Airborne LiDAR technique for estimating biomass components of maize: A case study in Zhangye City,Northwest China

Crop biomass is an important ecological indicator of growth, light use efficiency, and carbon stocks in agro-ecosystems. Light detection and ranging (LiDAR) or laser scanning has been widely used to estimate forest structural parameters and biomass. However, LiDAR is rarely used to estimate crop parameters because the short, dense canopies of crops limit the accuracy of the results. The objective of this study is to explore the potential of airborne LiDAR data in estimating biomass components of maize, namely aboveground biomass (AGB) and belowground biomass (BGB). Five biomass-related factors were measured during the entire growing season of maize. The field-measured canopy height and leaf area index (LAI) were identified as the factors that most directly affect biomass components through Pearson's correlation analysis and structural equation modeling (SEM). Field-based estimation models were proposed to estimate maize biomass components during the tasseling stage. Subsequently, the maize height and LAI over the entire study area were derived from LiDAR data and were used as input for the estimation models to map the spatial pattern of the biomass components. The results showed that the LiDAR-estimated biomass was comparable to the field-measured biomass, with root mean squared errors (RMSE) of 288.51 g/m² (AGB), and 75.81 g/m² (BGB). In conclusion, airborne LiDAR has great potential for estimating canopy height, LAI, and biomass components of maize during the peak growing season.     

Above-ground biomass estimation using airborne discrete-return and full-waveform LiDAR data in a coniferous forest

The estimation of forest aboveground biomass (AGB) is critical for quantifying carbon stocks and essential for evaluating global carbon cycle. Many previous studies have estimated forest AGB using airborne discrete-return Light Detection and Ranging (LiDAR) data, while fewer studies predicted forest AGB using airborne full-waveform LiDAR data. The objective of this work was to evaluate the utility of airborne discrete-return and full-waveform LiDAR data in estimating forest AGB. To fulfill the objective, airborne discrete-return LiDAR-derived metrics (DR-metrics), full-waveform LiDAR-derived metrics (FW-metrics) and structure parameters (combining height metrics and canopy cover) were used to estimate forest AGB. Additionally, the combined use of DR- and FW-metrics through a nonlinear way was also evaluated for AGB estimation in a coniferous forest in Dayekou, Gansu province of China. Results indicated that both height metrics derived from discrete-return and full-waveform LiDAR data were stronger predictors of forest AGB compared with other LiDAR-derived metrics. Canopy cover derived from discrete-return LiDAR data was not sensitive to forest AGB, while canopy cover estimated by full-waveform LiDAR data (CC_WF) showed moderate correlation with forest AGB. Structure parameters derived from full-waveform LiDAR data, such as H75_FW * CC_FW, were closely related to forest AGB. In contrast, structure parameters derived from discrete-return LiDAR data were not suitable for estimating forest AGB due to the less sensitivity of canopy cover CC_DR2 to forest AGB. This research also concluded that the synergistic use of DR- and FW-metrics can provide better AGB estimates in coniferous forest.     

Environmental and Biotic Controls over Aboveground Biomass Throughout a Tropical Rain Forest

The environmental and biotic factors affecting spatial variation in canopy three-dimensional (3-D) structure and aboveground tree biomass (AGB) are poorly understood in tropical rain forests. We combined field measurements and airborne light detection and ranging (lidar) to quantify 3-D structure and AGB across a 5,016 ha rain forest reserve on the northeastern flank of Mauna Kea volcano, Hawaii Island. We compared AGB among native stands dominated by Metrosideros polymorpha found along a 600–1800 m elevation/climate gradient, and on three substrate-age classes of 5, 20, and 65 kyr. We also analyzed how alien tree invasion, canopy species dominance and topographic relief influence AGB levels. Canopy vertical profiles derived from lidar measurements were strong predictors (r ² = 0.78) of AGB across sites and species. Mean AGB ranged from 48 to 363 Mg ha⁻¹ in native forest stands. Increasing elevation corresponded to a 53–84% decrease in AGB levels, depending upon substrate age. Holding climate constant, changes in substrate age from 5 to 65 kyr corresponded to a 23–53% decline in biomass. Invasion by Psidium cattleianum and Ficus rubiginosa trees resulted in a 19–38% decrease in AGB, with these carbon losses mediated by substrate age. In contrast, the spread of former plantation tree species Fraxinus uhdei corresponded to a 7- to 10-fold increase in biomass. The effects of topographic relief at both local and regional scales were evident in the AGB maps, with poorly drained terrain harboring 76% lower biomass than forests on well-drained relief. Our results quantify the absolute and relative importance of environmental factors controlling spatial variation in tree biomass across a rain forest landscape, and highlight the rapid changes in carbon storage incurred following biological invasion. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users. Author Contributions  GPA and RFH conceived of or designed the study. GPA, RFH, TAV, DEK, and TKB performed research and analyzed data. GPA, RFH, DEK, and TKB contributed new methods or models. GPA wrote the article.     

