Fanny Langerwisch

Forest resilience and tipping points at different spatio-temporal scales: approaches and challenges

1. Anthropogenic global change compromises forest resilience, with profound impacts to ecosystem functions and services. This synthesis paper reflects on the current understanding of forest resilience and potential tipping points under environmental change and explores challenges to assessing responses using experiments, observations and models. 2. Forests are changing over a wide range of spatio-temporal scales, but it is often unclear whether these changes reduce resilience or represent a tipping point. Tipping points may arise from interactions across scales, as processes such as climate change, land-use change, invasive species or deforestation gradually erode resilience and increase vulnerability to extreme events. Studies covering interactions across different spatio-temporal scales are needed to further our understanding. 3. Combinations of experiments, observations and process-based models could improve our ability to project forest resilience and tipping points under global change. We discuss uncertainties in changing CO2 concentration and quantifying tree mortality as examples. 4. Synthesis. As forests change at various scales, it is increasingly important to understand whether and how such changes lead to reduced resilience and potential tipping points. Understanding the mechanisms underlying forest resilience and tipping points would help in assessing risks to ecosystems and presents opportunities for ecosystem restoration and sustainable forest management.

Forest resilience, tipping points and global change processes

Summary Anthropogenic global change compromises forest resilience, with profound impacts to ecosystem functions and services. This synthesis paper reflects on the current understanding of forest resilience and potential tipping points under environmental change and explores challenges to assessing responses using experiments, observations and models. Forests are changing over a wide range of spatio-temporal scales, but it is often unclear whether these changes reduce resilience or represent a tipping point. Tipping points may arise from interactions across scales, as processes such as climate change, land-use change, invasive species or deforestation gradually erode resilience and increase vulnerability to extreme events. Studies covering interactions across different spatio-temporal scales are needed to further our understanding. Combinations of experiments, observations and process-based models could improve our ability to project forest resilience and tipping points under global change. We discuss uncertainties in changing CO2 concentration and quantifying tree mortality as examples. Synthesis. As forests change at various scales, it is increasingly important to understand whether and how such changes lead to reduced resilience and potential tipping points. Understanding the mechanisms underlying forest resilience and tipping points would help in assessing risks to ecosystems and presents opportunities for ecosystem restoration and sustainable forest management.

Investigating potential transferability of place-based research in land system science

Much of our knowledge about land use and ecosystem services in interrelated social-ecological systems is derived fromplace-based research.While local and regional case studies provide valuable insights, it is often unclear how relevant this research is beyond the study areas. Drawing generalized conclusions about practical solutions to landmanagement from local observations and formulating hypotheses applicable to other places in the world requires that we identify patterns of land systems that are similar to those represented by the case study. Here, we utilize the previously developed concept of land system archetypes to investigate potential transferability of research from twelve regional projects implemented in a large joint research framework that focus on issues of sustainable landmanagement across four continents. For each project, we characterize its project archetype, i.e. the unique land system based on a synthesis ofmore than 30 datasets of land-use intensity, environmental conditions and socioeconomic indicators.We estimate the transferability potential of project research by calculating the statistical similarity of locations across the world to the project archetype, assuming higher transferability potentials in locations with similar land system characteristics. Results show that areas with high transferability potentials are typically clustered around project sites but for some case studies can be found in regions that are geographically distant, especially when values of considered variables are close to the globalmean or where the project archetype is driven by large-scale environmental or socioeconomic conditions. Using specific examples from the local case studies, we highlight themerit of our approach and discuss the differences between local realities and information captured in global datasets. The proposedmethod provides a blueprint for large research programs to assess potential transferability of place-based studies to other geographical areas and to indicate possible gaps in research efforts. OPEN ACCESS

Large-scale impact of climate change vs. land-use change on future biome shifts in Latin America

Climate change and land-use change are two major drivers of biome shifts causing habitat and biodiversity loss. What is missing is a continental-scale future projection of the estimated relative impacts of both drivers on biome shifts over the course of this century. Here, we provide such a projection for the biodiverse region of Latin America under four socio-economic development scenarios. We find that across all scenarios 5-6% of the total area will undergo biome shifts that can be attributed to climate change until 2099. The relative impact of climate change on biome shifts may overtake land-use change even under an optimistic climate scenario, if land-use expansion is halted by the mid-century. We suggest that constraining land-use change and preserving the remaining natural vegetation early during this century creates opportunities to mitigate climate-change impacts during the second half of this century. Our results may guide the evaluation of socio-economic scenarios in terms of their potential for biome conservation under global change.

