Regional contingencies in the relationship between aboveground biomass and litter in the world’s grasslands

Based on regional-scale studies, aboveground production and litter decomposition are thought to positively covary, because they are driven by shared biotic and climatic factors. Until now we have been unable to test whether production and decomposition are generally coupled across climatically dissimilar regions, because we lacked replicated data collected within a single vegetation type across multiple regions, obfuscating the drivers and generality of the association between production and decomposition. Furthermore, our understanding of the relationships between production and decomposition rests heavily on separate meta-analyses of each response, because no studies have simultaneously measured production and the accumulation or decomposition of litter using consistent methods at globally relevant scales. Here, we use a multi-country grassland dataset collected using a standardized protocol to show that live plant biomass (an estimate of aboveground net primary production) and litter disappearance (represented by mass loss of aboveground litter) do not strongly covary. Live biomass and litter disappearance varied at different spatial scales. There was substantial variation in live biomass among continents, sites and plots whereas among continent differences accounted for most of the variation in litter disappearance rates. Although there were strong associations among aboveground biomass, litter disappearance and climatic factors in some regions (e.g. U.S. Great Plains), these relationships were inconsistent within and among the regions represented by this study. These results highlight the importance of replication among regions and continents when characterizing the correlations between ecosystem processes and interpreting their global-scale implications for carbon flux. We must exercise caution in parameterizing litter decomposition and aboveground production in future regional and global carbon models as their relationship is complex.

Estimating the aboveground biomass and wood volume of savanna woodlands in Brazil's Pantanal wetlands based on allometric correlations

The quantity and distribution of vegetal biomass are important aspects to consider in ecosystem studies. However, little information is available about Brazil's Pantanal woodland savannas. This work involved the development of regression equations of the aerial biomass and wood volume of native tree species in a region of woodland savanna on Rio Negro farm in the Pantanal of Nhecolandia, Brazil. Samples were taken from 10 trees of each of five species: Protium heptaphyllum (Aub1.) Marchand, Magonia pubescens A. St.-Hil., Diptychandra aurantiaca Tul., Terminalia argentea Mart. and Zucc. and Licania minutiflora (Sagot) Fritsch and from a miscellaneous group of I I different species. Linear and nonlinear regression analyses were developed relating the diameter at breast height to the dry weight of wood, branches and leaves, wood volume and total aerial biomass. All the regressions showed a significance of P < 0.05 and an R-2 close to or above 0.8. The biomass curve predicted by linear regression analysis of the studied species was similar to the nonlinear regression, with the exception of L. minutiflora and the miscellaneous group. The breast height diameter proved a good choice for estimating biomass and wood volume. The estimated wood volume and biomass of the Pantanal woodland savanna is crucial information for understanding the carbon cycle and for ensuring the region's conservation and sustainable use. (c) 2006 Elsevier B.V. All rights reserved.

Nutrient content in aboveground biomass of Brazilian peanut cultivars in conservation tillage on sugarcane straw and pasture area.

Fields studies were conducted in 2004/2005 in order to evaluate the effects of tillage on nutrient content in aboveground biomass of two peanut cultivars, cultivated in rotation after mechanical harvested sugarcane and pastures. These trials were carried out in two types of soils; Oxisol and Ultisol, respectively in Ribeir?ao Preto and Mirassol, S?ao Paulo State, Brazil. The experimental design was split-plot with four replications. Tillage treatments (conventional, minimum and no-tillage) were main plots while sub-plots were peanut genotypes IAC-Tatu ST (Valencia market-type, erect growth habit, red seed coat, maturity range around 100 days after planting) and IAC-Caiap´o (Runner market-type, prostate growth habit, pink testa, maturity range more than 135 days). From 15 to 90 days after emergence, samples of leaves and stems were harvested, dried, weighted and ground to determine macro and micronutrient concentration. At 75 days after sowing, the cultivar IAC-Caiap´o showed higher contents of N, P, K, Cu, and Zn while IAC-Tatu presented higher concentrations of Ca, Mg, and S. Zn content was higher in conservation tillage than in conventional, mainly in Oxisoil for both of cultivars.

