Summary1. Spatially explicit understanding of the delivery of multiple ecosystem services (ES) from global to local scales is currently limited. New studies analysing the simultaneous provision of multiple services at landscape scale should aid the understanding of multiple ES delivery and trade-offs to support policy, management and land planning. 2. Here, we propose a new approach for the analysis, mapping and understanding of multiple ES delivery in landscapes. Spatially explicit single ES models based on plant traits and abiotic characteristics are combined to identify 'hot' and 'cold' spots of multiple ES delivery, and the land use and biotic determinants of such distributions. We demonstrate the value of this trait-based approach as compared to a pure land-use approach for a pastoral landscape from the central French Alps, and highlight how it improves understanding of ecological constraints to, and opportunities for, the delivery of multiple services. 3. Vegetative height and leaf traits such as leaf dry matter content were response traits strongly influenced by land use and abiotic environment, with follow-on effects on several ecosystem properties, and could therefore be used as functional markers of ES. 4. Patterns of association among ES were related to the dominant traits underlying different ecosystem properties. The functional decoupling between height and leaf traits provided alternative pathways for high agronomic value, as well as determining hot and cold spots of ES. Traditional land uses such as organic fertilization and mowing or altitude summer grazing were also linked with ES hot spots, because functional characteristics supporting fodder production and quality are compatible with species and functional diversity. 5. Synthesis. Analyses of ES using plant functional variation across landscapes are a powerful approach to understanding the fundamental ecological mechanisms underlying ES provision, and trade-offs or synergies among services. Sustainable management of species and functionally diverse grassland could simultaneously aim at conserving biodiversity and locally important ES by taking advantage of correlations and trade-offs among different plant functional traits.

Greening roofs or walls to cool down city areas during summer, to capture storm water, to abate pollution, and to increase human well-being while enhancing biodiversity: nature-based solutions (NBS) refer to the sustainable management and use of nature for tackling societal challenges. Building on and comple- menting traditional biodiversity conservation and management strategies, NBS integrate science, policy, and practice and create biodiversity benefits in terms of diverse, well-managed ecosystems.

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Background: Vector-borne and zoonotic diseases generally display clear spatial patterns due to different space-dependent factors. Land cover and land use influence disease transmission by controlling both the spatial distribution of vectors or hosts, and the probability of contact with susceptible human populations. The objective of this study was to combine environmental and socio-economic factors to explain the spatial distribution of two emerging human diseases in Belgium, Puumala virus (PUUV) and Lyme borreliosis. Municipalities were taken as units of analysis.

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Land use and climate change are primary causes of changes in the supply of ecosystem services (ESs). Although the consequences of climate change on ecosystem properties and associated services are well documented, the cascading impacts of climate change on ESs through changes in land use are largely overlooked. We present a trait-based framework based on an empirical model to elucidate how climate change affects tradeoffs among ESs. Using alternative scenarios for mountain grasslands, we predicted how direct effects of climate change on ecosystems and indirect effects through farmers' adaptations are likely to affect ES bundles through changes in plant functional properties. ES supply was overall more sensitive to climate than to induced management change, and ES bundles remained stable across scenarios. These responses largely reflected the restricted extent of management change in this constrained system, which was incorporated when scaling up plot level climate and management effects on ecosystem properties to the entire landscape. The trait-based approach revealed how the combination of common driving traits and common responses to changed fertility determined interactions and tradeoffs among ESs.plant functional traits | trade-offs | global change | mountain agriculture E cosystem services (ESs) are increasingly used to assess and make land and natural resource use decisions that typically involve tradeoffs between conflicting goals and, in particular, between the different bundles of services that a given ecosystem could provide. These decisions are, however, rarely grounded in a mechanistic understanding of the ecosystem properties or processes that enable provision of multiple ESs. At the same time, mechanisms leading to tradeoffs among ESs are still poorly understood (1). Effective ES-based management decisions, especially in a climate-change context, require that we go beyond the description of spatial co-occurrences of targeted ESs under current climates (e.g., refs. 2 and 3) to understand direct interactions between ESs, and the effects of common drivers of change in ESs (4).A mechanistic approach to ES supply will be grounded in the relevant characteristics of the ecosystem components that contribute to it. Functional traits of ES providers are novel and powerful proxies (5, 6) that make it possible to scale wellunderstood functional tradeoffs from the organism level to ecosystem functioning and to ESs (7,8). Their relevance to ES modeling rests on the discovery that response functional traits that determine community response (e.g., fertilization favors plants with nitrogenrich leaves) overlap with effect functional traits that determine effects on ecosystem functioning (e.g., a majority of nitrogen-rich leaves promotes high primary productivity) (9).Scenario-based studies have compared bundles of ESs, and associated positive and negative relationships, across scenarios (10), but few published studies have sought to tease out the respective effects of different scenario drivers. Large-scale studies...