The concept of ecosystem services (ES) remains underused in supporting practical decisions in conservation/development plans and programs. One of the most important factors explaining this non-consideration is the lack of spatial information describing the naturesociety relationship in environmental and economic analyses. In this paper, we developed a novel method to predict, in spatially explicit terms, the recreation attractiveness potential combining supply and demand factors. Our method is based on the combination and transfer of a Lancasterian function of biophysical aspects and a travel cost model based on agents' sociodemographic characteristics. We further validate the usefulness of the proposed recreation model by using it in the evaluation of a regional park charter pursuing two main objectives: recreational attractiveness and habitat quality (modeled with InVEST). The results demonstrate first that the biophysical context plays a large role in the recreational trip choice and thus should not be ignored in travel cost studies. Second, from a policy guidance perspective, we show that providing spatial information appears particularly critical for ES to be a useful lever for action in day-today decision-making.

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We refer to jobs that promote biodiversity as bio-jobs. These jobs are located in a small number of sectors generally linked to natural resources: naturalist research, forestry, public works, water and waste management, etc. In this article, we examine two economic policies favouring the development of these bio-jobs. The government can support demand in sectors with bio-jobs through public procurement or can develop them through targeted exemptions. The most effective and relevant combination of these instruments is investigated via an original framework. We show that the government's action is driven by the nature of the sectors and especially by the level of any existing private demand. Then, the level of the wages plays a major role in the government's budget decision. Finally, we apply these recommendations to French data.

À partir d’une analyse monographique des secteurs d’activités franciliens, nous sommes en mesure de recenser le nombre d’emplois dont l’activité est entièrement, ou pour partie, favorable à la biodiversité en Île-de-France et celui des emplois indirects à l’échelle nationale. Ils représentent aujourd’hui 1 emploi sur 1000 en Île-de-France, soit 5090 bio-emplois en effectifs occupés (EO). Ils se répartissent, à plus de 70 %, entre les activités associatives, les activités de recherche et développement et l’administration publique. À cela s’ajoutent 2 355 emplois indirects en EO, soit un total de 7 450 bio-emplois directs et indirects en EO. Nous explorons ensuite des scénarios de politique régionale visant à soutenir ces bio-emplois.

Climate change (CC) and land use and land cover change (LULCC) threaten Mediterranean forests and the ecosystem services (ES) they provide. In complex socio-ecological systems and under high uncertainties, the resilience of ES has become the target objective for adaptive management strategies driven by decision makers and local stakeholders. This work develops an integrative and territorial approach to combining biophysical modeling and local managers' assessments to elaborate scenarios of LULCC in response to climate and socioeconomic changes. It also evaluates the impacts of forest ecosystem changes on coupled ES for different time horizons for a case study of the mountain Mediterranean forests of Mont-Ventoux Natural Regional Park. The results demonstrate first that the future ES provisions predicted by biophysical modeling in this area are less affected by CC than expected by local managers. Furthermore, LULCC increases the changes in ES provision and accentuates the difference between climate scenarios. These results originate from a combination of two effects:(1) pessimistic predictions by local managers and, as a consequence and (2) anticipatory actions that tend to reinforce or even accelerate the expected changes in the mountain Mediterranean forest area.