SCALEFORES: Scaling Rules For Ecosystem Service Mapping

Projektinformationen

SCALEFORES

ID Finanzhilfevereinbarung: 680176

DOI

10.3030/680176

Projekt abgeschlossen

EK-Unterschriftsdatum 22 Dezember 2015

Startdatum 1 Juli 2016

Enddatum 31 Mai 2023

Finanziert unter

• EXCELLENT SCIENCE - European Research Council (ERC)

Gesamtkosten

€ 1 483 096,00

EU-Beitrag

€ 1 483 096,00

Koordiniert durch

UNIVERSITY OF SOUTHAMPTON
United Kingdom

Periodic Reporting for period 5 - SCALEFORES (SCALEFORES: Scaling Rules For Ecosystem Service Mapping)

Berichtszeitraum: 2023-01-01 bis 2023-05-31

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

Land is a limited resource that must fulfil multiple functions. The big question is, how can we meet growing human demand for resources and ensure human well-being, without impairing biodiversity and ecosystem functions?

Such questions necessitate a landscape ecological approach, on the principle that ecosystem composition, structure and function partially depend on the spatial (and temporal) context of the ecosystem (i.e. its landscape context).

In the SCALEFORES project we adopt a landscape ecological approach to study a wide range of ecosystem services. We do empirical analyses of existing biophysical and socioeconomic datasets across broad geographic regions, in addition to spatial simulation modelling, to understand how landscape context affects ecosystem service provision at multiple scales.

The understanding gained from this research should be useful in understanding how to design, protect, and enhance landscapes relative to ecosystem services at multiple scales, and to inform tools for mapping ecosystem services.

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

The original focus of SCALEFORES have focused on developing new statistical methods for understanding how the spatial scale of variables (such as the amount of forest within some distance of pond) affects the aspects of nature most important to people (ecosystem services or natural capital). This led to two two major methodological papers - an analytical framework for cross-scale analysis of the effectivness of management interventions for ecosystem services, and another for maximizing the value of high resolution land cover data for predicting biodiversity outcomes. Both methods were applied in other contexts- the former for deer damage in the UK and bird diversity and bamboo invasions in Japan, and the latter for tree diversity across Europe.

As the project progressed, we become more interested in understanding and predicting land use change itself, as this is ultimately what drives ecosystem service and biodiversity delivery. Here, we came up with a new method for predicting frontiers of agricultural expansion that improves the prediction of future agricultural expansion.

Other major outputs included a systematic map of the impacts of urban greenspace on mental health, and paper looking at the drivers of woody vegetation dynamics across sub-Saharan Africa.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

Our new methods are well beyond the state of the art, as they mean we can now use the 'big data' available from satellites, surveys from government and citizen sciences to understand what management actions work in what places to maintain our ecosystem services and what ones don't.

On-going work is to use one of the methods to understand trade-offs between reforestation for climate change mitigation and increasing the risk of deer damage to existing forests in Scotland.

Graphical abstract of new method for predicting agricultural expansion