Invasion of <Emphasis Type="Italic">Spartina alterniflora</Emphasis> Enhanced Ecosystem Carbon and Nitrogen Stocks in the Yangtze Estuary,China

Whether plant invasion increases ecosystem carbon (C) stocks is controversial largely due to the lack of knowledge about differences in ecophysiological properties between invasive and native species. We conducted a field experiment in which we measured ecophysiological properties to explore the response of the ecosystem C stocks to the invasion of Spartina alterniflora (Spartina) in wetlands dominated by native Scirpus mariqueter (Scirpus) and Phragmites australis (Phragmites) in the Yangtze Estuary, China. We measured growing season length, leaf area index (LAI), net photosynthetic rate (Pn), root biomass, net primary production (NPP), litter quality and litter decomposition, plant and soil C and nitrogen (N) stocks in ecosystems dominated by the three species. Our results showed that Spartina had a longer growing season, higher LAI, higher Pn, and greater root biomass than Scirpus and Phragmites. Net primary production (NPP) was 2.16 kg C m⁻² y⁻¹ in Spartina ecosystems, which was, on average, 1.44 and 0.47 kg C m⁻² y⁻¹ greater than that in Scirpus and Phragmites ecosystems, respectively. The litter decomposition rate, particularly the belowground decomposition rate, was lower for Spartina than Scirpus and Phragmites due to the lower litter quality of Spartina. The ecosystem C stock (20.94 kg m⁻²) for Spartina was greater than that for Scirpus (17.07 kg m⁻²), Phragmites (19.51 kg m⁻²) and the mudflats (15.12 kg m⁻²). Additionally, Spartina ecosystems had a significantly greater N stock (698.8 g m⁻²) than Scirpus (597.1 g m⁻²), Phragmites ecosystems (578.2 g m⁻²) and the mudflats (375.1 g m⁻²). Our results suggest that Spartina invasion altered ecophysiological processes, resulted in changes in NPP and litter decomposition, and ultimately led to enhanced ecosystem C and N stocks in the invaded ecosystems in comparison to the ecosystems with native species.     

A universal airborne LiDAR approach for tropical forest carbon mapping

Airborne light detection and ranging (LiDAR) is fast turning the corner from demonstration technology to a key tool for assessing carbon stocks in tropical forests. With its ability to penetrate tropical forest canopies and detect three-dimensional forest structure, LiDAR may prove to be a major component of international strategies to measure and account for carbon emissions from and uptake by tropical forests. To date, however, basic ecological information such as height–diameter allometry and stand-level wood density have not been mechanistically incorporated into methods for mapping forest carbon at regional and global scales. A better incorporation of these structural patterns in forests may reduce the considerable time needed to calibrate airborne data with ground-based forest inventory plots, which presently necessitate exhaustive measurements of tree diameters and heights, as well as tree identifications for wood density estimation. Here, we develop a new approach that can facilitate rapid LiDAR calibration with minimal field data. Throughout four tropical regions (Panama, Peru, Madagascar, and Hawaii), we were able to predict aboveground carbon density estimated in field inventory plots using a single universal LiDAR model (r ²  = 0.80, RMSE = 27.6 Mg C ha⁻¹). This model is comparable in predictive power to locally calibrated models, but relies on limited inputs of basal area and wood density information for a given region, rather than on traditional plot inventories. With this approach, we propose to radically decrease the time required to calibrate airborne LiDAR data and thus increase the output of high-resolution carbon maps, supporting tropical forest conservation and climate mitigation policy.     

