LandscapeDNDC: a process model for simulation of biosphere–atmosphere–hydrosphere exchange processes at site and regional scale

Haas, Edwin; Klatt, Steffen; Fröhlich, A.; Kraft, Philipp; Werner, Christian; Kiese, Ralf; Grote, Rüdiger; Breuer, Lutz; Butterbach‐Bahl, Klaus

doi:10.1007/s10980-012-9772-x

Cited by 152 publications

(148 citation statements)

References 61 publications

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“…It is designed for simulating ecosystem C and N turnover and losses including associated changes in the C and N stocks of soils (Haas et al 2013). A particularly strong part of the model is the detailed description of ecosystem nitrogen processes, including trace gas emission and leaching.…”

Section: Landscapedndc Modelmentioning

confidence: 99%

“…Here, we use data from eight long-term forest ecosystem monitoring stations in Austria with different N status to calibrate a physiologically oriented ecosystem model (LandscapeDNDC) with a detailed soil process description (Haas et al 2013;MolinaHerrera et al 2015). We hypothesise that in temperate forest ecosystems, climate warming will increase tree growth and will enhance N mineralization and nitrification.…”

Section: Introductionmentioning

confidence: 99%

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Historic nitrogen deposition determines future climate change effects on nitrogen retention in temperate forests

et al. 2017

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Nitrogen (N) cycle processes in terrestrial ecosystems are highly sensitive to temperature and soil moisture variations. Thus, future climate change may affect the degree to which N deposited from the atmosphere will be retained in forest ecosystems. We evaluated the effect of future changes in climate and N deposition on ecosystem N cycling using the model LandscapeDNDC forced with historical data from eight long-term forest ecosystem monitoring stations in Austria and downscaled future N deposition and climate scenarios. With every 1°C of warming, annual N uptake in biomass increased by +0.03 to +0.54 kg N ha , and mean annual N leaching was between −0.09 and −2.03 kg N ha −1 lower. The magnitude of N deposition in the years from 1990 to 2010 was by far the most important determinant of the response of nitrogen cycling to future warming, including statistically significant relationships with humus N content and N leaching. We conclude that climate change will likely increase ecosystem N retention in temperate forest ecosystems, and even more so at forest sites with high past N deposition.

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Section: Landscapedndc Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Historic nitrogen deposition determines future climate change effects on nitrogen retention in temperate forests

et al. 2017

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“…For many European based studies investigating the spatial aspects of biomass production, the Corine land cover dataset (CLC) [38] is used as a base layer to identify the distribution of arable land used within a particular region [39]. This is then overlaid with other geo datasets containing information on various environmental properties (e.g., soil type, annual rainfall, temperature) [31,39].…”

Section: What Is Relca?mentioning

confidence: 99%

RELCA: a REgional Life Cycle inventory for Assessing bioenergy systems within a region

O’Keeffe¹,

Wochele-Marx²,

Thrän

2016

Energ Sustain Soc

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Background: The last decade has seen major development and adoption of bioenergy, particularly in Germany. This has resulted in a scattering of decentralised bioenergy plants across the landscape, due to their dependency on spatially diffuse biomass resources. Regional conditions (e.g., soils, climate, management) influence the environmental burdens resulting from biomass production and thus, also effect the environmental performance of bioenergy production. Therefore, more regionally focused life cycle approaches are required for assessing these bioenergy systems. The aim of this paper is to outline such an approach. "RELCA", is a regional life cycle inventory for assessing the regional and spatial variation in the environmental performance of bioenergy production within a region. Methods: Five modelling steps are combined to form the RELCA approach in order to determine: (1) regional crop allocation, (2) regional biomass management, (3) representative bioenergy plant models, (4) bioenergy plant catchments, and (5) indirect upstream emissions (non-regional) associated with regional bioenergy production. The challenges and options for each of these five modelling steps are outlined. Additionally, a simple example is provided using greenhouse gases emissions (GHG) to show how RELCA can be used to identify the potential regional distribution of environmental burdens associated with the production of a bioenergy product (e.g. biodiesel) within a region. Results: An approach for combining regionally distributed inventory for biomass production with regionally distributed inventory for bioenergy technologies, through the use of catchment delineation was developed. This enabled the introduction of greater regional details within the life cycle approach. As a first "proof of concept," GHG emissions were estimated for a simple example, illustrating how RELCA can identify the potential regional distribution of environmental burdens (direct and indirect) associated with producing a bioenergy product. Conclusions: RELCA (v1.0) is a powerful scoping approach, which is the first to investigate the regional and spatial variation in the environmental performance of bioenergy production within a region through the use of catchment delineation. RELCA (v1.0) is not without its limitations. Despite these, it still provides a good starting point for further discussion, improvements, and modelling developments for assessing the regional and spatial environmental implications of bioenergy production (e.g., such as impacts to soil, water, and biodiversity) for a within regional context .

