Evidence for strong seasonality in the carbon storage and carbon use efficiency of an Amazonian forest

absen

Potential net primary productivity in South America: application of a global model

We use a mechanistically based ecosystem simulation model to describe and analyze the spatial and temporal patterns of terrestrial net primary productivity (NPP) in South America. The Terrestrial Ecosystem Model (TEM) is designed to predict major carbon and nitrogen fluxes and pool sizes in terrestrial ecosystems at continental to global scales. Information from intensively studies field sites is used in combination with continental—scale information on climate, soils, and vegetation to estimate NPP in each of 5888 non—wetland, 0.5° latitude °0.5° longitude grid cells in South America, at monthly time steps. Preliminary analyses are presented for the scenario of natural vegetation throughout the continent, as a prelude to evaluating human impacts on terrestrial NPP. The potential annual NPP of South America is estimated to be 12.5 Pg/yr of carbon (26.3 Pg/yr of organic matter) in a non—wetland area of 17.0 ° 106 km2. More than 50% of this production occurs in the tropical and subtropical evergreen forest region. Six independent model runs, each based on an independently derived set of model parameters, generated mean annual NPP estimates for the tropical evergreen forest region ranging from 900 to 1510 g°m—2°yr—1 of carbon, with an overall mean of 1170 g°m—2°yr—1. Coefficients of variation in estimated annual NPP averaged 20% for any specific location in the evergreen forests, which is probably within the confidence limits of extant NPP measurements. Predicted rates of mean annual NPP in other types of vegetation ranged from 95 g°m—2°yr—1 in arid shrublands to 930 g°m@?yr—1 in savannas, and were within the ranges measured in empirical studies. The spatial distribution of predicted NPP was directly compared with estimates made using the Miami mode of Lieth (1975). Overall, TEM predictions were °10% lower than those of the Miami model, but the two models agreed closely on the spatial patterns of NPP in south America. Unlike previous models, however, TEM estimates NPP monthly, allowing for the evaluation of seasonal phenomena. This is an important step toward integration of ecosystem models with remotely sensed information, global climate models, and atmospheric transport models, all of which are evaluated at comparable spatial and temporal scales. Seasonal patterns of NPP in South America are correlated with moisture availability in most vegetation types, but are strongly influenced by seasonal differences in cloudiness in the tropical evergreen forests. On an annual basis, moisture availability was the factor that was correlated most strongly with annual NPP in South America, but differences were again observed among vegetation types. These results allow for the investigation and analysis of climatic controls over NPP at continental scales, within and among vegetation types, and within years. Further model validation is needed. Nevertheless, the ability to investigate NPP—environment interactions with a high spatial and temporal resolution at continental scales should prove useful if not essential for rigorous analysis of the potential effects of global climate changes on terrestrial ecosystems

Proposing a life cycle land use impact calculation methodology

The Life Cycle Assessment (LCA) community is yet to come to a consensus on a methodology to incorporate land use in LCA, still struggling with what exactly should be assessed and which indicators should be used. To solve this problem we start from concepts and models describing how ecosystems function and sustain, in order to understand how land use affects them. Earlier our research group presented a methodology based on the ecosystem exergy concept. This concept as based on the hypothesis that ecosystems develop towards more effective degradation of exergy fluxes passing through the system and is derived from two axioms: the principles of (i) maximum exergy storage and the (ii) maximum exergy dissipation. This concept aiming at the area of protection natural environment is different from conventional exergy analysis in LCA focusing on natural resources. To prevent confusion, the ecosystem exergy concept is further referred to as the MAximum Storage and Dissipation concept (MASD concept). In this paper we present how this concept identifies end-point impacts, mid-point impacts and mid-point indicators. The identified end-point impacts to assess are Ecosystem Structural Quality (ESQ) and Ecosystem Functional Quality (EFQ). In order to quantify these end-point impacts a dynamic multi-indicator set is proposed for quantifying the mid-point impacts on soil fertility, biodiversity and biomass production (quantifying the ESQ) and soil structure, vegetation structure and on-site water balance (quantifying the EFQ). Further we present an impact calculation method suitable for different environmental assessment tools and demonstrate the incorporation of the methodology in LCA

Ecosystems as climate controllers – biotic feedbacks (a review)

There is good evidence that higher global temperature will promote a rise of green house gas levels, implying a positive feedback which will increase the effect of the anthropogenic emissions on global temperatures. Here we present a review about the results which deal with the possible feedbacks between ecosystems and the climate system. There are a lot of types of feedback which are classified. Some circulation models are compared to each other regarding their role in interactive carbon cycle

Measurements of soil respiration and simple models dependent on moisture and temperature for an Amazonian southwest tropical forest