Fusion of airborne LiDAR data and hyperspectral imagery for aboveground and belowground forest biomass estimation

Vegetation biomass is a key biophysical parameter for many ecological and environmental models. The accurate estimation of biomass is essential for improving the accuracy and applicability of these models. Light Detection and Ranging (LiDAR) data have been extensively used to estimate forest biomass. Recently, there has been an increasing interest in fusing LiDAR with other data sources for directly measuring or estimating vegetation characteristics. In this study, the potential of fused LiDAR and hyperspectral data for biomass estimation was tested in the middle Heihe River Basin, northwest China. A series of LiDAR and hyperspectral metrics were calculated to obtain the optimal biomass estimation model. To assess the prediction ability of the fused data, single and fused LiDAR and hyperspectral metrics were regressed against field-observed belowground biomass (BGB), aboveground biomass (AGB) and total forest biomass (TB). The partial least squares (PLS) regression method was used to reduce the multicollinearity problem associated with the input metrics. It was found that the estimation accuracy of forest biomass was affected by LiDAR plot size, and the optimal plot size in this study had a radius of 22 m. The results showed that LiDAR data alone could estimate biomass with a relative high accuracy, and hyperspectral data had lower prediction ability for forest biomass estimation than LiDAR data. The best estimation model was using a fusion of LiDAR and hyperspectral metrics (R² = 0.785, 0.893 and 0.882 for BGB, AGB and TB, respectively, with p < 0.0001). Compared with LiDAR metrics alone, the fused LiDAR and hyperspectral data improved R² by 5.8%, 2.2% and 2.6%, decreased AIC value by 1.9%, 1.1% and 1.2%, and reduced RMSE by 8.6%, 7.9% and 8.3% for BGB, AGB and TB, respectively. These results demonstrated that biomass accuracies could be improved by the use of fused LiDAR and hyperspectral data, although the improvement was slight when compared with LiDAR data alone. This slight improvement could be attributed to the complementary information contained in LiDAR and hyperspectral data. In conclusion, fusion of LiDAR and other remotely sensed data has great potential for improving biomass estimation accuracy.     

Invasion by an exotic tree alters above and belowground ecosystem components

With the widespread introduction and invasion of exotic plants there is a need for studies that quantify alterations of basic ecosystem structure and function. Ecosystem invasion by Melaleuca quinquenervia significantly altered both above- and belowground ecosystem components in this study. We measured the quantity and nutrient concentration of the litterfall, litter layer, and soil; microbial biomass pools; and rates of potentially mineralizable nitrogen and soil oxygen demand. Annual litterfall was 4.9 times higher in the non-invaded sites and contained 1.9 times more phosphorus than invaded sites. Non-invaded plots contained a larger litter layer compared to invaded plots: 2.4 ± 1.2 kg m⁻² and 0.62 ± 0.3 kg m⁻² , respectively. Lower nutrient concentration and quantity of the litter layer in the invaded plots led to changes in the aboveground storage of nutrients. In the invaded plots there was four times less carbon, seven times less nitrogen, and ten times less phosphorus stored in the organic litter layer compared to the non-invaded plots. Microbial biomass nutrient pools were consistently lower at both the 0–5 cm and 5–15 cm depth in the invaded soils compared to non-invaded soils, indicating a plant mediated change. Although M. quinquenervia altered microbial community structure, microbial activities were not different between invaded and non-invaded plots at either depth as measured by rates of soil oxygen demand and potentially mineralizable nitrogen. These changes may affect both native plant growth and water quality, and may act to promote and maintain site dominance by M. quinquenervia.     

