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What ecologists should know before using land use/cover change projections for biodiversity and ecosystem service assessments

Abstract

Scenarios of biodiversity and ecosystem services (BES) are key for decision-makers to understand the consequences of future environmental change on BES. Though a major driver of terrestrial biodiversity loss, land use and land cover changes (LUCC) have been largely overlooked in previous BES assessments. But ecologists lack practical guidance for the general use of LUCC projections. We review the practices in use in LUCC-driven BES assessments and summarize the questions ecologists should address before using LUCC projections. LUCC-driven BES scenarios rely on a substantial set of different socioeconomic storylines (> 200 for 166 papers). Studies explore different futures, but generally concentrate on projections obtained from a single LUCC model. The rationale regarding time horizon, spatial resolution, or the set of storylines used is rarely made explicit. This huge heterogeneity and low transparency regarding the what, why, and how of using LUCC projections for the study of BES futures could discourage researchers from engaging in the design of such biodiversity scenarios. Our results call on those using LUCC projections to more systematically report on the choices they make when designing LUCC-based BES scenarios (e.g. time horizon, spatial and thematic resolutions, scope of contrasted futures). Beyond the improvement of reliability, reproducibility, and comparability of these scenarios, this could also greatly benefit others wanting to use the same LUCC projections, and help land use modellers better meet the needs of their intended audiences. The uncertainties in LUCC-driven BES futures should also be explored more comprehensively, including different socioeconomic storylines and different LUCC models, as recommended in studies dealing with climate-driven BES futures.

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Acknowledgements

This work contributes to the Labex OT-Med (no. ANR-11-LABX-0061) funded by the French Government “Investissements d’Avenir” program of the French National Research Agency (ANR) through the A*MIDEX project (no. ANR-11-IDEX-0001-02). We thank N. Dendoncker (Université de Namur, Belgium) and S. Zaehle (Max Planck Institute for Biogeochemistry, Germany) for the data on ALARM and ATEAM scenarios, E. Naiken for his help with the literature review, and F. Jabot for his friendly review of our manuscript.

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Correspondence to Cécile H. Albert.

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Glossary

Archetype

A storyline that is considered to be a perfect or typical example of a particular set of possible futures, because it has all their most important characteristics. Scenarios that have similar storylines could be grouped into few general archetypes.

Backcasting

Process of working backwards from the definition of a possible future (typically a vision), in order to determine what needs to happen to make this future unfold and connect to the present (typically a pathway).

Baseline

Set of reference data used to represent the initial conditions and that serve as a basis to compare alternative scenarios.

Business as usual

Scenario of—or pathway towards—a future considered to be the continuation of the current path.

Downscaling

The process of refining the spatial grain (resolution). For LUCC, downscaling means also incorporating more information on local constraints.

Driver, driving force

The underlying causes of change, affecting or shaping the future. For instance, can be a social (e.g. human population, inequalities), economic (e.g. prices), policy governance (e.g. fair-trade vs. market-based), technological (e.g. rate of innovation), or environmental (e.g. atmospheric CO2) factor.

Extrapolation

Application of a method or conclusion to a new situation assuming that existing trends will continue.

Family

Set of projections that comes from a given modelling team, a modelling framework, or a given research project. Note that our definition differs from the IPCC acception in which families are groups of scenarios following a given storyline (see “archetype”).

Foresight, Prospective

A systematic and multi-disciplinary approach to explore a multitude of mid- to long-term possible futures and drivers of change. Can be used as a guide in formulating public policy.

Participatory

Engaging representatives of local (and regional) actors (stakeholders) whose interests are varied and who may contribute to build visions of the future as a collective endeavour by sharing their know-how and knowledge about their common territory.

Pathway, Trajectory

A sequence of actions, events, and consequences taken over time to reach a specific future situation, or that leads to it.

Plausible

Judged to be reasonable because its underlying assumptions and internal consistency connect to reality.

Projection

An expected value of one indicator at a particular point in the future under a given scenario, based on assumptions regarding selected initial conditions and driving forces, and often computed with the aid of a model. Here, we focus on spatial projections, i.e. maps, of land use/cover at a given time.

Scenario

A description of how the future may unfold according to an explicit, coherent, and internally consistent set of assumptions about key drivers, relationships, and constraints. It is not a forecast about a most likely future state. The word “scenario” encompasses—and is sometimes used instead of—storyline, vision, and projection.

Storyline, Narrative

A coherent and qualitative description of a scenario, highlighting its main characteristics, the relationships between key driving forces and their dynamics.

Thematic resolution

The classification used to describe land use/cover in terms of number of classes and their definitions.

Time horizon, time frame

Farthest point in the future to be considered (e.g. 2080); complete period (past-to-future) of time considered.

Vision

The concise description of what the world might look like at some future time. A consensus can be drawn for a preferred and inspiring future, and a full strategy developed to reach this future (e.g. normative scenario).

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Albert, C.H., Hervé, M., Fader, M. et al. What ecologists should know before using land use/cover change projections for biodiversity and ecosystem service assessments. Reg Environ Change 20, 106 (2020). https://doi.org/10.1007/s10113-020-01675-w

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Keywords

  • Biodiversity modelling
  • Ecosystem services
  • Scenarios
  • Storylines
  • Global change
  • Land cover
  • Species richness
  • Ecological processes