Changes In Aboveground Biomass Research Articles

Immediate responses of soil nematode community to addition of multiple nutrients in a degraded grassland

Nutrient addition is a widely-used strategy to restore degraded grasslands. It remains unknown whether and how the number of added nutrients affects the soil nematode community in degraded grasslands. We examined the immediate responses of taxonomic and functional composition of the soil nematode community to different numbers of added nutrients using factorial combinations of nitrogen (N), phosphorus (P), and potassium (K + micronutrients) in a degraded grassland of northern China. The taxonomic and functional composition of the soil nematode community generally formed a unimodal relationship with the number of added nutrients. Changes of soil pH after fertilization affected the structural stability and complexity of the soil nematode community. The magnitude of nematode functional responses to nutrient supply was driven by changes of plant aboveground biomass and soil pH. Soil nematode community showed non-linear responses to the variations of the number of added nutrients in a degraded grassland, which contrasts previous findings from plant community. The number of added nutrients should be given full consideration in formulating effective restoration strategies for degraded grasslands.

Land productivity dynamics in and around protected areas globally from 1999 to 2013.

Tracking changes in total biomass production or land productivity is an essential part of monitoring land transformations and long-term alterations of the health and productive capacity of land that are typically associated with land degradation. Persistent declines in land productivity impact many terrestrial ecosystem services that form the basis for sustainable livelihoods of human communities. Protected areas (PAs) are key to globally conserve biodiversity and ecosystem services that are critical for human well-being, and cover about 15% of the land worldwide. Here we globally assess the trends in land productivity in PAs of at least 10 km2 and in their unprotected surroundings (10 km buffers) from 1999 to 2013. We quantify the percentage of the protected and unprotected land that shows stable, increasing or decreasing trends in land productivity, quantified as long-term (15 year) changes in above-ground biomass derived from satellite-based observations with a spatial resolution of 1 km. We find that 44% of the land in PAs globally has retained the productivity at stable levels from 1999 to 2013, compared to 42% of stable productivity in the unprotected land around PAs. Persistent increases in productivity are more common in the unprotected lands around PAs (32%) than within PAs (18%) globally, while about 14% of the protected land and 12% of the unprotected land around PAs has experienced declines in land productivity. Oceania has the highest percentage of land with stable productivity in PAs (57%), whereas Europe has the lowest percentage (38%) and also the largest share of protected land with increasing land productivity (32%). We discuss the observed differences between PAs and unprotected lands, and between different parts of the world, in relation to different types and levels of human activities and their impact on land productivity. Our assessment of land productivity dynamics helps to characterise the state, pressures and changes in and around protected areas globally. Further research may focus on more detailed analyses to disentangle the relative contribution of specific drivers (from climate change to land use change) and their interaction with land productivity dynamics and potential land degradation in different regions of the world.

Temporal and Spatial Pattern Characteristics of Vegetation in Qaidam Basin and Its Response to Climate Change

vegetation is a sensitive indicator of climate change. The spatial-temporal dynamic changes of vegetation cover and aboveground biomass and their relationship with climate factors in Qaidam Basin in recent 13 years were studied by using vegetation index. The results are as follows: (1) the total area of vegetation in Qaidam Basin increased from 2002 to 2015, with a growth rate of 644.11km2/a (R2 = 0.4919). In recent 14 years, the change of vegetation area has been increasing → decreasing → increasing → decreasing, among which the vegetation area has been increasing continuously from 2009 to 2012; (2) During the period of 2002-2015, the vegetation area of each level of vegetation coverage showed an increasing trend, and the increasing rates were 300.2km2/a, 242.8km2/a and 101.2km2/a, respectively, which indicated that the vegetation ecology in Qaidam Basin was developing to a benign trend; (3) the aboveground biomass of vegetation was mainly low-yield vegetation less than 1500kg/hm2, followed by vegetation of 1500-3000kg/hm2, accounting for the total area of vegetation The proportion is less than 10%, and the vegetation area of other grades is very small, only scattered, while the high-yield vegetation larger than 6000kg/hm2 is distributed in the southeast of the basin and the alpine mountains around the basin; (4) there is a certain coupling relationship between the climate and vegetation change in Qaidam basin, which is reflected in the positive correlation between the total vegetation area and the annual precipitation, the precipitation from May to September and the precipitation in summer, and the correlation significance of summer precipitation > may September precipitation>annual precipitation. However, it was negatively correlated with winter precipitation, but not with autumn precipitation and annual average temperature (P > 0.5).