Aboveground biomass increments over 26 years (1993–2019) in an old-growth cool-temperate forest in northern Japan

Assessing long-term changes in the biomass of old-growth forests with consideration of climate effects is essential for understanding forest ecosystem functions under a changing climate. Long-term biomass changes are the result of accumulated short-term changes, which can be affected by endogenous processes such as gap filling in small-scale canopy openings. Here, we used 26 years (1993–2019) of repeated tree census data in an old-growth, cool-temperate, mixed deciduous forest that contains three topographic units (riparian, denuded slope, and terrace) in northern Japan to document decadal changes in aboveground biomass (AGB) and their processes in relation to endogenous processes and climatic factors. AGB increased steadily over the 26 years in all topographic units, but different tree species contributed to the increase among the topographic units. AGB gain within each topographic unit exceeded AGB loss via tree mortality in most of the measurement periods despite substantial temporal variation in AGB loss. At the local scale, variations in AGB gain were partially explained by compensating growth of trees around canopy gaps. Climate affected the local-scale AGB gain: the gain was larger in the measurement periods with higher mean air temperature during the current summer but smaller in those with higher mean air temperature during the previous autumn, synchronously in all topographic units. The influences of decadal summer and autumn warming on AGB growth appeared to be counteracting, suggesting that the observed steady AGB increase in KRRF is not fully explained by the warming. Future studies should consider global and regional environmental factors such as elevated CO₂ concentrations and nitrogen deposition, and include cool-temperate forests with a broader temperature range to improve our understanding on biomass accumulation in this type of forests under climate change.

     

Understory Invasion by <Emphasis Type="Italic">Acacia longifolia</Emphasis> Alters the Water Balance and Carbon Gain of a Mediterranean Pine Forest

In water-limited ecosystems, where potential evapotranspiration exceeds precipitation, it is often assumed that plant invasions will not increase total ecosystem water use, because all available water is evaporated or transpired regardless of vegetation type. However, invasion by exotic species, with high water use rates, may potentially alter ecosystem water balance by reducing water available to native species, which may in turn impact carbon assimilation and productivity of co-occurring species. Here, we document the impact of invasion by an understory exotic woody species (Acacia longifolia) in a semi-arid Mediterranean dune pine forest. To quantify the effects of this understory leguminous tree on the water use and carbon fixation rates of Pinus pinaster we compare an invaded and a non-invaded stand. A. longifolia significantly altered forest structure by increasing plant density and leaf area index in the mid-stratum of the invaded forest. A. longifolia contributed significantly to transpiration in the invaded forest (up to 42%) resulting in a slight increase in stand transpiration in the invaded relative to non-invaded forest. More importantly, both water use and carbon assimilation rates of P. pinaster were significantly reduced in the invaded relative to non-invaded stand. Therefore, this study shows that exotic plant invasions can have significant impacts on hydrological and carbon cycling even in water-limited semi-arid ecosystems through a repartitioning of water resources between the native and the invasive species.     

Effects of nutrient additions on plant biomass and diversity of the herbaceous-subshrub layer of a Brazilian savanna (Cerrado)

The Brazilian Cerrado is a diversity hotspot due to its high level of endemism and rapid loss of habitats. It is estimated that the number of herbaceous species is four times higher than that of woody species. Increasing levels of nitrogen additions to natural ecosystems have been indicated as a determinant of biodiversity loss. We investigated the effects of nutrient additions on the productivity (aboveground and belowground) and on diversity of the herbaceous-subshrub layer of a Brazilian savanna (cerrado stricto sensu). The experiment was carried out in the IBGE Ecological Reserve, near Brasília, Brazil. Between 1998 and 2006, N, P, N plus P, or Ca were applied to sixteen 225 m² plots, arranged in a completely randomized design. Aboveground biomass was compared 1 year after the first fertilization and 10 years later. Floristic diversity was significantly different (P < 0.01) between the treatments. The highest and lowest species richness were presented in control and NP, respectively. The addition of P alone or in combination with N induced invasion by Melinis minutiflora (exotic C₄ grass). The aboveground biomass of this species was higher in NP and P plots. In the N treatment, Echinolaena inflexa (native C₃ grass) presented elevated cover and biomass but M. minutiflora was absent. The invasion by alien species resulted in negative impacts on native grass species. Besides changes in aboveground biomass, addition of N and P also led, although to a lesser extent, to changes in the root morphology and biomass, but these responses were modulated by seasonal variation in soil moisture. The results suggest that environmental changes in nutrient availability can lead to important consequences for diversity and functioning of this savanna where the numerous rare species have more chance to persist under dystrophic conditions as some species that tend to be dominant would be less competitive.     

