Pollinators in life cycle assessment: towards a framework for impact assessment

Abstract Human activities are threatening biodiversity at an unprecedented scale and pace, thus potentially affecting also the provision of critical ecosystem services, including insect pollination. Insect pollinators play an essential functional role in terrestrial ecosystems, supporting ecological stability and food security worldwide. Therefore, assessing impact on pollinators is fundamental in any effort aiming at enhancing the environmental sustainability of human production and consumption, especially in the agri-food supply chains. Different drivers are leading to pollinator populations' declines. Improving a supply-chain oriented assessment of the occurrence of pressure and impacts on pollinators is needed. However, current methodologies assessing impact along supply chains, such as life cycle assessment (LCA), miss to assess impact on pollinators. In fact, none of the existing life cycle impact assessment (LCIA) models effectively accounts for pollinators. Some LCIA models have mentioned pollination, but none has presented key drivers of impact and a proposal for integrating pollinators as target group for biodiversity protection within an LCIA framework. In order to devise a pathway towards the inclusion of impacts on pollinators in LCIA, we conducted a literature review of environmental and anthropogenic pressures acting on insect pollinators, potentially threatening pollination services. Based on the evidence in literature, we identified and described eight potential impact drivers, primarily deriving from industrial development and intensive agricultural practice: 1) intensified land use as a result of uncontrolled expansion of urban areas and modern agricultural practices; 2) use of pesticides; 3) presence of invasive alien plants; 4) competition with invasive alien pollinator species; 5) global and local climate change; 6) spread of pests and pathogens; 7) electro-magnetic pollution and 8) genetically modified crops. To account for these drivers in LCIA, there are specific modeling needs. Hence, the current study provides recommendation on how future research should be oriented to improve the current models and how novel indicators should be developed in order to cover the existing conceptual and methodological gaps

Large variability in response to projected climate and land‐use changes among European bumblebee species

Bumblebees (Bombus ssp.) are among the most important wild pollinators, but many species have suffered from range declines. Land-use change, agricultural intensification, and the associated loss of habitat have been identified as drivers of the observed dynamics, amplifying pressures from a changing climate. However, these drivers are still underrepresented in continental-scale species distribution modeling. Here, we project the potential distribution of 47 European bumblebee species in 2050 and 2080 from existing European-scale distribution maps, based on a set of climate and land-use futures simulated through a regional integrated assessment model and consistent with the RCP–SSP scenario framework. We compare projections including (1) dynamic climate and constant land use (CLIM); (2) constant climate and dynamic land use (LU); and (3) dynamic climate and dynamic land use (COMB) to disentangle the effects of land use and climate change on future habitat suitability, providing the first rigorous continental-scale assessment of linked climate–land-use futures for bumblebees. We find that direct climate impacts, although variable across species, dominate responses for most species, especially under high-end climate change scenarios (up to 99% range loss). Land-use impacts are highly variable across species and scenarios, ranging from severe losses (up to 75% loss) to considerable gains (up to 68% gain) of suitable habitat extent. Rare species thereby tend to be disproportionally affected by both climate and land-use change. COMB projections reveal that land use may amplify, attenuate, or offset changes to suitable habitat extent expected from climate impact depending on species and scenario. Especially in low-end climate change scenarios, land use has the potential to become a game changer in determining the direction and magnitude of range changes, indicating substantial potential for targeted conservation management