Protection status as determinant of carbon stock drivers in Cerrado sensu stricto

Abstract Aims Natural vegetation plays an important role in global carbon cycling and storage. Thus, the Cerrado (Brazilian savannah) is considered a carbon sink because of its intrinsic characteristics. Our aim was to evaluate how the aboveground biomass and biodiversity relationship change between three Cerrado remnants with different protection status: a ‘control area’ (Legal Reserve area), a protected area (PA) and a non-protected area (Non-PA). Methods All three studied fragments are situated in northern Minas Gerais state, Brazil. We estimated the aboveground carbon stocks based on the forest inventory. We also measured three dimensions of biodiversity metrics for each plot: functional trait dominance, taxonomic diversity and functional diversity. The following functional traits were evaluated for the species: wood density, maximum diameter and seed size. We carried out generalized linear models seeking to evaluate how carbon stocks, community-weighted mean (CWM) trait values, species richness and diversity, and functional diversity indices differ among the remnants. Important Findings The Cerrado areas without protection status had lower carbon stocks, species richness, species diversity, functional richness and functional dispersion, whereas both PA and Non-PA had lower CWM maximum diameter and seed size compared with the Legal Reserve control area. Generalized linear models showed that carbon stocks, species and functional richness metrics were correlated within and across sites, and thus, species richness could serve as a good proxy for functional richness and carbon stocks. The carbon stocks were positively driven by species richness and CWM maximum diameter, while they were negatively driven by functional dispersion. Functional richness, species diversity and CWM seed size appeared in the set of best models, but with no significant direct effect on carbon stocks. Thus, we concluded that absence of protection in the Cerrado areas decreases both species richness and carbon stocks.

Comparison of Statistical Modelling Approaches for Estimating Tropical Forest Aboveground Biomass Stock and Reporting Their Changes in Low-Intensity Logging Areas Using Multi-Temporal LiDAR Data

Accurately quantifying forest aboveground biomass (AGB) is one of the most significant challenges in remote sensing, and is critical for understanding global carbon sequestration. Here, we evaluate the effectiveness of airborne LiDAR (Light Detection and Ranging) for monitoring AGB stocks and change (ΔAGB) in a selectively logged tropical forest in eastern Amazonia. Specifically, we compare results from a suite of different modelling methods with extensive field data. The calibration AGB values were derived from 85 square field plots sized 50 × 50 m field plots established in 2014 and which were estimated using airborne LiDAR data acquired in 2012, 2014, and 2017. LiDAR-derived metrics were selected based upon Principal Component Analysis (PCA) and used to estimate AGB stock and change. The statistical approaches were: ordinary least squares regression (OLS), and nine machine learning approaches: random forest (RF), several variations of k-nearest neighbour (k-NN), support vector machine (SVM), and artificial neural networks (ANN). Leave-one-out cross-validation (LOOCV) was used to compare performance based upon root mean square error (RMSE) and mean difference (MD). The results show that OLS had the best performance with an RMSE of 46.94 Mg/ha (19.7%) and R² = 0.70. RF, SVM, and ANN were adequate, and all approaches showed RMSE ≤54.48 Mg/ha (22.89%). Models derived from k-NN variations all showed RMSE ≥64.61 Mg/ha (27.09%). The OLS model was thus selected to map AGB across the time-series. The mean (±sd—standard deviation) predicted AGB stock at the landscape level was 229.10 (±232.13) Mg/ha in 2012, 258.18 (±106.53) in 2014, and 240.34 (sd ± 177.00) Mg/ha in 2017, showing the effect of forest growth in the first period and logging in the second period. In most cases, unlogged areas showed higher AGB stocks than logged areas. Our methods showed an increase in AGB in unlogged areas and detected small changes from reduced-impact logging (RIL) activities occurring after 2012. We also detected that the AGB increase in areas logged before 2012 was higher than in unlogged areas. Based on our findings, we expect our study could serve as a basis for programs such as REDD+ and assist in detecting and understanding AGB changes caused by selective logging activities in tropical forests.

