29 research outputs found
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Climate change increases riverine carbon outgassing, while export to the ocean remains uncertain
Any regular interaction of land and river during flooding affects carbon pools within the terrestrial system, riverine carbon and carbon exported from the system. In the Amazon basin carbon fluxes are considerably influenced by annual flooding, during which terrigenous organic material is imported to the river. The Amazon basin therefore represents an excellent example of a tightly coupled terrestrial–riverine system. The processes of generation, conversion and transport of organic carbon in such a coupled terrigenous–riverine system strongly interact and are climate-sensitive, yet their functioning is rarely considered in Earth system models and their response to climate change is still largely unknown. To quantify regional and global carbon budgets and climate change effects on carbon pools and carbon fluxes, it is important to account for the coupling between the land, the river, the ocean and the atmosphere. We developed the RIVerine Carbon Model (RivCM), which is directly coupled to the well-established dynamic vegetation and hydrology model LPJmL, in order to account for this large-scale coupling. We evaluate RivCM with observational data and show that some of the values are reproduced quite well by the model, while we see large deviations for other variables. This is mainly caused by some simplifications we assumed. Our evaluation shows that it is possible to reproduce large-scale carbon transport across a river system but that this involves large uncertainties. Acknowledging these uncertainties, we estimate the potential changes in riverine carbon by applying RivCM for climate forcing from five climate models and three CO2 emission scenarios (Special Report on Emissions Scenarios, SRES). We find that climate change causes a doubling of riverine organic carbon in the southern and western basin while reducing it by 20% in the eastern and northern parts. In contrast, the amount of riverine inorganic carbon shows a 2- to 3-fold increase in the entire basin, independent of the SRES scenario. The export of carbon to the atmosphere increases as well, with an average of about 30%. In contrast, changes in future export of organic carbon to the Atlantic Ocean depend on the SRES scenario and are projected to either decrease by about 8.9% (SRES A1B) or increase by about 9.1% (SRES A2). Such changes in the terrigenous–riverine system could have local and regional impacts on the carbon budget of the whole Amazon basin and parts of the Atlantic Ocean. Changes in riverine carbon could lead to a shift in the riverine nutrient supply and pH, while changes in the exported carbon to the ocean lead to changes in the supply of organic material that acts as a food source in the Atlantic. On larger scales the increased outgassing of CO2 could turn the Amazon basin from a sink of carbon to a considerable source. Therefore, we propose that the coupling of terrestrial and riverine carbon budgets should be included in subsequent analysis of the future regional carbon budget
Farming system archetypes help explain the uptake of agri-environment practices in Europe
The adoption of agri-environment practices (AEPs) is crucial for safeguarding the long-term sustainability of ecosystem services within European agricultural landscapes. However, the tailoring of agri-environment policies to the unique characteristics of farming systems is a challenging task, often neglecting local farm parameters or requiring extensive farm survey data. Here, we develop a simplified typology of farming system archetypes (FSAs), using field-level data on farms' economic size and specialisation derived from the Integrated Administration and Control System in three case studies in Germany, Czechia and the United Kingdom. Our typology identifies groups of farms that are assumed to react similarly to agricultural policy measures, bridging the gap between efforts to understand individual farm behaviour and broad agri-environmental typologies. We assess the usefulness of our approach by quantifying the spatial association of identified archetypes of farming systems with ecologically relevant AEPs (cover crops, fallow, organic farming, grassland maintenance, vegetation buffers, conversion of cropland to grassland and forest) to understand the rates of AEP adoption by different types of farms. Our results show that of the 20 archetypes, economically large farms specialised in general cropping dominate the agricultural land in all case studies, covering 56% to 85% of the total agricultural area. Despite regional differences, we found consistent trends in AEP adoption across diverse contexts. Economically large farms and those specialising in grazing livestock were more likely to adopt AEPs, with economically larger farms demonstrating a proclivity for a wider range of measures. In contrast, economically smaller farms usually focused on a narrower spectrum of AEPs and, together with farms with an economic value <2 000 EUR, accounted for 70% of all farms with no AEP uptake. These insights indicate the potential of the FSA typology as a framework to infer key patterns of AEP adoption, thus providing relevant information to policy-makers for more direct identification of policy target groups and ultimately for developing more tailored agri-environment policies
