Conference Agenda

Conservation science and economics research determine that wild species provide various valuable ecosystem services (ES) to agricultural production. Whether those services provide a strong incentive to farmers to allocate some land to habitat for those species depends on the characteristics of the land and ES, with Simpson (2019) finding a modest incentive for farmers to conserve habitat. This paper develops a farmer decision model using a set of agricultural production functions that have multiple ecosystem services entering in different observed ways, including synergistically. We use the model to examine how the farmer’s incentive for habitat conservation relates to market access costs for inputs that substitute for ES and varies across settings that provide more than one ES. We find that common market settings in low-income countries and common multiple ES settings can increase the farmer’s optimal habitat conservation. We also explore the response of private habitat conservation and rural incomes to policies that reduce market access costs, make payments for ecosystem services, and conserve public land for habitat. We apply the model to a coffee-growing region in Costa Rica that raises issues about the contribution of off-farm habitat to on-farm agricultural productivity and farmer’s private habitat conservation levels.

Biodiversity provides essential ecosystem services to human welfare, yet the topic is understudied in economic literature. This paper estimates the cost of herbivore biodiversity declines in Southern Africa via the mechanism of bush encroachment, a form of land degradation in which trees and shrubs expand into grasslands used to range cattle. Since wild herbivores control encroachment, biodiversity loss potentially decreases cattle production by reducing available rangeland. We exploit the placement of livestock fencing across Namibia and Botswana as a natural experiment in local biodiversity changes. Using these fences to instrument for encroachment induced by biodiversity loss, we estimate causal impacts on cattle density across the region and find that a one square kilometer increase in shrub cover decreases cattle density by around 7 individuals. These estimates suggest there were around 1.5 million fewer cattle in 2020 compared to 2002, equal to more than 30 million USD in lost trade revenue in 2020 alone. Finally, we use a machine learning algorithm to predict species distributions based on observational data and combine this with expert range maps to examine the role of biodiversity as a driving mechanism.

There is a critical gap in macro-economic modelling, namely the lack of representation of ecosystems and biodiversity. These provide services such as pollination, soil erosion and flood control, which contribute a significant proportion to global GDP. Their omission leads to inaccurate long-term socioeconomic projections, particularly under accelerating environmental change.

This study addresses this gap by explicitly integrating ecosystem services and biodiversity loss into long-term socioeconomic projections under climate change. Building on the European ecosystem accounting standards (SEEA-EA), we evaluate the impact of the decline in available pollination services across the EU using (1) observed trends in wild pollinator populations from European indexes as the EU Butterfly Index and (2) projected declines derived from state-of-the-art climate-driven species distribution models (SDMs) for key pollinator taxa (wild bees, hoverflies, butterflies, beetles). The ecological projections are spatially matched with crop cultivation areas from FAO Cropgrids and pollination dependency ratios for 103 european crops to estimate agricultural productivity losses at high spatial resolution under several climate scenarios (RCP2.6; 4.5; 6.0; 7.0 and 8.5) and socioeconomic pathways (SSP1; 2; 3; 5) up to 2070. These biophysical impacts are translated into second-order economic shocks using a regionalized version of the ICES Computable General Equilibrium (CGE) model (GTAP11), enabling assessment of macroeconomic consequences at NUTS2-level resolution. A conservation policy scenario is also evaluated, representing the implementation of main EU conservation policies available to date (Common Agricultural Policy (CAP), Nature Restoration Law, Natura2000 network). This scenario assumes stabilization and restoration of pollination potential to match 1990 levels in the absence of climate change, reflecting the anticipated effects of EU biodiversity policies through habitat restoration, pesticide reduction, and protected area expansion.

Results highlight the spatial heterogeneity of pollination decline and its disproportionate effects on pollinator-dependent crops across regions, revealing critical vulnerabilities in the EU agricultural systems. Although the aggregate impact on EU GDP remains modest, preliminary results indicate that economic impacts on the agricultural sector could reach up to –2.52% by 2080 relative to a no-climate-change scenario, with several regions experiencing losses exceeding –5%. Sectoral estimates show that numerous regions may face reductions of 9% to 22% of sectoral GDP in the case of Vegetables, fruit, nuts, Oil seeds and Other crops sectors, with effects propagating also to sectors not strictly dependent on pollination. Overall, excluding additional co-benefits such as flood control and soil-erosion mitigation, the conservation policy does not appear cost-efficient, as projected economic costs slightly outweigh the benefits associated with net increases in land productivity.

By stepping into the integration of biodiversity loss within climate-change macroeconomic impact assessment, this study delivers the first long-term evaluation of pollination impacts derived from a multi-model, multi-scenario SDM ensemble. The proposed framework provides a reproducible basis for embedding biodiversity dynamics into economic planning and for informing nature-restoration and climate-adaptation policies.

``No net loss'' policies are increasingly common tools through which governments reduce environmental damage. To function efficiently, these policies require trade, with firms who damage the environment paying for offsetting environmental improvements from other actors. Yet, current trade is hamstrung because the blocky nature of supply and demand for environmental services has yet to be recognised by existing market design solutions. In this paper we propose and test, both in the real world and laboratory, a package market using the Balanced Winners' Contribution rule of Lindsay (2018). Proprietary data from the real world shows that the package market design is highly flexible and can facilitate trade where current approaches fail. The experimental results point to this new market design offering substantial efficiency gains relative to the current approaches applied internationally, suggesting broad applicability of the market.