Remotely sensed C3 and C4 grass species aboveground biomass variability in response to seasonal climate and topography

Seasonal climate and topography influence C3 and C4 grass species aboveground biomass (AGB). Climate change further threatens these grasses AGB, thereby compromising their ability to provide ecosystem goods and services. This emphasises the need to monitor their AGB for well‐informed management. New‐generation sensors, with improved resolution capabilities present an opportunity to explore C3 and C4 AGB. This study therefore investigated the response of remotely sensed C3 and C4 grasses AGB to seasonal climate and topography. Overall, the spatial and temporal responses of AGB due to seasonal climate and topography were observed across the study area. For example, in March, a marked increase in C4 AGB was associated with an increase in rainfall, with the highest significant positive relationship (R² = 0.82, p < 0.005). Elevation had very significant positive relationship (R² = 0.84; p < 0.005) with C3 and highest negative (R² = ?0.77; p < 0.005) with C4 AGB. During the winter fall, AGB significantly decreased from averages of 2.592 and 1.101 kg/m² in winter (May), to 0.718 and 0.469 kg/m² in August, for C3 and C4 grasses, respectively. These findings provide a key step in monitoring rangelands and assessing management practices to boost productivity.     

The secondary invasion of giant African land snail has little impact on litter or seedling dynamics in rainforest

In the absence of empirical evidence, invasive species are often assumed to have negative impacts because of their conspicuously high abundance. The giant African land snail Achatina (Lissachatina) fulica is one such invader where its impact in natural ecosystems remains completely untested. On Christmas Island (Indian Ocean), A. fulica has become established across large tracts of rainforest following the impacts of invasive yellow crazy ant (Anoplolepis gracilipes) in mutualism with non‐native scale insects. Yellow crazy ants facilitate the secondary invasion of A. fulica by extirpating native red land crabs (Gecarcoidea natalis) that are normally effective predators of A. fulica. We used a multifaceted approach to investigate some potential impacts of abundant A. fulica in invaded rainforest. Over the course of a wet season, diel activity transects showed that A. fulica consumed detrital material almost exclusively. However, stable isotope analysis did not confidently identify A. fulica as a predominantly detritivorous species. We found no statistically significant treatment effects of A. fulica exclusion on standing leaf litter and seedling recruitment processes during a 6‐month manipulative field study. However, litter cover and biomass did remain slightly higher where A. fulica were excluded, albeit with overlapping confidence intervals with control plots. Our study constitutes the first empirical test for impact of A. fulica in a natural ecosystem and suggests that for Christmas Island rainforest, this species is not a damaging invader. Other studies will need to assess the impacts of A. fulica in other natural areas before these findings could be considered broadly applicable.     

Influences of vegetation,model, and data parameters on forest aboveground biomass assessment using an area-based approach

Although aboveground biomass (AGB) estimation using area-based approaches (ABAs) and its application to forestry have been actively researched through three decades, this technology has been little operationalized in the Central European forest sector. That means specific recommendations are needed in order to apply ABA for forest biomass modelling in this region. The present study was directed to filling such gaps while examining the effect of input ABA parameters on AGB model quality in conditions of mixed mountainous forests in Central Europe. Specific objectives were to assess whether the strength of the AGB model can be impacted by 1) canopy conditions (leaf-on and leaf-off), 2) airborne LiDAR point density (2.5, 5.0, 7.5, 10.0 points/m²), 3) field methods to estimate AGB (with regeneration components or without), and 4) machine learning methods (AdaBoost, Random decision forest, multilayer neural network, and Bayesian ridge regression). The results show that canopy conditions and airborne LiDAR point densities did not affect the strength of the AGB model, but that model's strength was affected by the vegetation regeneration component in the field biomass reference and by the machine learning method tested for modelling. AdaBoost and random decision forest were the most successful methods. To evaluate the quality of an AGB model it is recommended to combine several individual evaluation functions into the model score. The study highlights several recommendations to follow when estimating AGB from ALS using an ABA in Central European forests.     