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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 as coherently linked through their water, carbon, and energy fluxes. These features render LPJmL4 suitable for assessing a broad range 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 dealing with the impacts of historical and future environmental change on the terrestrial biosphere at regional and global scale and provide a comprehensive overview of 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 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 in support of major activities such as the IPCC and SDG process
Farming system archetypes help explain the uptake of agri-environment practices in Europe
The adoption of agri-environment practices (AEPs) is crucial for safeguarding the long-term sustainability of ecosystem services within European agricultural landscapes. However, the tailoring of agri-environment policies to the unique characteristics of farming systems is a challenging task, often neglecting local farm parameters or requiring extensive farm survey data. Here, we develop a simplified typology of farming system archetypes (FSAs), using field-level data on farms' economic size and specialisation derived from the Integrated Administration and Control System in three case studies in Germany, Czechia and the United Kingdom. Our typology identifies groups of farms that are assumed to react similarly to agricultural policy measures, bridging the gap between efforts to understand individual farm behaviour and broad agri-environmental typologies. We assess the usefulness of our approach by quantifying the spatial association of identified archetypes of farming systems with ecologically relevant AEPs (cover crops, fallow, organic farming, grassland maintenance, vegetation buffers, conversion of cropland to grassland and forest) to understand the rates of AEP adoption by different types of farms. Our results show that of the 20 archetypes, economically large farms specialised in general cropping dominate the agricultural land in all case studies, covering 56% to 85% of the total agricultural area. Despite regional differences, we found consistent trends in AEP adoption across diverse contexts. Economically large farms and those specialising in grazing livestock were more likely to adopt AEPs, with economically larger farms demonstrating a proclivity for a wider range of measures. In contrast, economically smaller farms usually focused on a narrower spectrum of AEPs and, together with farms with an economic value <2 000 EUR, accounted for 70% of all farms with no AEP uptake. These insights indicate the potential of the FSA typology as a framework to infer key patterns of AEP adoption, thus providing relevant information to policy-makers for more direct identification of policy target groups and ultimately for developing more tailored agri-environment policies
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 as coherently linked through their water, carbon, and energy fluxes. These features render LPJmL4 suitable for assessing a broad range 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 dealing with the impacts of historical and future environmental change on the terrestrial biosphere at regional and global scale and provide a comprehensive overview of 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 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 in support of major activities such as the IPCC and SDG process
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
Climate change increases riverine carbon outgassing, while export to the ocean remains uncertain
Any regular interaction of land and river during flooding affects carbon
pools within the terrestrial system, riverine carbon and carbon exported
from the system. In the Amazon basin carbon fluxes are considerably
influenced by annual flooding, during which terrigenous organic material is
imported to the river. The Amazon basin therefore represents an excellent
example of a tightly coupled terrestrial–riverine system. The processes of
generation, conversion and transport of organic carbon in such a coupled
terrigenous–riverine system strongly interact and are climate-sensitive, yet
their functioning is rarely considered in Earth system models and their
response to climate change is still largely unknown. To quantify regional
and global carbon budgets and climate change effects on carbon pools and
carbon fluxes, it is important to account for the coupling between the land,
the river, the ocean and the atmosphere. We developed the RIVerine
Carbon Model (RivCM), which is directly coupled to the well-established dynamic
vegetation and hydrology model LPJmL, in order to account for this large-scale coupling. We evaluate RivCM with observational data and show that some
of the values are reproduced quite well by the model, while we see large
deviations for other variables. This is mainly caused by some
simplifications we assumed. Our evaluation shows that it is possible to
reproduce large-scale carbon transport across a river system but that this involves large uncertainties. Acknowledging these uncertainties, we estimate the
potential changes in riverine carbon by applying RivCM for climate forcing
from five climate models and three CO<sub>2</sub> emission scenarios (Special Report on Emissions Scenarios, SRES). We
find that climate change causes a doubling of riverine organic carbon in the
southern and western basin while reducing it by 20 % in the eastern and
northern parts. In contrast, the amount of riverine inorganic carbon shows a
2- to 3-fold increase in the entire basin, independent of the SRES scenario.
