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Tracking Ecosystem Service Relationships (e.g. Tradeoffs and Bundles) Introduction

Tracking Ecosystem Service Relationships (e.g. Tradeoffs and Bundles) Introduction Current natural resource decisions do not consider all ecosystem services. This often leads to unintended tradeoffs among services and inequitable distribution of some services.

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Tracking Ecosystem Service Relationships (e.g. Tradeoffs and Bundles) Introduction

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  1. Tracking Ecosystem Service Relationships (e.g. Tradeoffs and Bundles) • Introduction • Current natural resource decisions do not consider all ecosystem services. This often leads to unintended tradeoffs among services and inequitable distribution of some services. • In order for more services to be included in decisions, we need to be able to track them, and their relationships over time. But there are a lot of services, and we don’t understand well how they relate. • The literature is full of conceptual ideas about how services relate (tradeoffs and bundles), with some attempts to address consistencies and differences in these patterns (Elena Bennett, Peterson, etc.). • However, these conceptual and limited experimental or observational cases are not rich enough to deal with all the real complexity of how ecosystem services interact. • Some services always track together in the same way, others do not. Some that do are those that have shared production pathways (sharing same resources/dynamics). Give examples (think about tradeoff curves and see if we just need the shape of the curve instead of whole mechanism. Is shape of curve consistent across our 3 factors). Some do NOT always track together, and we don’t know what drives that. • We first discuss two key issues that will help clarify the discussion of service relationships. We then propose a framework that identifies three factors that generally influence the relationship among ecosystem services. We then provide examples of how using this framework can help predict how services will relate in a given system, and discuss how using this framework can help in the development of metrics and monitoring.

  2. Setting the stage • decision makers and scientists are still sloppy in the way we talk about services. Naming of services needs to be clear and explicit so that the relationship among services can be assessed easily. The distinction here is between things like “forest services” and carbon sequestration for climate regulation or “watershed services” and water purification for drinking. • The relationship among services will likely be affected by the point in the supply chain that you are interested in. Supply/service/value distinction and example of how thinking about different stages gives a different relationship among services.

  3. The Framework • There are three key factors that will likely determine the nature of the relationship among services: scale, starting conditions, and drivers. • Scale • Time • Space • Starting conditions • Social such as wealth, access, institutions, health, food security, water security, etc. Use agriculture example where staring in a place with low food supply, degraded landscape and adding agriculture may enhance many services in addition to food provision (e.g. food, erosion control, carbon storage, water quality, regulation of vector borne disease may all track positively), but increasing agriculture in a more wealthy area may lead to an increase in food alongside a decrease in many of these other services. • Biophysical such as ecosystem type, ecosystem vulnerability or resilience, climate conditions, etc. Use example of carbon:water tradeoff. In native grasslands, carbon goes up as water goes down, in native forest areas, carbon goes up as water goes up. • Driver • Services may track differently in response to climate change than they do in response to land use change. Discuss both general and explicit drivers (e.g. climate • vs. land use change and till vs. no till, etc). • In most cases all three of these are likely interacting, but knowing about these three things will likely determine how services relate.

  4. Examples • 2-3 examples that demonstrate the point. Make sure to address all 3 factors, but don’t have to get all 3 into each example. • Conclusions • After we’ve thought this all out, are there direct lessons that can be applied to identifying indicators or choosing metrics? • Discuss how this hypothesis should be tested with extensive review of existing examples, and with new wok. • Discuss how this will help in development of consistent protocols for emerging global assessment platforms, small scale efforts, government processes, etc.

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