Estimating seasonal aboveground biomass of a riparian pioneer plant community: An exploratory analysis by canopy structural data

The aboveground biomass (AGB) of vegetation is of central importance for ecosystem services by providing a measure of productivity. Models have been developed for estimating AGB via canopy structural variables in both fundamental and applied ecological studies. However, the potential of canopy structural variables for describing AGB dynamics throughout a growing season are still unclear. This study focuses on the AGB seasonal dynamics of a pioneer community, Cynodon dactylon (L.) Pers. (Bermuda grass), in a newly-formed riparian habitat at China’s Three Gorges Reservoir. The objectives are (1) to determine the most important structural variable for estimating AGB at different growing stages during the season, and (2) to develop a model that can estimate AGB at the different growing stages and using multiple structural variables. We sampled the C. dactylon community six times during the growing season from May to September 2016. Six variables were engaged in the analysis, including five canopy structural variables, i.e., canopy height (H), canopy cover (CC), leaf area index (LAI), the volume related variables V_LAI (H × LAI) and V_CC (H × CC), and one seasonal growth effect variable (SV). We conducted univariate linear regression analysis to determine the most important estimator of AGB and the best subset regression analysis were used to develop the AGB estimation model. The detected most important AGB estimator changed with different growing stages throughout a season. Canopy structural characteristics of the community are key factors for determining such changes. Cover was the most important variable for AGB estimation during the early growing season and V_LAI was the most important variable in the mid and end of the growing season. The developed best multivariate models explained an additional 11% in AGB variance on average for the different growing stages compared with the univariate models using the most important estimators. SV was found to be useful in developing an acceptance general AGB estimation model appropriate for the entire growing season. The findings of this study are expected to provide knowledge for guiding sampling work and to assist with modeling AGB and understanding the AGB seasonal dynamics in the future.     

Canopy structure,photosynthetic capacity and nitrogen distribution in adjacent mixed and monospecific stands of <Emphasis Type="Italic">Phragmites australis</Emphasis> and <Emphasis Type="Italic">Typha latifolia</Emphasis>

Shifts in canopy structure associated with nonnative plant invasions may interact with species-specific patterns of canopy resource allocation to reinforce the invasion process. We documented differences in canopy light availability and canopy resource allocation in adjacent monospecific and mixed stands of Phragmites australis and Typha spp. in a Great Lakes coastal wetland presently undergoing Phragmites invasion to better understand how light availability influences leaf nitrogen content (N_mass) and photosynthetic capacity (A_max) in these species. Due to their horizontally oriented leaves, light attenuates more rapidly in monospecific stands of Phragmites than in monospecific stands of Typha, where leaves are more vertically-oriented. Whereas Typha canopies followed our prediction that patterns of N_mass and A_max should closely parallel patterns of canopy light availability, N_mass and A_max were consistent throughout Phragmites’ canopies. Moreover, we observed overall greater N_mass and lower photosynthetic nitrogen use efficiency in leaves of Phragmites than in leaves of Typha. Improved understanding of the link between N_mass and A_max in these canopies should improve our understanding of carbon and nitrogen cycling consequences of Phragmites invasion in wetland ecosystems.     

