive. The findings presented in this thesis demonstrate the value of combining and modelling spatial data in exploring insect-delivered ecosystem services. Whilst there is much scope for further work, including integration with experimental data, spatial modelling remains key to providing the large-scale evidence required by policy makers and agricultural land managers

Fate of semi-natural grassland in England between 1960 and 2013: a test of national conservation policy

It is well documented that significant losses in semi-natural grassland occurred across Europe during the second half of the twentieth century. However, comparatively few studies have investigated and quantified the fate of large numbers of individual grassland areas. This is important for understanding the causes of decline, and consequently establishing new policies to conserve and restore lost habitats. This study addresses this problem; GIS was used to compare historic survey data collected between 1960 and 1981 with two contemporary spatial datasets of habitats in England. The datasets included the Priority Habitats Inventory 2013 and the Land Cover Map 2007 and this was undertaken for different types of semi-natural grassland across England. Considerable decreases occurred across the different grassland types, with a loss of 47% of studied semi-natural grasslands sites in England over 32–53 years. Of this, the majority of grassland was lost to conversion to agriculturally-improved grassland or arable cultivation, 45% and 43% respectively. Changes to woodland and urban areas were also evident, but on a much smaller scale. Sites receiving statutory protection as a Site of Special Scientific Interest were found to have retained more grassland (91%), compared with non-protected sites (27%), thus highlighting the effectiveness of this aspect of current conservation policy in England, and the need for this to continue in the future

Effects of future agricultural change scenarios on beneficial insects

Insects provide vital ecosystem services to agricultural systems in the form of pollination and natural pest control. However, there are currently widespread declines in the beneficial insects which deliver these services (i.e. pollinators and ‘natural enemies’ such as predators and parasitoids). Two key drivers of these declines have been the expansion of agricultural land and intensification of agricultural production. With an increasing human population requiring additional sources of food, further changes in agricultural land use appear inevitable. Identifying likely trajectories of change and predicting their impacts on beneficial insects provides a scientific basis for making informed decisions on the policies and practices of sustainable agriculture. We created spatially explicit, exploratory scenarios of potential changes in the extent and intensity of agricultural land use across Great Britain (GB). Scenarios covered 52 possible combinations of change in agricultural land cover (i.e. agricultural expansion or grassland restoration) and intensity (i.e. crop type and diversity). We then used these scenarios to predict impacts on beneficial insect species richness and several metrics of functional diversity at a 10km (hectad) resolution. Predictions were based on species distribution models derived from biological records, comprising data on 116 bee species (pollinators) and 81 predatory beetle species (natural enemies). We identified a wide range of possible consequences for beneficial insect species richness and functional diversity as result of future changes in agricultural extent and intensity. Current policies aimed at restoring semi-natural grassland should result in increases in the richness and functional diversity of both pollinators and natural enemies, even if agricultural practices remain intensive on cropped land (i.e. land-sparing). In contrast, any expansion of arable land is likely to be accompanied by widespread declines in richness of beneficial insects, even if cropping practices become less intensive (i.e. land-sharing), although effects of functional diversity are more mixed

The Free Will Theorem

On the basis of three physical axioms, we prove that if the choice of a particular type of spin 1 experiment is not a function of the information accessible to the experimenters, then its outcome is equally not a function of the information accessible to the particles. We show that this result is robust, and deduce that neither hidden variable theories nor mechanisms of the GRW type for wave function collapse can be made relativistic. We also establish the consistency of our axioms and discuss the philosophical implications.Comment: 31 pages, 6figure

National patterns of functional diversity and redundancy in predatory ground beetles and bees associated with key UK arable crops

1. Invertebrates supporting natural pest control and pollination ecosystem services are crucial to world-wide crop production. Understanding national patterns in the spatial structure of natural pest control and pollination can be used to promote effective crop management and contribute to long-term food security. 2. We mapped the species richness and functional diversity of ground beetles and bees to provide surrogate measures of natural pest control and pollination for Great Britain. Func- tional diversity represents the value and range of morphological and behavioural traits that support ecosystem services. We modelled the rate at which functional diversity collapsed in response to species extinctions to provide an index of functional redundancy. 3. Deficits in functional diversity for both pest control and pollination were found in areas of high arable crop production. Ground beetle functional redundancy was positively corre- lated with the landscape cover of semi-natural habitats where extinctions were ordered by body size and dispersal ability. For bees, functional redundancy showed a weak positive cor- relation with semi-natural habitat cover where species extinctions were ordered by feeding specialization. 4. Synthesis and applications. Increasingly, evidence suggests that functionally diverse assem- blages of ground beetles and bees may be a key element to strategies that aim to support pol- lination and natural pest control in crops. If deficits in both functional diversity and redundancy in areas of high crop production are to be reversed, then targeted implementation of agri-environment schemes that establish semi-natural habitat may provide a policy mecha- nism for supporting these ecosystem services