Predicting biomass dynamics at the national extent from digital aerial photogrammetry

The demand for precise mapping and monitoring of forest resources, such as above ground biomass (AGB), has increased rapidly. National accounting and monitoring of AGB requires regularly updated information based on consistent methods. While remote sensing technologies such as airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) have been shown to deliver the necessary 3D spatial data for AGB mapping, the capacity of repeat acquisition, remotely sensed, vegetation structure data for AGB monitoring has received less attention. Here, we use vegetation height models (VHMs) derived from repeat acquisition DAP data (with ALS terrain correction) to map and monitor woody AGB dynamics across Switzerland over 35 years (1983-2017 inclusive), using a linear least-squares regression approach. We demonstrate a consistent relationship between canopy height derived from DAP and field-based NFI measures of woody AGB across four inventory periods. Over the environmentally heterogeneous area of Switzerland, our models have a comparable predictive performance (R2 = 0.54) to previous work predicting AGB based on ALS metrics. Pearson correlation coefficients between measured and predicted changes in woody AGB over time increased with shorter time gaps (< 2 years) between image capture and field-based measurements, ranging between 0.76 and 0.34. A close temporal match between field surveys and remote sensing data acquisition is thus key to reliable mapping and monitoring of AGB dynamics, especially in areas where forest management and natural disturbances trigger relatively fast canopy dynamics. We show that VHMs derived from repeat DAP capture constitute a cost effective and reliable approach to map and monitor changes in woody AGB at a national extent and can provide an important information source for national carbon accounting and monitoring of ecosystem service provisioning.

Effects of long-term warming on the aboveground biomass and species diversity in an alpine meadow on the Qinghai-Tibetan Plateau of China

Ecosystems in high-altitude regions are more sensitive and respond more rapidly than other ecosystems to global climate warming. The Qinghai-Tibet Plateau (QTP) of China is an ecologically fragile zone that is sensitive to global climate warming. It is of great importance to study the changes in aboveground biomass and species diversity of alpine meadows on the QTP under predicted future climate warming. In this study, we selected an alpine meadow on the QTP as the study object and used infrared radiators as the warming device for a simulation experiment over eight years (2011–2018). We then analyzed the dynamic changes in aboveground biomass and species diversity of the alpine meadow at different time scales, including an early stage of warming (2011–2013) and a late stage of warming (2016–2018), in order to explore the response of alpine meadows to short-term (three years) and long-term warming (eight years). The results showed that the short-term warming increased air temperature by 0.31°C and decreased relative humidity by 2.54%, resulting in the air being warmer and drier. The long-term warming increased air temperature and relative humidity by 0.19°C and 1.47%, respectively, and the air tended to be warmer and wetter. The short-term warming increased soil temperature by 2.44°C and decreased soil moisture by 12.47%, whereas the long-term warming increased soil temperature by 1.76°C and decreased soil moisture by 9.90%. This caused the shallow soil layer to become warmer and drier under both short-term and longterm warming. Furthermore, the degree of soil drought was alleviated with increased warming duration. Under the long-term warming, the importance value and aboveground biomass of plants in different families changed. The importance values of grasses and sedges decreased by 47.56% and 3.67%, respectively, while the importance value of weeds increased by 1.37%. Aboveground biomass of grasses decreased by 36.55%, while those of sedges and weeds increased by 8.09% and 15.24%, respectively. The increase in temperature had a non-significant effect on species diversity. The species diversity indices increased at the early stage of warming and decreased at the late stage of warming, but none of them reached significant levels (P>0.05). Species diversity had no significant correlation with soil temperature and soil moisture under both short-term and long-term warming. Soil temperature and aboveground biomass were positively correlated in the control plots (P=0.014), but negatively correlated under the long-term warming (P=0.013). Therefore, eight years of warming aggravated drought in the shallow soil layer, which is beneficial for the growth of weeds but not for the growth of grasses. Warming changed the structure of alpine meadow communities and had a certain impact on the community species diversity. Our studies have great significance for the protection and effective utilization of alpine vegetation, as well as for the prevention of grassland degradation or desertification in high-altitude regions.