Soil respiration plays a significant role in the carbon cycle of Amazonian tropical forests, although in situ measurements have only been poorly reported and the dependence of soil moisture and soil temperature also weakly understood. This work investigates the temporal variability of soil respiration using field measurements, which also included soil moisture, soil temperature and litterfall, from April 2003 to January 2004, in a southwest Brazilian tropical rainforest near Ji-Paraná, Rondônia. The experimental design deployed five automatic (static, semi-opened) soil chambers connected to an infra-red CO2 gas analyzer. The mean half-hourly soil respiration showed a large scattering from 0.6 to 18.9 µmol CO2 m-2 s-1 and the average was 8.0±3.4 µmol CO2 m-2 s-1. Soil respiration varied seasonally, being lower in the dry season and higher in the wet season, which generally responded positively to the variation of soil moisture and temperature year round. The peak was reached in the dry-to-wet season transition (September), this coincided with increasing sunlight, evapotranspiration and ecosystem productivity. Litterfall processes contributed to meet very favorable conditions for biomass decomposition in early wet season, especially the fresh litter on the forest floor accumulated during the dry season. We attempted to fit three models with the data: the exponential Q10 model, the Reichstein model, and the log-soil moisture model. The models do not contradict the scattering of observations, but poorly explain the variance of the half-hourly data, which is improved when the lag-time days averaging is longer. The observations suggested an optimum range of soil moisture, between 0.11

Integration of Npp Semi Mechanistic - Modelling, Remote Sensing and Cis in Estimating Co2 Absorption of Forest Vegetation in Lore Lindu National Park

Net Primary Production, NPP, is one of the most important variables characterizing the performance of an ecosystem. It is the difference between the total carbon uptake from the air through photosynthesis and the carbon loss due to respiration by living plants. However, field measurements of NPP are time-consuming and expensive. Current techniques are therefore not useful for obtaining NPP estimates over large areas. By combining the remote sensing and GIS technology and modelling, we can estimate NPP of a large ecosystem with a little ease. This paper discusses the use of a process based physiological sunshade canopy models in estimating NPP of Lore Lindu National Park (LLNP). The discussion includes on how to parameterize the models and how to scale up from leaf to the canopy. The version documented in this manuscript is called NetPro Model, whicha potential NPP model where water effect is not included yet. The model integrates CIS and the use of Remote Sensing, and written in Visual Basic 6.0 programming language and Map Objects 2.1. NetPro has the capability of estimating NPP of Cs vegetation under present environmental condition and under future scenarios (increasing [CO2], increasing temperature and increasing or decreasing leaf nitrogen level). Based on site-measured parameterisation of VaM* (Photosynthetic capacity), /JjRespiration) and leaf nitrogen ONi), the model was run under increasing CO2 level and temperature and varied leaf nitrogen. The output of the semi-mechanistic modelling is radiation use efficiency (?). Analysis of remote sensing data give Normalized Difference Vegetation Index (NDVI) and related Leaf Area Index (LAI) and traction of absorbed Photosynthetically Active Radiation (/M>AK). Climate data are obtained from 12 meteorological stations around die parks, which includes global radiations, minimum and maximum temperature. CO2 absorbed by vegetation (Gross Primary Production, GPP) is then calculated using the above variables and parameters with the following equation:estimating NPP, while ecosystem respiration is set as a function of temperature for estimating NEE. Under present condition, the net absorption of CO> by the vegetation of Lore Lindu National Park (NPP) is 1330.31 gCm"2year"' and at double CO2 and temperature increased of 3.5 "C, it increased by 23 %, reaching 1638.80 gCm'2 year'1

INTEGRATION OF NPP SEMI MECHANISTIC - MODELLING, REMOTE SENSING AND CIS IN ESTIMATING CO2 ABSORPTION OF FOREST VEGETATION IN LORE LINDU NATIONAL PARK

Net Primary Production, NPP, is one of the most important variables characterizing the performance of an ecosystem. It is the difference between the total carbon uptake from the air through photosynthesis and the carbon loss due to respiration by living plants. However, field measurements of NPP are time-consuming and expensive. Current techniques are therefore not useful for obtaining NPP estimates over large areas. By combining the remote sensing and GIS technology and modelling, we can estimate NPP of a large ecosystem with a little ease. This paper discusses the use of a process based physiological sunshade canopy models in estimating NPP of Lore Lindu National Park (LLNP). The discussion includes on how to parameterize the models and how to scale up from leaf to the canopy. The version documented in this manuscript is called NetPro Model, whicha potential NPP model where water effect is not included yet. The model integrates CIS and the use of Remote Sensing, and written in Visual Basic 6.0 programming language and Map Objects 2.1. NetPro has the capability of estimating NPP of Cs vegetation under present environmental condition and under future scenarios (increasing [CO2], increasing temperature and increasing or decreasing leaf nitrogen level). Based on site-measured parameterisation of VaM* (Photosynthetic capacity), /JjRespiration) and leaf nitrogen ONi), the model was run under increasing CO2 level and temperature and varied leaf nitrogen. The output of the semi-mechanistic modelling is radiation use efficiency (?). Analysis of remote sensing data give Normalized Difference Vegetation Index (NDVI) and related Leaf Area Index (LAI) and traction of absorbed Photosynthetically Active Radiation (/M>AK). Climate data are obtained from 12 meteorological stations around die parks, which includes global radiations, minimum and maximum temperature. CO2 absorbed by vegetation (Gross Primary Production, GPP) is then calculated using the above variables and parameters with the following equation:estimating NPP, while ecosystem respiration is set as a function of temperature for estimating NEE. Under present condition, the net absorption of CO> by the vegetation of Lore Lindu National Park (NPP) is 1330.31 gCm"2year"' and at double CO2 and temperature increased of 3.5 "C, it increased by 23 %, reaching 1638.80 gCm'2 year'1.Key words : NPP Semi-mechanistic model, photosynthesis, carbon sequestration, net primary-production, tropical fores