Comparing strengths and weaknesses of three ecosystem services modelling tools in a diverse UK river catchment

Ecosystem services modelling tools can help land managers and policy makers evaluate the impacts of alternative management options or changes in land use on the delivery of ecosystem services. As the variety and complexity of these tools increases, there is a need for comparative studies across a range of settings, allowing users to make an informed choice. Using examples of provisioning and regulating services (water supply, carbon storage and nutrient retention), we compare three spatially explicit tools – LUCI (Land Utilisation and Capability Indicator), ARIES (Artificial Intelligence for Ecosystem Services) and InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs). Models were parameterised for the UK and applied to a temperate catchment with widely varying land use in North Wales. Although each tool provides quantitative mapped output, can be applied in different contexts, and can work at local or national scale, they differ in the approaches taken and underlying assumptions made. In this study, we focus on the wide range of outputs produced for each service and discuss the differences between each modelling tool. Model outputs were validated using empirical data for river flow, carbon and nutrient levels within the catchment. The sensitivity of the models to land-use change was tested using four scenarios of varying severity, evaluating the conversion of grassland habitat to woodland (0–30% of the landscape). We show that, while the modelling tools provide broadly comparable quantitative outputs, each has its own unique features and strengths. Therefore the choice of tool depends on the study question

Effects of habitat composition and landscape structure on worker foraging distances of five bumblebee species

Bumblebees (Bombus spp.) are important pollinators of both crops and wild flowers. Their contribution to this essential ecosystem service has been threatened over recent decades by changes in land use, which have led to declines in their populations. In order to design effective conservation measures it is important to understand the effects of variation in landscape composition and structure on the foraging activities of worker bumblebees. This is because the viability of individual colonies is likely to be affected by the trade-off between the energetic costs of foraging over greater distances and the potential gains from access to additional resources. We used field surveys, molecular genetics and fine resolution remote sensing to estimate the locations of wild bumblebee nests and to infer foraging distances across a 20 km2 agricultural landscape in southern England. We investigated five species, including the rare B. ruderatus and ecologically similar but widespread B. hortorum. We compared worker foraging distances between species and examined how variation in landscape composition and structure affected foraging distances at the colony level. Mean worker foraging distances differed significantly between species. Bombus terrestris, B. lapidarius and B. ruderatus exhibited significantly greater mean foraging distances (551 m, 536 m, 501 m, respectively) than B. hortorum and B. pascuorum (336 m, 272 m, respectively). There was wide variation in worker foraging distances between colonies of the same species, which was in turn strongly influenced by the amount and spatial configuration of available foraging habitats. Shorter foraging distances were found for colonies where the local landscape had high coverage and low fragmentation of semi-natural vegetation, including managed agri-environmental field margins. The strength of relationships between different landscape variables and foraging distance varied between species, for example the strongest relationship for B. ruderatus being with floral cover of preferred forage plants. Our findings suggest that favourable landscape composition and configuration has the potential to minimise foraging distances across a range of bumblebee species. There is thus potential for improvements in the design and implementation of landscape management options, such as agri-environment schemes, aimed at providing foraging habitat for bumblebees and enhancing crop pollination services

Symmetries and the identity of physical states

The paper proposes a combined account of identity for physical states and direct empirical significance for symmetries according to which symmetry-related state variables designate distinct physical states if and only if the symmetry that relates them has direct empirical significance. Strengthening an earlier result, I show that, given this combined account, the local gauge symmetries in our leading contemporary theories of particle physics do not have any direct empirical significance

High resolution wheat yield mapping using Sentinel-2

Accurate crop yield estimates are important for governments, farmers, scientists and agribusiness. This paper provides a novel demonstration of the use of freely available Sentinel-2 data to estimate within-field wheat yield variability in a single year. The impact of data resolution and availability on yield estimation is explored using different combinations of input data. This was achieved by combining Sentinel-2 with environmental data (e.g. meteorological, topographical, soil moisture) for different periods throughout the growing season. Yield was estimated using Random Forest (RF) regression models. They were trained and validated using a dataset containing over 8000 points collected by combine harvester yield monitors from 39 wheat fields in the UK. The results demonstrate that it is possible to produce accurate maps of within-field yield variation at 10 m resolution using Sentinel-2 data (RMSE 0.66 t/ha). When combined with environmental data further improvements in accuracy can be obtained (RMSE 0.61 t/ha). We demonstrate that with knowledge of crop-type distribution it is possible to use these models, trained with data from a few fields, to estimate within-field yield variability on a landscape scale. Applying this method gives us a range of crop yield across the landscape of 4.09 to 12.22 t/ha, with a total crop production of approx. 289,000 t