Nutrient addition increases grassland sensitivity to droughts.

Grasslands worldwide are expected to experience an increase in extreme events such as drought, along with simultaneous increases in mineral nutrient inputs as a result of human industrial activities. These changes are likely to interact because elevated nutrient inputs may alter plant diversity and increase the sensitivity to droughts. Dividing a system's sensitivity to drought into resistance to change during the drought and rate of recovery after the drought generates insights into different dimensions of the system's resilience in the face of drought. Here, we examine the effects of experimental nutrient fertilization and the resulting diversity loss on the resistance to and recovery from severe regional droughts. We do this at 13 North American sites spanning gradients of aridity, five annual grasslands in California, and eight perennial grasslands in the Great Plains. We measured rate of resistance as the change in annual aboveground biomass (ANPP) per unit change in growing season precipitation as conditions declined from normal to drought. We measured recovery as the change in ANPP during the postdrought period and the return to normal precipitation. Resistance and recovery did not vary across the 400-mm range of mean growing season precipitation spanned by our sites in the Great Plains. However, chronic nutrient fertilization in the Great Plains reduced drought resistance and increased drought recovery. In the California annual grasslands, arid sites had a greater recovery postdrought than mesic sites, and nutrient addition had no consistent effects on resistance or recovery. Across all study sites, we found that predrought species richness in natural grasslands was not consistently associated with rates of resistance to or recovery from the drought, in contrast to earlier findings from experimentally assembled grassland communities. Taken together, these results suggest that human-induced eutrophication may destabilize grassland primary production, but the effects of this may vary across regions and flora, especially between perennial and annual-dominated grasslands.

Using the random forest model and validated MODIS with the field spectrometer measurement promote the accuracy of estimating aboveground biomass and coverage of alpine grasslands on the Qinghai-Tibetan Plateau

Abstract Maintaining the aboveground biomass (AGB) and canopy cover (CC) of grassland is key for sustainable grassland management and rational conservation planning, especially for fragile regions of Qinghai-Tibetan Plateau (QTP). However, the estimation of AGB and CC with land use changes is often challenging due to poor availability of high-quality images of remote sensing or the large-scale field survey data. In this study, we used the transect survey method combining with quadrat measurements with 1200 plant samplings and near surface hyperspectral measurements at 180 sites to validate the MODIS data. An integrative approach combining the plant sampling, near surface hyperspectral measurements, remote sensing data interpretation, random forest modelling and Hurst phenomenon prediction was developed to accurately and efficiently estimate the CC and AGB of the alpine grasslands on the QTP from 2000 to 2017 and their future trends. The results showed: 1) estimation of AGB and CC in different land use types by integrating random forest with multiple factors (NDVI, latitude, longitude and altitude, grassland types) was more accurate; 2) the inter-annual changes of AGB and CC of the alpine grasslands presented significant fluctuations, with an increasing trend in the QTP; 3) the areas with improved vegetation conditions of AGB (66.55%) and CC (64.58%) were much larger than those with degraded vegetation conditions of AGB (33.45%) and CC (35.42%) in past 20 years. 4) there are 60.66% of the AGB and 59.87% of coverage showing sustainability and increasing in the future. Estimating the AGB and CC with multiple factors using the random forest and validated MODIS with the field spectrometer can improve the accuracy. The findings of this study can provide scientific basis for promoting the sustainability of grassland ecosystem through adaptive and rational management on the QTP and worldwide.

Chronic nitrogen addition promotes dissolved organic carbon accumulation in a temperate freshwater wetland

Temperate wetlands have been undergoing increased nitrogen (N) inputs in the past decades, yet its influence on dissolved organic carbon (DOC) dynamics is still elusive in these ecosystems. Here, using a field multi-level N addition (0, 6, 12, and 24 g N m−2 year−1) experiment, we investigated the changes in aboveground plant biomass, DOC production from plant litters, DOC biodegradation, and DOC concentration in surface water and soil pore water (0–15 cm depth) following 10 years of N addition in a freshwater marsh of Northeast China. We observed that, irrespective of N addition levels, N addition caused an increase in DOC production from plant litters under both non-flooded and flooded conditions. Conversely, DOC biodegradation was inhibited by N addition in both surface water and soil pore water. Because of enhanced DOC production from plant litters and declined DOC biodegradation, N addition elevated DOC concentration in surface water and soil pore water across the growing season. In addition, long-term N addition increased aboveground plant biomass, but decreased species richness. Our results suggest that long-term N enrichment promotes DOC accumulation through the contrasting effects on litter-derived DOC production and microbial decomposition of DOC in temperate wetlands.