Ecosystem services accounting: Part I - Outdoor recreation and crop pollination

The Knowledge Innovation Project on an Integrated system of Natural Capital and ecosystem services Accounting (KIP INCA) aims to develop the first ecosystem accounts at EU level, following the UN System of Environmental-Economic Accounting- Experimental Ecosystem Accounts (SEEA-EEA). The application of the SEEA-EEA framework is useful to illustrate ecosystem accounts with clear examples and contribute to further develop to methodology and give guidance for Natural Capital Accounting. The aim of this study is to assess and account for two ecosystem services: outdoor recreation and crop pollination. Each service was assessed biophysically within the ESTIMAP toolbox, allowing us to quantify different service components: the service potential that the ecosystems can deliver; the demand for each service; and the actual flow of the service used based on the spatial relationship between the service potential and demand. The results of the biophysical assessment were then translated into monetary units using valuation methods consistent with the System of National Accounts. Valuation methods require the integration of the key variables of the biophysical model to quantify the actual flow. In this way, changes in the value of the service are strictly linked to changes in biophysical assessment, which includes potential, demand and their spatial relationship determining the actual flow. Accounting of outdoor recreation shows that at EU level, forest ecosystems have the highest value for outdoor recreation, although this varies among countries. Households are the users of the service, with Germany being the country with the largest share of population whose demand for daily recreation is covered. As demonstrated, countries with a larger share of population living within 4 km of recreational areas present higher level of life satisfaction. EU accounting shows an overall increase in the use of the service between 2000 and 2012 (26%), mainly due to the enhancement of the recreation potential, and, to a lesser extent, to an increase in the demand (population). These results are useful to support policy decisions related to land planning, aiming at guaranteeing the equitable accessibility to outdoor recreation opportunities (citizen rights): 38% of the population at the EU have limited accessibility to recreational areas (unmet demand). We estimated for 2012 an actual flow of 40 million potential visits to recreational areas per year (daily use), with a total value of 31 billion euro. At this stage, the full accounting cannot be given for crop pollination due to the lack of connection between the available valuation methods and the biophysical model assessing the service flow. In this sense, further research is needed to develop suitable methods to link the valuation technique with the biophysical model. In spite of these limitations, the crop pollination assessment provides useful results for the EU Pollinators Initiative. The work presented in this report highlights the importance of the spatial relationship between ecosystem service potential and demand. The changes in the use of the service quite often cannot be explained solely by changes in the potential and the demand, but also by their spatial relationship. When dealing with ecosystem services the spatial component is a key driver that needs to be integrated within the accounting framework for a consistent assessment. The spatial relationship between potential and demand is different for each service. Crop pollination requires the spatial overlap between potential and demand, whereas proximity is the key spatial feature for outdoor recreation. As shown by the two examples presented here, ecosystem service accounts significantly differ depending on the service being assessed, both conceptually and methodologically. Hence, further examples of ecosystem service accounting are needed to produce accounting tables for a representative number of service. Ultimately, the availability of this information represents a key input for the analysis of synergies and trade-offs between ecosystem services.JRC.D.3-Land Resource

Linking accounts for ecosystem services and benefits to the economy through bridging (LISBETH)

The acronym LISBETH stands for LInking accounts for ecosystem Services and Benefits to the Economy THrough bridging. LISBETH is based on INCA (Integrated system for Natural Capital Accounting) and is meant to facilitate the use of INCA accounts in traditional economic analytical tools. Three practical examples are described and commented on. The first application shows how to combine crop provision accounts with the conventional accounts related to agricultural products and their trade. Combined account presentations are useful for policymakers, not only for technical analytical purposes but also for communicating with a wider non-technical audience. The second application shows how to build consumption-based accounts using multiregional input–output tables; in our example we assess the water purification service embedded in traded crops. Consumption remains in fact the ultimate driver behind production processes. The third application shows how to link ecosystem services accounts to general equilibrium models to assess the economic impacts generated by changes in ecosystem services; in our example we address the impact of invasive alien species on pollination and in turn on pollination-dependent crops and their trade. The three applications provide several insights in terms of their usefulness at different steps of the policy cycle, their feasibility, their technical complexity (and thus the level of skill required) and also in terms of the primary users (from specialised analysts to a non-specialised audience).JRC.D.3-Land Resource

Species distribution models for crop pollination: a modelling framework applied to Great Britain

Insect pollination benefits over three quarters of the world's major crops. There is growing concern that observed declines in pollinators may impact on production and revenues from animal pollinated crops. Knowing the distribution of pollinators is therefore crucial for estimating their availability to pollinate crops; however, in general, we have an incomplete knowledge of where these pollinators occur. We propose a method to predict geographical patterns of pollination service to crops, novel in two elements: the use of pollinator records rather than expert knowledge to predict pollinator occurrence, and the inclusion of the managed pollinator supply. We integrated a maximum entropy species distribution model (SDM) with an existing pollination service model (PSM) to derive the availability of pollinators for crop pollination. We used nation-wide records of wild and managed pollinators (honey bees) as well as agricultural data from Great Britain. We first calibrated the SDM on a representative sample of bee and hoverfly crop pollinator species, evaluating the effects of different settings on model performance and on its capacity to identify the most important predictors. The importance of the different predictors was better resolved by SDM derived from simpler functions, with consistent results for bees and hoverflies. We then used the species distributions from the calibrated model to predict pollination service of wild and managed pollinators, using field beans as a test case. The PSM allowed us to spatially characterize the contribution of wild and managed pollinators and also identify areas potentially vulnerable to low pollination service provision, which can help direct local scale interventions. This approach can be extended to investigate geographical mismatches between crop pollination demand and the availability of pollinators, resulting from environmental change or policy scenarios

