Scholarly Work - Ecology

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A tree-ring perspective on the terrestrial carbon cycle
(2014-08) Babst, Flurin; Alexander, M. Ross; Szejner, Paul; Bouriaud, Olivier; Klesse, Stefan; Roden, John; Ciais, Philippe; Poulter, Benjamin; Frank, David; Moore, David J.P.; Trouet, Valerie
Tree-ring records can provide valuable information to advance our understanding of contemporary terrestrial carbon cycling and to reconstruct key metrics in the decades preceding monitoring data. The growing use of tree rings in carbon-cycle research is being facilitated by increasing recognition of reciprocal benefits among research communities. Yet, basic questions persist regarding what tree rings represent at the ecosystem level, how to optimally integrate them with other data streams, and what related challenges need to be overcome. It is also apparent that considerable unexplored potential exists for tree rings to refine assessments of terres-trial carbon cycling across a range of temporal and spatial domains. Here, we summarize recent advances and highlight promising paths of investigation with respect to (1) growth phenology, (2) forest productivity trends and variability, (3) CO2 fertilization and water-use efficiency, (4) forest disturbances, and (5) comparisons between observational and computational forest productivity estimates. We encourage the integration of tree-ring data: with eddy-covarian measurements to investigate carbon allocation patterns and water-use efficiency; with remotely sensed observations to distinguish the timing of cambial growth and leaf phenology; and with forest inventories to develop continuous, annually-resolved and long-term carbon budgets. In addition, we note the potential of tree-ring records and derivatives thereof to help evaluate the performance of earth system models regarding the simulated magnitude and dynamics of forest carbon uptake, and inform these models about growth responses to (non-)climatic drivers. Such efforts are expected to improve our understanding of forest carbon cycling and place current developments into a long-term perspective.
Climate change and European forests: What do we know, what are the uncertainties, and what are the implications for forest management?
(Elsevier BV, 2014-12) Lindner, Marcus; Fitzgerald, Joanne B.; Zimmermann, Niklaus E.; Reyer, Christopher; Delzon, Sylvain; van der Maaten, Ernst; Schelhaas, Mart-Jan; Lasch, Petra; Eggers, Jeanette; van der Maaten-Theunissen, Marieke; Suckow, Felicitas; Psomas, Achilleas; Poulter, Benjamin; Hanewinkel, Marc
The knowledge about potential climate change impacts on forests is continuously expanding and some changes in growth, drought induced mortality and species distribution have been observed. However despite a signiﬁcant body of research, a knowledge and communication gap exists between scientists and non-scientists as to how climate change impact scenarios can be interpreted and what they imply for European forests. It is still challenging to advise forest decision makers on how best to plan for climate change as many uncertainties and unknowns remain and it is difﬁcult to communicate these to practitioners and other decision makers while retaining emphasis on the importance of planning for adaptation. In this paper, recent developments in climate change observations and projections, observed and projected impacts on European forests and the associated uncertainties are reviewed and synthesised with a view to understanding the implications for forest management. Current impact assessments with simulation models contain several simpliﬁcations, which explain the discrepancy between results of many simulation studies and the rapidly increasing body of evidence about already observed changes in forest productivity and species distribution. In simulation models uncertainties tend to cascade onto one another; from estimating what future societies will be like and general circulation models (GCMs) at the global level, down to forest models and forest management at the local level. Individual climate change impact studies should not be uncritically used for decision-making without reﬂection on possible shortcomings in system understanding, model accuracy and other assumptions made. It is important for decision makers in forest management to realise that they have to take long-lasting management decisions while uncertainty about climate change impacts are still large. We discuss how to communicate about uncertainty e which is imperative for decision making e without diluting the overall message. Considering the range of possible trends and uncertainties in adaptive forest management requires expert knowledge and enhanced efforts for providing science-based decision support.
Challenges in developing a computationally efficient plant physiological height-class-structured forest model
(Elsevier BV, 2014-09) Poulter, Benjamin; Scherstjanoi, M.; Kaplan, J.O.; Lischke, H.
Ongoing and future climate change may be of sufficient magnitude to significantly impact global forest ecosystems. In order to anticipate the potential range of changes to forests in the future and to better understand the development and state of forest ecosystems at present, a variety of forest ecosystem models of varying complexity have been developed over the past 40 years. While most of these models focus on representing either forest demographics including age and height structure, or forest biogeochemistry including plant physiology and ecosystem carbon cycling, it is increasingly seen as crucial that forest ecosystem models include equally good representations of both. However, only few models currently include detailed representations of both biogeochemistry and demographics, and those mostly have high computational demands. Here, we present TreeM-LPJ, a first step towards a new, computationally efficient forest dynamics model. We combine the height-class scheme of the forest landscape model TreeMig with the biogeochemistry of the dynamic global vegetation model LPJ-GUESS. The resulting model is able to simulate forest growth by considering vertical spatial variability without stochastic functions, considerably reducing computational demand. Discretization errors are kept small by using a numerical algorithm that extrapolates growth success in height, and thereby dynamically updates the state variables of the trees in the different height classes. We demonstrate TreeM-LPJ in an application on a transect in the central Swiss Alps where we show results from the new model compare favorably with the more complex LPJ-GUESS. TreeM-LPJ provides a combination of biological detail and computational efficiency that can serve as a useful basis for large-scale vegetation modeling.

Scholarly Work - Ecology

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