Modeling and Mapping Agroforestry Aboveground Biomass in the Brazilian Amazon Using Airborne Lidar Data.

Agroforestry has large potential for carbon (C) sequestration while providing many economical, social, and ecological benefits via its diversified products. Airborne lidar is considered as the most accurate technology for mapping aboveground biomass (AGB) over landscape levels. However, little research in the past has been done to study AGB of agroforestry systems using airborne lidar data. Focusing on an agroforestry system in the Brazilian Amazon, this study first predicted plot-level AGB using fixed-effects regression models that assumed the regression coefficients to be constants. The model prediction errors were then analyzed from the perspectives of tree DBH (diameter at breast height)?height relationships and plot-level wood density, which suggested the need for stratifying agroforestry fields to improve plot-level AGB modeling. We separated teak plantations from other agroforestry types and predicted AGB using mixed-effects models that can incorporate the variation of AGB-height relationship across agroforestry types. We found that, at the plot scale, mixed-effects models led to better model prediction performance (based on leave-one-out cross-validation) than the fixed-effects models, with the coefficient of determination (R2) increasing from 0.38 to 0.64. At the landscape level, the difference between AGB densities from the two types of models was ~10% on average and up to ~30% at the pixel level. This study suggested the importance of stratification based on tree AGB allometry and the utility of mixed-effects models in modeling and mapping AGB of agroforestry systems.

Arctic aboveground tundra biomass dynamics between 1982 and 2010

Numerous studies have evaluated the dynamics of Arctic tundra vegetation throughout the past few decades, using remotely sensed proxies of vegetation, such as the normalized difference vegetation index (NDVI). While extremely useful, these coarse-scale satellite-derived measurements give us minimal information with regard to how these changes are being expressed on the ground, in terms of tundra structure and function. In this analysis, we used a strong regression model between NDVI and aboveground tundra phytomass, developed from extensive field-harvested measurements of vegetation biomass, to estimate the biomass dynamics of the circumpolar Arctic tundra over the period of continuous satellite records (1982-2010). We found that the southernmost tundra subzones (C-E) dominate the increases in biomass, ranging from 20 to 26%, although there was a high degree of heterogeneity across regions, floristic provinces, and vegetation types. The estimated increase in carbon of the aboveground live vegetation of 0.40 Pg C over the past three decades is substantial, although quite small relative to anthropogenic C emissions. However, a 19.8% average increase in aboveground biomass has major implications for nearly all aspects of tundra ecosystems including hydrology, active layer depths, permafrost regimes, wildlife and human use of Arctic landscapes. While spatially extensive on-the-ground measurements of tundra biomass were conducted in the development of this analysis, validation is still impossible without more repeated, long-term monitoring of Arctic tundra biomass in the field.

Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks

Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8-50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mgha(-1)) at spatial scales ranging from 5 to 250m (0.025-6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20-400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial ``dilution'' bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.

Changes in plant biomass and species composition of alpine Kobresia meadows along altitudinal gradient on the Qinghai-Tibetan Plateau