Climate-driven spatial mismatches between British orchards and their pollinators: increased risks of pollination deficits

Understanding how climate change can affect crop-pollinator systems helps predict potential geographical mismatches between a crop and its pollinators, and therefore identify areas vulnerable to loss of pollination services. We examined the distribution of orchard species (apples, pears, plums and other top fruits) and their pollinators in Great Britain, for present and future climatic conditions projected for 2050 under the SRES A1B Emissions Scenario. We used a relative index of pollinator availability as a proxy for pollination service. At present there is a large spatial overlap between orchards and their pollinators, but predictions for 2050 revealed that the most suitable areas for orchards corresponded to low pollinator availability. However, we found that pollinator availability may persist in areas currently used for fruit production, but which are predicted to provide sub-optimal environmental suitability for orchard species in the future. Our results may be used to identify mitigation options to safeguard orchard production against the risk of pollination failure in Great Britain over the next 50 years; for instance choosing fruit tree varieties that are adapted to future climatic conditions, or boosting wild pollinators through improving landscape resources. Our approach can be readily applied to other regions and crop systems, and expanded to include different climatic scenarios

European cities: territorial analysis of characteristics and trends - An application of the LUISA Modelling Platform (EU Reference Scenario 2013 - Updated Configuration 2014)

Cities and towns are at the core of the European economy but they are often also the places where problems related to the quality of life of citizens such as unemployment, segregation and poverty are most evident. To curtail the negative impacts and foster the positive effects of ongoing urban processes in Europe, policies have to be adjusted and harmonised to accommodate future urbanization trends. Such an analysis of the evolution of European cities requires the evaluation of impacts of continent-wide drivers and, at the same time, assessment of the effect of national and local strategies. As a contribution to this analysis of the current and future evolution of European territories (countries, macro-regions, regions or urban areas), the Directorate-General Joint Research Centre (DG JRC) of the European Commission (EC) has developed the Land-Use-based Integrated Sustainability Assessment (LUISA) Modelling Platform. Based on the concept of ‘dynamic land functions’, LUISA has adopted a novel approach towards activity-based modelling and endogenous dynamic allocation of population, services and activities. This report illustrates how European cities could potentially evolve over the time period 2010-2050, according to the reference configuration of the LUISA modelling platform, on the basis of a collection of spatial indicators covering several thematic fields. These spatial indicators aim to improve our understanding of urbanization and urban development processes in Europe; explore territorial dimensions of projected demographic and economic changes, and finally examine some key challenges that urban areas are or may be exposed to. Some of the key findings of this report are given below: - The proportion of the population living in cities, towns and suburbs is higher in the EU than in the rest of the world. According to the LUISA forecasts, the urban proportion will continue to increase up to 2030; subsequently slow down, and reach a relatively steady state by 2050. - In 2010, 65% of the EU population were living in Functional Urban Areas (FUA, the city and its commuting zone). This figure is expected to reach 70% by 2050. The total EU-28 population is expected to grow by 4.6%. Most of this population growth will occur particularly in FUA which will grow by an average 14%. - As of 2010, the amount of artificial areas per inhabitant in the EU-28 was estimated as 498 m2: it becomes 539 m2 in 2050 with an 8% increase. Although there is not a unique spatial pattern, land take tends to start peak at 5 km distance from the city centre. This is due to the fact that land is often less available for development within city centres and that the majority of land take therefore will occur firstly in the suburbs and then in rural areas. - By 2050, potential accessibility – as measure of economic opportunities - will be higher in the urban areas of north-western Europe, while it will not improve in lagging European regions. Urban form has a considerable impact on average travelled distances and thus potentially on the energy dependence of transport. - Green infrastructure is mainly located at the periphery of urban areas. Its share per person is generally low or very low in most of the European cities, with few exceptions. Green infrastructure per capita in FUA shows a general trend towards a decrease across the EU-28 (by approximately 13%) between 2010 and 2050. - Larger cities tend to have higher average flood risk, especially due to the higher sensitivity in terms of potential human and physical losses. The analysis herein presented is part of a wider initiative of DG JRC and DG REGIO aiming to improve the management of knowledge and sharing of information related to territorial policies, such as those concerning urban development. In this framework, the work will be further developed, covering the following main elements: - Development of the European Urban Data Platform, providing a single access point for data and indicators on the status and trends of European urban areas; - Updates of the LUISA configuration, to account for new socio-economic projections; - Support to the development of the EU Urban Agenda and related initiatives; - Provision of evidence-based support for the evaluation of territorial policies in particular to proof the role of cities in the implementation of EU priorities.JRC.H.8-Sustainability Assessmen

