http://www.researchonline.mq.edu.au/vital/access/services/Feed ${session.getAttribute("locale")} 5 http://www.researchonline.mq.edu.au/vital/access/manager/Repository/mq:23423 Land models, which have been developed by the modeling community in the past few decades to predict future states of ecosystems and climate, have to be critically evaluated for their performance skills of simulating ecosystem responses and feedback to climate change. Benchmarking is an emerging procedure to measure performance of models against a set of defined standards. This paper proposes a benchmarking framework for evaluation of land model performances and, meanwhile, highlights major challenges at this infant stage of benchmark analysis. The framework includes (1) targeted aspects of model performance to be evaluated, (2) a set of benchmarks as defined references to test model performance, (3) metrics to measure and compare performance skills among models so as to identify model strengths and deficiencies, and (4) model improvement. Land models are required to simulate exchange of water, energy, carbon and sometimes other trace gases between the atmosphere and land surface, and should be evaluated for their simulations of biophysical processes, biogeochemical cycles, and vegetation dynamics in response to climate change across broad temporal and spatial scales. Thus, one major challenge is to select and define a limited number of benchmarks to effectively evaluate land model performance. The second challenge is to develop metrics of measuring mismatches between models and benchmarks. The metrics may include (1) a priori thresholds of acceptable model performance and (2) a scoring system to combine data-model mismatches for various processes at different temporal and spatial scales. The benchmark analyses should identify clues of weak model performance to guide future development, thus enabling improved predictions of future states of ecosystems and climate. The near-future research effort should be on development of a set of widely acceptable benchmarks that can be used to objectively, effectively, and reliably evaluate fundamental properties of land models to improve their prediction performance skills. 2012-12-17T10:00:13.729Z ]]> http://www.researchonline.mq.edu.au/vital/access/manager/Repository/mq:17781 Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs - determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy-in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69000 out of the world's 300000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log-normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation - but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait-based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models. 2012-05-23T21:36:09.770Z ]]> http://www.researchonline.mq.edu.au/vital/access/manager/Repository/mq:18394 Complex Earth system models, and their various sub-components, are not yet subject to rigorous evaluation against observations as much as they should be, despite the existence of hundreds of proposed diagnostics. A concerted process is urgently needed to make this the norm, not the exception. Earth Observation, field observations and palaeo data can be applied to contexts as diverse as wildfire, marine ecosystems, the land carbon cycle, and greenhouse gases. Model evaluation (by comparing models and benchmark data) and model weighting (defining the 'quality' of models on the basis of such a comparison) should be considered as separate issues. Systematic approaches to parameter optimization, such as the adjoint technique, allow structural differences between models to be identified and limitations to be addressed. Such methods are established in atmospheric tracer transport and carbon cycling; research carried out in the QUEST programme has demonstrated their applicability for climate modelling. Although it is impossible to devise a foolproof metric for the ability of models to predict the future, relevant metrics could be based on their ability to simulate the past. Furthermore, it should be possible to extend parameter optimization techniques to assimilate data from the past. There are limits to what can be achieved by benchmarking against a mean state, when it is a change in state that is of greatest interest. It is useful to benchmark individual processes rather than aggregate properties. Coupling good components does not automatically result in a good Earth System model, so for complex models, a two-stage process is needed: first, benchmarking the components in stand-alone mode, and second, using the same benchmarks in coupled mode. 2012-03-29T21:20:54.419Z ]]> http://www.researchonline.mq.edu.au/vital/access/manager/Repository/mq:11581 The terrestrial biosphere is a key regulator of atmospheric chemistry and climate. During past periods of climate change, vegetation cover and interactions between the terrestrial biosphere and atmosphere changed within decades. Modern observations show a similar responsiveness of terrestrial biogeochemistry to anthropogenically forced climate change and air pollution. Although interactions between the carbon cycle and climate have been a central focus, other biogeochemical feedbacks could be as important in modulating future climate change. Total positive radiative forcings resulting from feedbacks between the terrestrial biosphere and the atmosphere are estimated to reach up to 0.9 or 1.5 W m−2 K−1 towards the end of the twenty-first century, depending on the extent to which interactions with the nitrogen cycle stimulate or limit carbon sequestration. This substantially reduces and potentially even eliminates the cooling effect owing to carbon dioxide fertilization of the terrestrial biota. The overall magnitude of the biogeochemical feedbacks could potentially be similar to that of feedbacks in the physical climate system, but there are large uncertainties in the magnitude of individual estimates and in accounting for synergies between these effects. 2011-02-02T05:30:49.068Z ]]>