Alpine Kobresia meadows are major vegetation types on the Qinghai-Tibetan Plateau. There is growing concern over their relationships among biodiversity, productivity and environments. Despite the importance of species composition, species richness, the type of different growth forms, and plant biomass structure for Kobresia meadow ecosystems, few studies have been focused on the relationship between biomass and environmental gradient in the Kobresia meadow plant communities, particularly in relation to soil moisture and edaphic gradients. We measured the plant species composition, herbaceous litter, aboveground and belowground biomass in three Kobresia meadow plant communities in Haibei Alpine Meadow Ecosystem Research Station from 2001 to 2004. Community differences in plant species composition were reflected in biomass distribution. The total biomass showed a decrease from 13196.96 +/- 719.69 g/m(2) in the sedge-dominated K. tibetica swamp to 2869.58 +/- 147.52 g/m(2) in the forb and sedge dominated K. pygmaea meadow, and to 2153.08 +/- 141.95 g/m(2) in the forbs and grasses dominated K. humilis along with the increase of altitude. The vertical distribution of belowground biomass is distinct in the three meadow communities, and the belowground biomass at the depth of 0-10 cm in K. tibetica swamp meadow was significantly higher than that in K. humilis and K. pygmaea meadows (P < 0.01). The herbaceous litter in K. tibetica swamp was significantly higher than those in K. pygnaeca and K. humilis meadows. The effects of plant litter are enhanced when ground water and soil moisture levels are raised. The relative importance of litter and vegetation may vary with soil water availability. In the K. tibetica swamp, total biomass was negatively correlated to species richness (P < 0.05); aboveground biomass was positively correlated to soil organic matter, soil moisture, and plant cover (P < 0.05); belowground biomass was positively correlated with soil moisture (P < 0.05). However, in the K. pygnaeca and K. humilis meadow communities, aboveground biomass was positively correlated to soil organic matter and soil total nitrogen (P < 0.05). This suggests that the distribution of biomass coincided with soil moisture and edaphic gradient in alpine meadows.

Temperature and biomass influences on interannual changes in CO2 exchange in an alpine meadow on the Qinghai-Tibetan Plateau

Three years of eddy covariance measurements were used to characterize the seasonal and interannual variability of the CO2 fluxes above an alpine meadow (3250 m a.s.l.) on the Qinghai-Tibetan Plateau, China. This alpine meadow was a weak sink for atmospheric CO2, with a net ecosystem production (NEP) of 78.5, 91.7, and 192.5 g C m(-2) yr(-1) in 2002, 2003, and 2004, respectively. The prominent, high NEP in 2004 resulted from the combination of high gross primary production (GPP) and low ecosystem respiration (R-e) during the growing season. The period of net absorption of CO2 in 2004, 179 days, was 10 days longer than that in 2002 and 5 days longer than that in 2003. Moreover, the date on which the mean air temperature first exceeded 5.0 degrees C was 10 days earlier in 2004 (DOY110) than in 2002 or 2003. This date agrees well with that on which the green aboveground biomass (Green AGB) started to increase. The relationship between light-use efficiency and Green AGB was similar among the three years. In 2002, however, earlier senescence possibly caused low autumn GPP, and thus the annual NEP, to be lower. The low summertime R-e in 2004 was apparently caused by lower soil temperatures and the relatively lower temperature dependence of R-e in comparison with the other years. These results suggest that (1) the Qinghai-Tibetan Plateau plays a potentially significant role in global carbon sequestration, because alpine meadow covers about one-third of this vast plateau, and (2) the annual NEP in the alpine meadow was comprehensively controlled by the temperature environment, including its effect on biomass growth.