Litter Inputs, but Not Litter Diversity, Maintain Soil Processes in Degraded Tropical Forests—A Cross-Continental Comparison

Land-use change in tropical forests can reduce biodiversity and ecosystem carbon (C) storage, but although changes in aboveground biomass C in human-modified tropical forests are well documented, patterns in the dynamics and storage of C belowground are less well characterised. To address this, we used a reciprocal litter transplant experiment to assess litter decomposition and soil respiration under distinct litter types in forested or converted habitats in Panama, Central America, and in Sabah, Malaysian Borneo. The converted habitats comprised a large clearing on the Panama Canal and oil palm plantation in Borneo; forested habitats comprised a 60-year old secondary forest in Panama and a disturbed forest in Borneo that was selectively logged until 2008. In each habitat, we installed mesocosms and litterbags with litter collected from old-growth forest, secondary forest or an introduced species: Elaeis guineensis in Borneo and Saccharum spontaneum in Panama. We measured litter mass loss, soil respiration, and soil microbial biomass during nine months at each site. Decomposition differed markedly between habitat types and between forest vs. introduced litter, but the decay rates and properties of old-growth and secondary forest litters in the forest habitats were remarkably similar, even across continents. Slower decomposition of all litter types in the converted habitats was largely explained by microclimate, but the faster decay of introduced litter was linked to lower lignin content compared to the forest litter. Despite marked differences in litter properties and decomposition, there was no effect of litter type on soil respiration or microbial biomass. However, regardless of location, litter type, and differences in soil characteristics, we measured a similar decline in microbial activity and biomass in the absence of litter inputs. Interestingly, whereas microbial biomass and soil respiration increased substantially in response to litter inputs in the forested habitats and the converted habitat in Panama, there was little or no corresponding increase in the converted habitat in Borneo, indicating that soil recovery capacity had declined substantially in oil palm plantations. Overall, our results suggest that litter inputs are essential to preserve key soil processes, but litter diversity may be less important, especially in highly disturbed habitats.

Dynamic Changes of Aboveground Biomass of Vegetation in Qaidam Basin

In order to monitor the temporal and spatial dynamics of vegetation in the Qaidam Basin, the ground-based vegetation biomass model of the basin was established by using basin ground measurements data during 2016-2018 and NDVI of MOD13Q1: Y=0.0002X2-0.863X+2052.4(R2=0.7656, P<0.01), and using this model to estimate the long-term aboveground biomass data set of the vegetation of basin. Above-ground biomass of vegetation is mainly low-yield vegetation of less than 1500 kg/hm2, followed by vegetation of 1500-3000 kg/hm2, the area of which accounts for less than 10% of the total vegetation area, and the vegetation of the other levels is very small, only scattered, High-yield vegetation which is greater than 6000 kg/hm2 is distributed in the southeast of the basin and in the alpine mountains around the basin

Decline of large-diameter trees in a bamboo-dominated forest following anthropogenic disturbances in southwestern Amazonia

