Diverse values of nature for sustainability.

Twenty-five years since foundational publications on valuing ecosystem services for human well-being1,2, addressing the global biodiversity crisis3 still implies confronting barriers to incorporating nature's diverse values into decision-making. These barriers include powerful interests supported by current norms and legal rules such as property rights, which determine whose values and which values of nature are acted on. A better understanding of how and why nature is (under)valued is more urgent than ever4. Notwithstanding agreements to incorporate nature's values into actions, including the Kunming-Montreal Global Biodiversity Framework (GBF)5 and the UN Sustainable Development Goals6, predominant environmental and development policies still prioritize a subset of values, particularly those linked to markets, and ignore other ways people relate to and benefit from nature7. Arguably, a 'values crisis' underpins the intertwined crises of biodiversity loss and climate change8, pandemic emergence9 and socio-environmental injustices10. On the basis of more than 50,000 scientific publications, policy documents and Indigenous and local knowledge sources, the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) assessed knowledge on nature's diverse values and valuation methods to gain insights into their role in policymaking and fuller integration into decisions7,11. Applying this evidence, combinations of values-centred approaches are proposed to improve valuation and address barriers to uptake, ultimately leveraging transformative changes towards more just (that is, fair treatment of people and nature, including inter- and intragenerational equity) and sustainable futures.

The impact of climate change on crop mix shift in the Nordic region.

Growing evidence of anthropogenic climate change suggests marked changes in agricultural ecosystems and crop suitability across the globe. Northern Europe is primarily predicted to see beneficial impacts through crop shifts towards the North of the region. However, studies that quantify the magnitude of climate induced past shifts and the likely future shifts in the agricultural land use patterns are lacking. We use a rich municipality level longitudinal data set from the Nordic region from 1979 to 2012 to study farmers' adaptation to climate change in terms of crop mix shift. We model four land use classes, namely, cereal, grass, oil seed, and 'others', a category summing the remaining agricultural land uses. On top of climatic variables, we include biophysical and economic variables as controls in the regression. We utilize a multinomial fractional logit regression to estimate changes in the land use mix. The projection results indicate that both the near future (2041-2070) and the far future (2071-2100) projected climate are likely to increase the area share of cereal and at the same time decrease the share of grass in the Nordic region relative to the baseline climate (1981-2010). However, these results vary across the region. The results generally suggest a moderate climate induced impact on the spatial crop distributions. Our projection results show a moderate shift in agricultural crop distributions depending on the climate scenario and the time-horizon. Depending on the climate change scenario, grass and cereal are expected to shift by up to 92.8 and 178.7 km, respectively, towards opposite directions; grass towards the South-West and cereal towards the North-East. Overall, the projected areal expansion of cereal towards the North-East is expected to lead to increased environmental pressure.

Cost-effective abatement of non-point source nitrogen emissions - The effects of uncertainty in retention.

Non-point nitrogen discharges from agriculture are difficult to regulate, because of the diffuse nature of the pollution. Inflexible and uniform regulation policies have been the solution in many parts of the world. A more targeted and flexible regulation, adjusted to the heterogeneity of hydrological conditions and ambient water quality, as well as the heterogeneity in abatement costs between farms, has been challenging to develop and implement. One reason is the difficulties measuring the hydrological conditions on a detailed spatial scale. One of the most important hydrological factors, which co-determines the load reduction, is the retention (attenuation) of nitrogen in the catchment, from the root zone to the coast. It is therefore critical to understand how uncertainty in retention affects policy recommendations. In this paper, we use a spatial costs-minimization catchment model, TargetEconN, applied to the Danish catchment Limfjorden. The model includes retention, effects of measures and abatement costs at a detailed spatial scale. The model identifies optimal spatial allocation of nitrogen abatement measures at different load reduction targets to the fjord. We use the model to evaluate the sensitivity of the results to different forms of uncertainty in retention by running scenarios. For all scenarios, the total costs, the marginal costs and the distribution of measures are compared, and special emphasis is paid to how uncertainty on the retention affects the cost-effective allocation of abatement measures. The results indicate that taking spatial heterogeneity of retention into account is important to obtain cost-effective nitrogen abatement as this reduces the costs by approximately 25 percent. We assess the importance of uncertainty in the retention estimates by comparing baseline results with the results from model runs using 1) the mean retention estimate for all areas, 2) misspecification of the retention estimates by 10-20 percent in low and high retention areas, and 3) random misspecification of the retention across the catchment. The results indicate that this range of misspecification and uncertainty in retention, does not play a major role for the allocation of measures, nor for the total costs. We conclude that considering spatial heterogeneity in retention is important for cost-effectiveness, and that a policy where retention is included in the allocation of measures is relatively robust towards the uncertainty in the measurements of retention. Uncertainty and misspecification can lead to higher costs for individual farmers. However, for the agricultural community as a whole it is much more costly not to take differences in retention into account.