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“…LandscapeDNDC (Haas et al, 2012) describes microclimate, water cycle, plant physiological processes, soil biogeochemistry and silvicultural properties (such as height, diameter and number of trees). The soil biogeochemical part has been recoded from the agricultural DeNitrificationDeComposition (DNDC) model and its forest adaptation PnET-N-DNDC (Li et al, 1992(Li et al, , 2000.…”

Section: Landscapedndcmentioning

confidence: 99%

Environmental change impacts on the C- and N-cycle of European forests: a model comparison study

et al. 2013

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Forests are important components of the greenhouse gas balance of Europe. There is considerable uncertainty about how predicted changes to climate and nitrogen deposition will perturb the carbon and nitrogen cycles of European forests and thereby alter forest growth, carbon sequestration and N₂O emission. The present study aimed to quantify the carbon and nitrogen balance, including the exchange of greenhouse gases, of European forests over the period 2010–2030, with a particular emphasis on the spatial variability of change. The analysis was carried out for two tree species: European beech and Scots pine. For this purpose, four different dynamic models were used: BASFOR, DailyDayCent, INTEGRATOR and Landscape-DNDC. These models span a range from semi-empirical to complex mechanistic. Comparison of these models allowed assessment of the extent to which model predictions depended on differences in model inputs and structure. We found a European average carbon sink of 0.160 ± 0.020 kgC m⁻² yr⁻¹ (pine) and 0.138 ± 0.062 kgC m⁻² yr⁻¹ (beech) and N₂O source of 0.285 ± 0.125 kgN ha⁻¹ yr⁻¹ (pine) and 0.575 ± 0.105 kgN ha⁻¹ yr⁻¹ (beech). The European average greenhouse gas potential of the carbon sink was 18 (pine) and 8 (beech) times that of the N₂O source. Carbon sequestration was larger in the trees than in the soil. Carbon sequestration and forest growth were largest in central Europe and lowest in northern Sweden and Finland, N. Poland and S. Spain. No single driver was found to dominate change across Europe. Forests were found to be most sensitive to change in environmental drivers where the drivers were limiting growth, where changes were particularly large or where changes acted in concert. The models disagreed as to which environmental changes were most significant for the geographical variation in forest growth and as to which tree species showed the largest rate of carbon sequestration. Pine and beech forests were found to have differing sensitivities to environmental change, in particular the response to changes in nitrogen and precipitation, with beech forest more vulnerable to drought. There was considerable uncertainty about the geographical location of N₂O emissions. Two of the models BASFOR and LandscapeDNDC had largest emissions in central Europe where nitrogen deposition and soil nitrogen were largest, whereas the two other models identified different regions with large N₂O emission. N₂O emissions were found to be larger from beech than pine forests and were found to be particularly sensitive to forest growth

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LandscapeDNDC: a process model for simulation of biosphere–atmosphere–hydrosphere exchange processes at site and regional scale

Cited by 152 publications

References 61 publications

Historic nitrogen deposition determines future climate change effects on nitrogen retention in temperate forests

Historic nitrogen deposition determines future climate change effects on nitrogen retention in temperate forests

RELCA: a REgional Life Cycle inventory for Assessing bioenergy systems within a region

Environmental change impacts on the C- and N-cycle of European forests: a model comparison study

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