The LEGATO cross-disciplinary integrated ecosystem service research framework: an example of integrating research results from the analysis of global change impacts and the social, cultural and economic system dynamics of irrigated rice production

AbstractIn a cross-disciplinary project (LEGATO) combining inter- and transdisciplinary methods, we quantify the dependency of rice-dominated socio-ecological systems on ecosystem functions (ESF) and the ecosystem services (ESS) the integrated system provides. In the collaboration of a large team including geo- and bioscientists, economists, political and cultural scientists, the mutual influences of the biological, climate and soil conditions of the agricultural area and its surrounding natural landscape have been analysed. One focus was on sociocultural and economic backgrounds, another on local as well as regional land use intensity and biodiversity, and the potential impacts of future climate and land use change. LEGATO analysed characteristic elements of three service strands defined by the Millennium Ecosystem Assessment (MA): (a) provisioning services: nutrient cycling and crop production; (b) regulating services: biocontrol and pollination; and (c) cultural services: cultural identity and aesthetics. However, in line with much of the current ESS literature, what the MA called supporting services is treated as ESF within LEGATO. As a core output, LEGATO developed generally applicable principles of ecological engineering (EE), suitable for application in the context of future climate and land use change. EE is an emerging discipline, concerned with the design, monitoring and construction of ecosystems and aims at developing strategies to optimise ecosystem services through exploiting natural regulation mechanisms instead of suppressing them. Along these lines LEGATO also aims to create the knowledge base for decision-making for sustainable land management and livelihoods, including the provision of the corresponding governance and management strategies, technologies and system solutions.

Rice ecosystem services in South-east Asia

Josef Settele · Kong Luen Heong · Ingolf Kühn · Stefan Klotz · Joachim H. Spangenberg · Gertrudo Arida · Alexis Beaurepaire · Silke Beck · Erwin Bergmeier · Benjamin Burkhard · Roland Brandl · Jesus Victor Bustamante · Adam Butler · Jimmy Cabbigat · Xuan Canh Le · Josie Lynn A. Catindig · Van Chien Ho · Quoc Cuong Le · Kinh Bac Dang · Monina Escalada · Christophe Dominik · Markus Franzén · Oliver Fried · Christoph Görg · Volker Grescho · Sabine Grossmann · Geoff M. Gurr · Buyung A. R. Hadi · Huu Hai Le · Alexander Harpke · Annika L. Hass · Norbert Hirneisen · Finbarr G. Horgan · Stefan Hotes · Yuzuru Isoda · Reinhold Jahn · Helen Kettle · Anika Klotzbücher · Thimo Klotzbücher · Fanny Langerwisch · Wai‐Hong Loke · Yu‐Pin Lin · Zhongxian Lu · Keng‐Yeang Lum · Damasa B. Magcale‐Macandog · Glenn Marion · Leonardo Marquez · Felix Müller · Hung Manh Nguyen · Quynh Anh Nguyen · Van Sinh Nguyen · Jürgen Ott · Lyubomir Penev · Hong Thai Pham · Nico Radermacher · Beatriz Rodriguez‐Labajos · Christina Sann · Cornelia Sattler · Martin Schädler · Stefan Scheu · Anja Schmidt · Julian Schrader · Oliver Schweiger · Ralf Seppelt · Kukiat Soitong · Pavel Stoev · Susanne Stoll‐Kleemann · Vera Tekken · Kirsten Thonicke · Bianca Tilliger · Kai Tobias · Y. Andi Trisyono · Thanh Truong Dao · Teja Tscharntke · Quang Tuan Le · Manfred Türke · Tomáš Václavík · Doris Vetterlein · Sylvia ’Bong’ Villareal · Kim Chi Vu · Quynh Vu · Wolfgang W. Weisser · Catrin Westphal · Zengrong Zhu · Martin Wiemers

LPJmL4 – a dynamic global vegetation model with managed land – Part 1: Model description

This paper provides a comprehensive description of the newest version of the Dynamic Global Vegetation Model with managed Land, LPJmL4. This model simulates internally consistently the growth and productivity of both natural and agricultural vegetation in coherently linked through their water, carbon and energy fluxes. These features render LPJmL4 suitable for assessing a broad range 5 of feedbacks within, and impacts upon, the terrestrial biosphere as increasingly shaped by human activities such as climate change and land-use change. Here we describe the core model structure including recently developed modules now unified in LPJmL4. Thereby, we also review LPJmL model developments and evaluations in the field of permafrost, human and ecological water demand and improved representation of crop types. We summarize and discuss LPJmL model applications 10 dealing with impacts of historical and future environmental change on the terrestrial biosphere at regional and global scale and provide a comprehensive overview over LPJmL publications since the first model description in 2007. To demonstrate the main features of the LPJmL4 model, we display reference simulation results for key processes such as the current global distribution of natural and managed ecosystems, their productivities, and associated water fluxes. A thorough evaluation of 15 the model is provided in a companion paper. By making the model source code freely available at https://gitlab.pik-potsdam.de/lpjml/LPJmL, we hope to stimulate the application and further development of LPJmL4 across scientific communities, not least in support of major activities such as the IPCC and SDG process.

Assessing carbon dynamics in Amazonia with the Dynamic Global Vegetation Model LPJmL - discharge evaluation

et al. 2006).A substantial, globally significant carbon flow exists be-tween the atmosphere, land ecosystems, and aquatic ecosys-tems in the Amazon basin, probably leading to a major, yet poorly constrained carbon export to the Tropical Atlantic. One estimate of the annual export of carbon to the ocean is 40 Tg C/yr (M