Assessing the health status of managed honeybee colonies (HEALTHY-B): a toolbox to facilitate harmonised data collection

Tools are provided to assess the health status of managed honeybee colonies by facilitating further harmonisation of data collection and reporting, design of field surveys across the European Union (EU) and analysis of data on bee health. The toolbox is based on characteristics of a healthy managed honeybee colony: an adequate size, demographic structure and behaviour; an adequate production of bee products (both in relation to the annual life cycle of the colony and the geographical location); and provision of pollination services. The attributes ‘queen presence and performance’, ‘demography of the colony’, ‘in-hive products’ and ‘disease, infection and infestation’ could be directly measured in field conditions across the EU, whereas ‘behaviour and physiology’ is mainly assessed through experimental studies. Analysing the resource providing unit, in particular land cover/use, of a honeybee colony is very important when assessing its health status, but tools are currently lacking that could be used at apiary level in field surveys across the EU. Data on ‘beekeeping management practices’ and ‘environmental drivers’ can be collected via questionnaires and available databases, respectively. The capacity to provide pollination services is regarded as an indication of a healthy colony, but it is assessed only in relation to the provision of honey because technical limitations hamper the assessment of pollination as regulating service (e.g. to pollinate wild plants) in field surveys across the EU. Integrating multiple attributes of honeybee health, for instance, via a Health Status Index, is required to support a holistic assessment. Examples are provided on how the toolbox could be used by different stakeholders. Continued interaction between the Member State organisations, the EU Reference Laboratory and EFSA is required to further validate methods and facilitate the efficient use of precise and accurate bee health data that are collected by many initiatives throughout the EU

Evaluating predictive performance of statistical models explaining wild bee abundance in a mass‐flowering crop

Wild bee populations are threatened by current agricultural practices in many parts of the world, which may put pollination services and crop yields at risk. Loss of pollination services can potentially be predicted by models that link bee abundances with landscape‐scale land‐use, but there is little knowledge on the degree to which these statistical models are transferable across time and space. This study assesses the transferability of models for wild bee abundance in a mass‐flowering crop across space (from one region to another) and across time (from one year to another). The models used existing data on bumblebee and solitary bee abundance in winter oilseed rape fields, together with high‐resolution land‐use crop‐cover and semi‐natural habitats data, from studies conducted in five different regions located in four countries (Sweden, Germany, Netherlands and the UK), in three different years (2011, 2012, 2013). We developed a hierarchical model combining all studies and evaluated the transferability using cross‐validation. We found that both the landscape‐scale cover of mass‐flowering crops and permanent semi‐natural habitats, including grasslands and forests, are important drivers of wild bee abundance in all regions. However, while the negative effect of increasing mass‐flowering crops on the density of the pollinators is consistent between studies, the direction of the effect of semi‐natural habitat is variable between studies. The transferability of these statistical models is limited, especially across regions, but also across time. Our study demonstrates the limits of using statistical models in conjunction with widely available land‐use crop‐cover classes for extrapolating pollinator density across years and regions, likely in part because input variables such as cover of semi‐natural habitats poorly capture variability in pollinator resources between regions and years