Groundwater nitrate response to sustainable nitrogen management.

Throughout the world, nitrogen (N) losses from intensive agricultural production may end up as undesirably high concentrations of nitrate in groundwater with a long-term impact on groundwater quality. This has human and environmental health consequences, due to the use of groundwater as a drinking water resource, and causes eutrophication of groundwater-dependent ecosystems such as wetlands, rivers and near-coastal areas. At national scale, the measured nitrate concentrations and trends in Danish oxic groundwater in the last 70 years correlate well with the annual agricultural N surpluses. We also show that the N use efficiency of agriculture is related to the groundwater nitrate concentrations. We demonstrate an inverted U-shape of annual nitrate concentrations as a function of economic growth from 1948 to 2014. Our analyses evidence a clear trend of a reversal at the beginning of the 1980s towards a more sustainable agricultural N management. This appears to be primarily driven by societal demand for groundwater protection linked to economic prosperity and an increased environmental awareness. However, the environmental and human health thresholds are still exceeded in many locations. Groundwater protection is of fundamental global importance, and this calls for further development of environmentally and economically sustainable N management in agriculture worldwide.

A bio-economic analysis of a sustainable agricultural transition using green biorefinery.

Traditional pig production often relies on cereal-based feed, which has adverse environmental effects, e.g. nitrogen leaching and greenhouse gas (GHG) emissions. Alternative production systems are therefore sought to improve the sustainability of pig production. A promising alternative is to use proteinaceous feed from grass, produced in a green bio-refinery (GBR), to substitute part of the cereals in the feed. Cultivation of grass on arable land can reduce nitrogen leaching and pesticide application, and increase carbon storage. The GBR using grass as feedstock also produces valuable byproducts, e.g. fibre and biogas. In this study we combine a life-cycle analysis (LCA) and a cost-benefit analysis to compare the economic and environmental effects of producing the pig feed to produce 1ton of pork using two feeding systems. We apply this approach to the intensive Danish pork production as a case study. The results show that compared with traditional cereal-based feeding system for producing a ton of pork, using proteinaceous concentrate from small-scale GBR will (1) decrease the average feed cost by 5.01%; (2) produce a profit of 96€ before tax in the GBR; and (3) decrease the nitrogen leaching (NO3-N) by 28.2%. However, in most of the scenarios (except for G2), the nitrogen emissions into the air (N2O-N) will also increase because of the increased N fertilizer application compared to a cereal-based system. In most of the scenarios (except for S1 and G1), the energy and land use will also be saved. However, some important factors, e.g. the soil characteristics, pressed juice fraction in fresh biomass and scale of GBR, could subvert the conclusion about energy and land use saving in the alternative feeding system.

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, which are predicted to provide suboptimal 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.

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.

Bringing ecosystem services into economic decision-making: land use in the United Kingdom.

Landscapes generate a wide range of valuable ecosystem services, yet land-use decisions often ignore the value of these services. Using the example of the United Kingdom, we show the significance of land-use change not only for agricultural production but also for emissions and sequestration of greenhouse gases, open-access recreational visits, urban green space, and wild-species diversity. We use spatially explicit models in conjunction with valuation methods to estimate comparable economic values for these services, taking account of climate change impacts. We show that, although decisions that focus solely on agriculture reduce overall ecosystem service values, highly significant value increases can be obtained from targeted planning by incorporating all potential services and their values and that this approach also conserves wild-species diversity.

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling.

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere.

Valuing ecosystem services in terms of ecological risks and returns.

The economic valuation of ecosystem services is a key policy tool in stemming losses of biological diversity. It is proposed that the loss of ecosystem function and the biological resources within ecosystems is due in part to the failure of markets to recognize the benefits humans derive from ecosystems. Placing monetary values on ecosystem services is often suggested as a necessary step in correcting such market failures. We consider the effects of valuing different types of ecosystem services within an economic framework. We argue that provisioning and regulating ecosystem services are generally produced and consumed in ways that make them amenable to economic valuation. The values associated with cultural ecosystem services lie outside the domain of economic valuation, but their worth may be expressed through noneconomic, deliberative forms of valuation. We argue that supporting ecosystem services are not of direct value and that the losses of such services can be expressed in terms of the effects of their loss on the risk to the provision of the directly valued ecosystem services they support. We propose a heuristic framework that considers the relations between ecological risks and returns in the provision of ecosystem services. The proposed ecosystem-service valuation framework, which allows the expression of the value of all types of ecosystem services, calls for a shift from static, purely monetary valuation toward the consideration of trade-offs between the current flow of benefits from ecosystems and the ability of those ecosystems to provide future flows.