Carbon stocks in the Guinea savanna of Ghana: estimates from three protected areas

Savannas are widespread in sub‐Saharan Africa (SSA) and play a major role in the global carbon balance. Extensive quantification of savanna carbon stocks in SSA will therefore contribute to better accounting of the global carbon budget in the era of climate change. In this study, we investigated the spatial distribution of carbon stocks of different soil fractions and aboveground biomass within three forest reserves in the Guinea savanna zone of Ghana. Soil carbon stocks (SCSs) ranged from 4.80 to 12.61 Mg C/ha in surface soils (0–10 cm depth). Higher SCSs were associated with the silt +clay fraction than microaggregates and small macroaggregates in all three reserves. Relative to the dominant tree species (Vitellaria paradoxa), the highest SCSs were recorded under the sub‐canopy (SC), drip line (DL), and interspace (2 * SC + DL) zones for the Klupene, Sinsablegbinni, and Kenikeni forest reserves, respectively. The highest tree carbon stock was 60.01 Mg C/ha in Kenikeni. Sinsablegbinni had an average stock of 26.74 Mg C/ha and had the highest tree density. Average carbon capture by a single tree ranged from 0.04 to 0.34 Mg C. Aboveground grass carbon stock ranged from 0.08 to 0.47 Mg C/ha, while the belowground carbon stock ranged from 0.03 to 0.44 Mg C/ha. Accumulation of carbon in the aboveground grass biomass was greater at Klupene with low forest cover.     

Genet dynamics of a regenerating dwarf bamboo population across heterogeneous light environments in a temperate forest understorey

Despite the advantage of plant clonality in patchy environments, studies focusing on genet demography in relation to spatially heterogeneous environments remain scarce. Regeneration of bamboos in forest understoreys after synchronous die‐off provides an opportunity for assessing how they come to proliferate across heterogeneous light environments. In a Japanese forest, we examined genet demography of a population of Sasa kurilensis over a 7‐year period starting 10 years after die‐off, shortly after which some genets began spreading horizontally by rhizomes. The aboveground biomass was estimated, and genets were discriminated in 9‐m² plots placed under both canopy gaps and closed canopies. Overall, the results suggest that the survival and spread of more productive genets and the spatial expansion of genets into closed canopies underlie the proliferation of S. kurilensis. Compared to canopy gaps, the recovery rate of biomass was much slower under closed canopies for the first 10 years after the die‐off, but became accelerated during the next 7 years. Genet survival was greater for more productive genets (with greater initial number of culms), and the spaces occupied by genets that died were often colonized afterward by clonal growth of surviving genets. The number of genets decreased under canopy gaps due to greater mortality, but increased under closed canopies where greater number of genets colonized clonally from outside the plots than genets died. The colonizing genets were more productive (having larger culms) than those originally germinated within the plots, and the contribution of colonizing genets to the biomass was greater under closed canopies. Our study emphasizes the importance of investigating genet dynamics over relevant spatiotemporal scales to reveal processes underlying the success of clonal plants in heterogeneous habitats.     

Regional Variations in Biomass Distribution in Brazilian Savanna Woodland

The Cerrado, the savanna biome in central Brazil, mostly comprised of woodland savanna, is experiencing intense and fast land use changes. To understand the changes in Cerrado carbon stocks, we present an overview of biomass distribution in different Cerrado vegetation types (i.e., grasslands, shrublands and forestlands). We surveyed 26 studies including 170 Cerrado sites. The grasslands presented mean total biomass of 24 Mg/ha, with 70 percent allocated in the belowground portion. In shrublands, the mean total biomass was 58 Mg/ha being 58 percent in the belowground portion. Finally, in forestlands the mean total biomass was 98 Mg/ha with 18 percent as belowground biomass. The surveyed studies presented 12 allometric equations for biomass estimate, most involving both diameter and height. Data on wood density for Cerrado shrubs and trees are not abundant and the average value was 0.66 g/cm³, similar to that found in the central portion of the Amazon Forest. We also examined the relationship between total precipitation and dry‐season intensity with biomass variation in the Cerrado shrubland using data from tropical rainfall measurement mission (TRMM) for the period 2000–2010. Dry‐season precipitation amount in cerrado areas in severe drought regions explained 29 percent of the variation in aboveground woody biomass. This finding is important in the face of the predictions of longer and more severe dry seasons in the region due to climate change.     

