Process-based models can be classified into: (a) terrestrial biogeochemical models (TBMs), which simulate fluxes of carbon, water and nitrogen coupled within terrestrial ecosystems, and (b) dynamic global vegetation models (DGVMs), which further couple these processes interactively with changes in slow ecosystem processes depending on resource competition, establishment, growth and mortality of different vegetation types. In this study, four models -RHESSys, GOTILWA 1 , LPJ-GUESS and ORCHIDEErepresenting both modelling approaches were compared and evaluated against benchmarks provided by eddy-covariance measurements of carbon and water fluxes at 15 forest sites within the EUROFLUX project. Overall, model-measurement agreement varied greatly among sites. Both modelling approaches have somewhat different strengths, but there was no model among those tested that universally performed well on the two variables evaluated. Small biases and errors suggest that ORCHIDEE and GOTILWA 1 performed better in simulating carbon fluxes while LPJ-GUESS and RHESSys did a better job in simulating water fluxes. In general, the models can be considered as useful tools for studies of climate change impacts on carbon and water cycling in forests. However, the various sources of variation among models simulations and between models simulations and observed data described in this study place some constraints on the results and to some extent reduce their reliability. For example, at most sites in the Mediterranean region all models generally performed poorly most likely because of problems in the representation of water stress effects on both carbon uptake by photosynthesis and carbon release by heterotrophic respiration (R h ).The use of flux data as a means of assessing key processes in models of this type is an important approach to improving model performance. Our results show that the models have value but that further model development is necessary with regard to the representation of the some of the key ecosystem processes.

The uncertainties and sources of variation in projected impacts of climate change on agriculture and terrestrial ecosystems depend not only on the emission scenarios and climate models used for projecting future climates, but also on the impact models used, and the local soil and climatic conditions of the managed or unmanaged ecosystems under study. We addressed these uncertainties by applying different impact models at site, regional and continental scales, and by separating the variation in simulated relative changes in ecosystem performance into the different sources of uncertainty and variation using analyses of variance. The crop and ecosystem models used output from a range of global and regional climate models (GCMs and RCMs) projecting climate change over Europe between 1961–1990 and 2071–2100 under the IPCC SRES scenarios. The projected impacts on productivity of crops and ecosystems included the direct effects of increased CO2 concentration on photosynthesis. The variation in simulated results attributed to differences between the climate models were, in all cases, smaller than the variation attributed to either emission scenarios or local conditions. The methods used for applying the climate model outputs played a larger role than the choice of the GCM or RCM. The thermal suitability for grain maize cultivation in Europe was estimated to expand by 30–50% across all SRES emissions scenarios. Strong increases in net primary productivity (NPP) (35–54%) were projected in northern European ecosystems as a result of a longer growing season and higher CO2 concentrations. Changing water balance dominated the projected responses of southern European ecosystems, with NPP declining or increasing only slightly relative to present-day conditions. Both site and continental scale models showed large increases in yield of rain-fed winter wheat for northern Europe, with smaller increases or even decreases in southern Europe. Site-based, regional and continental scale models showed large spatial variations in the response of nitrate leaching from winter wheat cultivation to projected climate change due to strong interactions with soils and climate. The variation in simulated impacts was smaller between scenarios based on RCMs nested within the same GCM than between scenarios based on different GCMs or between emission scenarios

Climate change resulting from the enhanced greenhouse effect together with the direct effect of increased atmospheric CO2 concentrations on vegetation growth are expected to produce changes in the cycling of carbon in terrestrial ecosystems. Impacts will vary across Europe, and regional-scale studies are needed to resolve this variability. In this study, we used the LPJ-GUESS ecosystem model driven by a suite of regional climate model (RCM) scenarios from the European Union (EU) project PRUDENCE to estimate climate impacts on carbon cycling across Europe. We identified similarities and discrepancies in simulated climate impacts across scenarios, particularly analyzing the uncertainties arising from the range of climate models and emissions scenarios considered. Our results suggest that net primary production (NPP) and heterotrophic respiration (Rh) will generally increase throughout Europe, but with considerable variation between European subregions. The smallest NPP increases, and in some cases decreases, occurred in the Mediterranean, where many ecosystems switched from sinks to sources of carbon by 2100, mainly as a result of deteriorating water balance. Over the period 1991–2100, modeled climate change impacts on the European carbon balance ranged from a sink of 11.6 GtC to a source of 3.3 Gt C, the average annual sink corresponding with 1.85% of the current EU anthropogenic emissions. Projected changes in carbon balance were more dependent on the choice of the general circulation model (GCM) providing boundary conditions to the RCM than the choice of RCM or the level of anthropogenic greenhouse gases emissions

Los modelos alométricos para estimar biomasa, carbono y dióxido de carbono son de gran importancia en la modelación forestal, mediante estos es posible cuantificar la mitigación de emisiones de gases de efecto invernadero. El objetivo del presente estudio fue ajustar modelos alométricos para estimar la biomasa aérea en una plantación de Pinus cembroides y P. halepensis. Se aplicó el método indirecto (método Adelaide) con una muestra de 50 árboles por especie. El estudio se realizó en dos áreas: Cuauhtémoc y El Recreo, de Saltillo, Coahuila. Para cada componente de biomasa de hojas-ramas, fuste y total se ajustaron seis modelos, se utilizaron variables independientes de diámetro normal y altura; se seleccionó el mejor modelo conforme al coeficiente de determinación ajustado (R2adj), el error estándar (Syx) y la significancia de los parámetros de regresión. Los resultados indicaron que el diámetro normal estima, adecuadamente, la biomasa por componente de P. cembroides (R2adj promedio de 0.86); para P. halepensis, la biomasa se calculó con el diámetro normal y la altura (R2adj de 0.79 en promedio). El método indirecto es un buen estimador de biomasa aérea en ambas especies, los mejores ajustes de modelos pueden usarse para cuantificar almacenes de carbono y dióxido de carbono en la región.

Los sistemas tradicionales en las zonas productoras de café (Coffea arabica) se desarrollan en ecosistemas bajo sombra, con amplia diversidad de especies de flora y fauna. En la actualidad, la composición florística original se ha modificado por cambios en el establecimiento de Inga spp. Por lo anterior, surge la importancia de conocer la diversidad y estructura arbórea actual del sistema agroforestal en el cultivo de café en el Soconusco, Chiapas. Para tal fin se establecieron 10 unidades de muestreo (UM) al azar en la región media del Soconusco Chiapas; con dimensiones de 1 000 m2 (20 x 50 m). Se registraron variables para identificar su estratificación vertical y horizontal, y se calcularon los Índices de valor de importancia (IVI), diversidad de especies arbóreas, Shannon-Wiener y Simpson. Se identificaron 23 especies arbóreas de una población de 279 árboles; a las plantaciones con mayor edad cronológica les correspondió mayor diversidad y estructura arbórea. La vegetación observada presentó estratos inferiores de <9 m y los superiores de >18 m. Los taxones con más presencia en las UM fueron Tabebuia donnell smithii, Inga micheliana, Cordia alliodora y Cedrela odorata. De acuerdo con los índices de diversidad de Simpson y Shannon-Wiener, la vegetación prevaleciente tiene poca diversidad de especies arbóreas. El mayor Índice de Valor de importancia se registró en Tabebuia donnell smithii e Inga micheliana.