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biospheremetrics v1.0.1: An R package to calculate two complementary terrestrial biosphere integrity indicators: human colonization of the biosphere (BioCol) and risk of ecosystem destabilization (EcoRisk)

Authors
/persons/resource/stenzel

Stenzel,  Fabian
Potsdam Institute for Climate Impact Research;

/persons/resource/Johanna.Braun

Braun,  Johanna
Potsdam Institute for Climate Impact Research;

/persons/resource/jannes.breier

Breier,  Jannes
Potsdam Institute for Climate Impact Research;

Erb,  Karlheinz
External Organizations;

/persons/resource/Dieter.Gerten

Gerten,  Dieter
Potsdam Institute for Climate Impact Research;

Heinke,  Jens
External Organizations;

Matej,  Sarah
External Organizations;

/persons/resource/sebastian.ostberg

Ostberg,  Sebastian
Potsdam Institute for Climate Impact Research;

/persons/resource/Sibyll.Schaphoff

Schaphoff,  Sibyll
Potsdam Institute for Climate Impact Research;

/persons/resource/Wolfgang.Lucht

Lucht,  Wolfgang
Potsdam Institute for Climate Impact Research;

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Citation

Stenzel, F., Braun, J., Breier, J., Erb, K., Gerten, D., Heinke, J., Matej, S., Ostberg, S., Schaphoff, S., Lucht, W. (in press): biospheremetrics v1.0.1: An R package to calculate two complementary terrestrial biosphere integrity indicators: human colonization of the biosphere (BioCol) and risk of ecosystem destabilization (EcoRisk). - Geoscientific Model Development.


Cite as: https://publications.pik-potsdam.de/pubman/item/item_29646
Abstract
Ecosystems are under multiple stressors and impacts can be measured with multiple variables. Humans have altered mass and energy flows of basically all ecosystems on Earth towards dangerous levels. However, integrating the data and synthesizing conclusions is becoming more and more complicated. Here we present an automated and easy to apply R package to assess terrestrial biosphere integrity which combines 2 complementary metrics: The BioCol metric quantifies the human colonization pressure exerted on the biosphere through alteration and extraction (appropriation) of net primary productivity, whereas the EcoRisk metric quantifies biogeochemical and vegetation structural changes as a proxy for the risk of ecosystem destabilization. Applied to simulations with the dynamic global vegetation model LPJmL5 for 1500–2016, we find that presently (period 2007–2016), large regions show modification and extraction of >25 % of the preindustrial potential net primary production, leading to drastic alterations in key ecosystem properties and suggesting a high risk for ecosystem destabilization. In consequence of these dynamics, EcoRisk shows particularly high values in regions with intense land use and deforestation, but also in regions prone to impacts of climate change such as the arctic and boreal zone. The metrics presented here enable global-scale, spatially explicit evaluation of historical and future states of the biosphere and are designed for use by the wider scientific community, not only limited to assessing biosphere integrity, but also to benchmark model performance. The package will be maintained on GitHub and through that we encourage application also to other models and data sets.