Effects of plant diversity on bioenergy parameters in grassland biomass

Extensive grassland biomass for bioenergy production has long been subject of scientific research. The possibility of combining nature conservation goals with a profitable management while reducing competition with food production has created a strong interest in this topic. However, the botanical composition will play a key role for solid fuel quality of grassland biomass and will have effects on the combustion process by potentially causing corrosion, emission and slagging. On the other hand, botanical composition will affect anaerobic digestibility and thereby the biogas potential. In this thesis aboveground biomass from the Jena-Experiment plots was harvested in 2008 and 2009 and analysed for the most relevant chemical constituents effecting fuel quality and anaerobic digestibility. Regarding combustion, the following parameters were of main focus: higher heating value (HHV), gross energy yield (GE), ash content, ash softening temperature (AST), K, Ca, Mg, N, Cl and S content. For biogas production the following parameters were investigated: substrate specific methane yield (CH4 sub), area specific methane yield (CH4 area), crude fibre (CF), crude protein (CP), crude lipid (CL) and nitrogen-free extract (NfE). Furthermore, an improvement of the fuel quality was investigated through applying the Integrated generation of solid Fuel and Biogas from Biomass (IFBB) procedure. Through the specific setup of the Jena-Experiment it was possible to outline the changes of these parameters along two diversity gradients: (i) species richness (SR; 1 to 60 species) and (ii) functional group (grasses, legumes, small herbs and tall herbs) presence. This was a novel approach on investigating the bioenergy characteristic of extensive grassland biomass and gave detailed insight in the sward-composition¬ - bioenergy relations such as: (i) the most relevant SR effect was the increase of energy yield for both combustion (annual GE increased by 26% from SR8→16 and by 65% from SR8→60) and anaerobic digestion (annual CH4 area increased by 22% from SR8→16 and by 49% from SR8→60) through a strong interaction of SR with biomass yield; (ii) legumes play a key role for the utilization of grassland biomass for energy production as they increase the energy content of the substrate (HHV and CH4 sub) and the energy yield (GE and CH4 area); (iii) combustion is the conversion technique that will yield the highest energy output but requires an improvement of the solid fuel quality in order to reduce the risk of corrosion, emission and slagging related problems. This was achieved through applying the IFBB-procedure, with reductions in ash (by 23%), N (28%), K (85%), Cl (56%) and S (59%) and equal levels of concentrations along the SR gradient.

Effect of soil waterlogging on below-ground biomass allometric relations in Norway spruce

An increasing importance is assigned to the estimation and verification of carbon stocks in forests. Forestry practice has several long-established and reliable methods for the assessment of aboveground biomass; however we still miss accurate predictors of belowground biomass. A major windthrow event exposing the coarse root systems of Norway spruce trees allowed us to assess the effects of contrasting soil stone and water content on belowground allocation. Increasing stone content decreases root/shoot ratio, while soil waterlogging leads to an increase in this ratio. We constructed allometric relationships for belowground biomass prediction and were able to show that only soil waterlogging significantly impacts model parameters. We showed that diameter at breast height is a reliable predictor of belowground biomass and, once site-specific parameters have been developed, it is possible to accurately estimate belowground biomass in Norway spruce.

Biomass and Stand Characteristics of a Highly Productive Mixed Douglas-Fir and Western Hemlock Plantation in Coastal Washington

Aboveground biomass predictive equations were developed for a highly productive 47-year-old mixed Douglas-fir and western hemlock stand in southwest Washington State to characterize the preharvest stand attributes for the Fall River Long-Term Site Productivity Study. The equations were developed using detailed biomass data taken from 31 Douglas-fir and 11 western hemlock trees within the original stand. The stand had an average of 615 live trees per hectare, with an average dbh of 35.6 cm (39.1 cm for Douglas-fir and 33.3 cm for western hemlock) and an average total tree height of 31.6 m (32.8 m for Douglas-fir and 30.2 m for western hemlock). Equations developed were of the form In Y = b(1) + b(2) In dbh, where Y = biomass in kg, dbh = diameter in cm at 1.3 m height, b(1) = intercept, and b(2) = slope of equation. Each tree part was estimated separately and also combined into total aboveground biomass. The total aboveground biomass estimation equations were In Y = -0.9950 + 2.0765 In dbh for Douglas-fir, and In Y = -1.6612 + 2.2321 In dbh for western hemlock. The estimate of the aboveground live-free biomass was of 395 Mg ha(-1) (235 Mg ha(-1) for Douglas-fir and 160 Mg ha(-1) for western hemlock), with 9.5, 29.3, 12.9, 308, and 32.7 Mg ha(-1) in the foliage, live branches, dead branches, stem wood, and stem hark, respectively. When compared with biomass estimates from six other studies, ranging in age from 22 to 110 years and from 96.3 to 636 Mg ha(-1), the biomass of the Fall River site was relatively high for its age, indicating very high productivity.