Vegetation shift from deciduous to evergreen dwarf shrubs in response to selective herbivory offsets carbon losses: evidence from 19 years of warming and simulated herbivory in the subarctic tundra

Selective herbivory of palatable plant species provides a competitive advantage for unpalatable plant species, which often have slow growth rates and produce slowly decomposable litter. We hypothesized that through a shift in the vegetation community from palatable, deciduous dwarf shrubs to unpalatable, evergreen dwarf shrubs, selective herbivory may counteract the increased shrub abundance that is otherwise found in tundra ecosystems, in turn interacting with the responses of ecosystem carbon (C) stocks and CO₂ balance to climatic warming. We tested this hypothesis in a 19‐year field experiment with factorial treatments of warming and simulated herbivory on the dominant deciduous dwarf shrub Vaccinium myrtillus. Warming was associated with a significantly increased vegetation abundance, with the strongest effect on deciduous dwarf shrubs, resulting in greater rates of both gross ecosystem production (GEP) and ecosystem respiration (ER) as well as increased C stocks. Simulated herbivory increased the abundance of evergreen dwarf shrubs, most importantly Empetrum nigrum ssp. hermaphroditum, which led to a recent shift in the dominant vegetation from deciduous to evergreen dwarf shrubs. Simulated herbivory caused no effect on GEP and ER or the total ecosystem C stocks, indicating that the vegetation shift counteracted the herbivore‐induced C loss from the system. A larger proportion of the total ecosystem C stock was found aboveground, rather than belowground, in plots treated with simulated herbivory. We conclude that by providing a competitive advantage to unpalatable plant species with slow growth rates and long life spans, selective herbivory may promote aboveground C stocks in a warming tundra ecosystem and, through this mechanism, counteract C losses that result from plant biomass consumption.     

Patterns of Below- and Aboveground Biomass in Eucalyptus populnea Woodland Communities of Northeast Australia along a Rainfall Gradient

In vegetated terrestrial ecosystems, carbon in below- and aboveground biomass (BGB, AGB) often constitutes a significant component of total-ecosystem carbon stock. Because carbon in the BGB is difficult to measure, it is often estimated using BGB to AGB ratios. However, this ratio can change markedly along resource gradients, such as water availability, which can lead to substantial errors in BGB estimates. In this study, BGB and AGB sampling was carried out in Eucalyptus populnea-dominated woodland communities of northeast Australia to examine patterns of BGB to AGB ratio and vertical root distribution at three sites along a rainfall gradient (367, 602, and 1,101 mm). At each site, a vegetation inventory was undertaken on five transects (100 × 4 m), and trees representing the E. populnea vegetation structure were harvested and excavated to measure aboveground and coarse-root (diameter of at least 15 mm) biomass. Biomass of fine and small roots (diameter less than 15 mm) at each site was estimated from 40 cores sampled to 1 m depth. The BGB to AGB ratio of E. populnea-dominated woodland plant communities declined from 0.58 at the xeric end to 0.36 at the mesic end of the rainfall gradient. This was due to a marked decline in AGB with increased aridity whereas the BGB was relatively stable. The vertical distribution of fine roots in the top 1 m of soil varied along the rainfall gradient. The mesic sites had more fine-root biomass (FRB) in the upper soil profile and less at depth than the xeric site. Accordingly, at the xeric site, a much larger proportion of FRB was found at depth compared to the mesic sites. The vertical distribution patterns of small roots of the E. populnea woodland plant communities were consistently )-shaped, with the highest biomass occurring at 15–30-cm depth. The potential significance of such a rooting pattern for grass–tree and shrub–tree co-existence in these ecosystems is discussed. Overall, our results revealed marked changes in BGB to AGB ratio of E. populnea woodland communities along a rainfall gradient. Because E. populnea woodlands cover a large area (96 M ha), their contribution to continental-scale carbon sequestration and greenhouse gas emission can be substantial. Use of the rainfall-zone-specific ratios found in this study, in lieu of a single generic ratio for the entire region, will significantly improve estimates of BGB carbon stocks in these woodlands. In the absence of more specific data, our results will also be relevant in other regions with similar vegetation and rainfall gradients (that is, arid and semiarid woodland ecosystems).