The export of carbon to the atmosphere increases as well, with an average of
about 30 %. In contrast, changes in future export of organic carbon to the
Atlantic Ocean depend on the SRES scenario and are projected to either
decrease by about 8.9 % (SRES A1B) or increase by about 9.1 % (SRES A2).
Such changes in the terrigenous–riverine system could have local and
regional impacts on the carbon budget of the whole Amazon basin and parts of
the Atlantic Ocean. Changes in riverine carbon could lead to a shift in
the riverine nutrient supply and pH, while changes in the exported carbon to
the ocean lead to changes in the supply of organic material that acts as a
food source in the Atlantic. On larger scales the increased outgassing of
CO<sub>2</sub> could turn the Amazon basin from a sink of carbon to a considerable source. Therefore, we propose that the coupling of terrestrial and riverine carbon budgets should be included in subsequent analysis of the future
regional carbon budget
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Potential effects of climate change on inundation patterns in the Amazon Basin
Floodplain forests, namely the Várzea and Igapó, cover an area of more than 97 000 km2. A key factor for their function and diversity is annual flooding. Increasing air temperature and higher precipitation variability caused by climate change are expected to shift the flooding regime during this century, and thereby impact floodplain ecosystems, their biodiversity and riverine ecosystem services. To assess the effects of climate change on the flooding regime, we use the Dynamic Global Vegetation and Hydrology Model LPJmL, enhanced by a scheme that realistically simulates monthly flooded area. Simulation results of discharge and inundation under contemporary conditions compare well against site-level measurements and observations. The changes of calculated inundation duration and area under climate change projections from 24 IPCC AR4 climate models differ regionally towards the end of the 21st century. In all, 70% of the 24 climate projections agree on an increase of flooded area in about one third of the basin. Inundation duration increases dramatically by on average three months in western and around one month in eastern Amazonia. The time of high- and low-water peak shifts by up to three months. Additionally, we find a decrease in the number of extremely dry years and in the probability of the occurrence of three consecutive extremely dry years. The total number of extremely wet years does not change drastically but the probability of three consecutive extremely wet years decreases by up to 30% in the east and increases by up to 25% in the west. These changes implicate significant shifts in regional vegetation and climate, and will dramatically alter carbon and water cycles
Deforestation in Amazonia impacts riverine carbon dynamics
Fluxes of organic and inorganic carbon within the Amazon basin are
considerably controlled by annual flooding, which triggers the export of
terrigenous organic material to the river and ultimately to the Atlantic
Ocean. The amount of carbon imported to the river and the further conversion,
transport and export of it depend on temperature, atmospheric CO<sub>2</sub>,
terrestrial productivity and carbon storage, as well as discharge. Both
terrestrial productivity and discharge are influenced by climate and land
use change. The coupled LPJmL and RivCM model system (Langerwisch et
al., 2016) has been applied to assess the combined impacts of climate and
land use change on the Amazon riverine carbon dynamics. Vegetation dynamics
(in LPJmL) as well as export and conversion of terrigenous carbon to and
within the river (RivCM) are included. The model system has been applied for
the years 1901 to 2099 under two deforestation scenarios and with climate
forcing of three SRES emission scenarios, each for five climate models. We
find that high deforestation (business-as-usual scenario) will strongly decrease (locally by up to 90 %) riverine particulate and dissolved organic carbon amount until the end of the current century. At the same time, increase in discharge leaves net carbon transport during the first decades of the century roughly unchanged only if a sufficient area is still forested. After 2050 the amount of transported carbon will decrease drastically. In contrast to that, increased temperature and atmospheric CO<sub>2</sub> concentration determine the amount of riverine inorganic carbon stored in the Amazon basin. Higher atmospheric CO<sub>2</sub> concentrations increase riverine inorganic carbon amount by up to 20 % (SRES A2). The changes in riverine carbon fluxes have direct effects on carbon export, either to the atmosphere via outgassing or to the Atlantic Ocean via discharge. The outgassed carbon will increase slightly in the Amazon basin, but can be regionally reduced by up to 60 % due to deforestation. The discharge of organic carbon to the ocean will be reduced by about 40 % under the most severe deforestation and climate change scenario. These changes would have local and regional consequences on the carbon balance and habitat characteristics in the Amazon basin itself as well as in the adjacent Atlantic Ocean