Reduction in the aboveground biomass of larger trees is the main consequence of disturbances in open forests dominated by bamboo. Because these trees are of central importance both for ecosystem function and for the economic value of the forest for management, the impact on these trees due to the increase of bamboo abundance following anthropogenic disturbances is both an environmental and a commercial concern. Bamboo-dominated forests in southwestern Amazonia are increasingly exposed to the combined impacts of fire and selective logging. Although the climbing bamboos (Guadua spp.) are considered native species of these forests, disturbances contribute to a discontinuous canopy, which is an ideal scenario for an increase in abundance of these opportunistic plants. The regeneration of tree biomass is limited in these cases, decreasing the carbon stock of the forest. This study compares changes in bamboo abundance and forest structure in the face of forest fire and post-burn logging in the municipality (county) of Rio Branco, Acre state, Brazil. The study was conducted on the Transacreana Highway (AC 090) in the eastern portion of Acre state, Brazil. We compared changes in bamboo abundance and aboveground biomass (AGB) of an area of forest with no known recent disturbances to areas in the same forest that had been disturbed by fire and post-burn logging, which are frequent sources of disturbance in this region. The live and dead AGB values were estimated by field inventory in 2016, which was 11 years after a fire and 9 years after selective logging. The AGB values for trees and palms were estimated by allometric equations in three 2-ha areas. Bamboo abundance was expressed both by bamboo biomass (Mg ha−1) and culm density (culms ha−1), sampled by direct measurements in three 200-m2 areas. Bamboo abundance was over 20% higher in forest that had been burned but not logged, as compared to undisturbed forest. Compared to undisturbed plots, aboveground forest biomass (live + dead) was 34% lower in plots exposed to fire but not logging, and 36% lower if exposed to both. Live trees and palms represented 77% of the total forest biomass (live + dead), and almost a half of this contribution (41%) was in individuals in the largest diameter class (diameter at breast height > 50 cm). Increase in the level of impact led to a reduction in aboveground carbon stock of the forest. One of the main consequences of disturbances in open forests dominated by bamboo is reduction of live trees and palms, especially in the diameter at breast height (DBH) class over 50 cm.

Why do crop models diverge substantially in climate impact projections? A comprehensive analysis based on eight barley crop models

Robust projections of climate impact on crop growth and productivity by crop models are key to designing effective adaptations to cope with future climate risk. However, current crop models diverge strongly in their climate impact projections. Previous studies tried to compare or improve crop models regarding the impact of one single climate variable. However, this approach is insufficient, considering that crop growth and yield are affected by the interactive impacts of multiple climate change factors and multiple interrelated biophysical processes. Here, a new comprehensive analysis was conducted to look holistically at the reasons why crop models diverge substantially in climate impact projections and to investigate which biophysical processes and knowledge gaps are key factors affecting this uncertainty and should be given the highest priorities for improvement. First, eight barley models and eight climate projections for the 2050s were applied to investigate the uncertainty from crop model structure in climate impact projections for barley growth and yield at two sites: Jokioinen, Finland (Boreal) and Lleida, Spain (Mediterranean). Sensitivity analyses were then conducted on the responses of major crop processes to major climatic variables including temperature, precipitation, irradiation, and CO2, as well as their interactions, for each of the eight crop models. The results showed that the temperature and CO2 relationships in the models were the major sources of the large discrepancies among the models in climate impact projections. In particular, the impacts of increases in temperature and CO2 on leaf area development were identified as the major causes for the large uncertainty in simulating changes in evapotranspiration, above-ground biomass, and grain yield. Our findings highlight that advancements in understanding the basic processes and thresholds by which climate warming and CO2 increases will affect leaf area development, crop evapotranspiration, photosynthesis, and grain formation in contrasting environments are needed for modeling their impacts.

Assessing differences in the response of forest aboveground biomass and composition under climate change in subtropical forest transition zone

The subtropical forest transition zone in southern China is a typical transition zone with high coverage and diverse vegetation. Projected climate change will affect physiological processes of trees, which would consequently alter the forest aboveground biomass (AGB) and composition at broad spatial scales. However, spatially heterogeneous responses may also be shaped by climate change, succession, and harvesting in different forest habitats. The objectives of this study were to assess the changes in subtropical forest AGB and composition in response to climate change, while comparing the responses of two similar forest landscapes: Taihe County (TH) and Longnan County (LN). We used a loose-coupling of PnET-II with LANDIS-II to simulate changes in forest AGB and composition under climate change scenarios (Current climate, RCP2.6, RCP4.5, RCP6.0, and RCP8.5) with harvest disturbances. Our simulation results demonstrated that forest AGB and composition were significantly affected by climate change in both landscapes. Changes in forest AGB was mostly driven by succession and harvest, but climate change also greatly contribute to the variation in AGB of deciduous broad-leaved forests (DBF), and coniferous forests (CF). Moreover, a larger area of LN experienced biomass reduction compared to TH, specifically under the RCP8.5 scenario. Given our estimates of the response in forest AGB and composition under climate change scenarios across different periods, we recommend that the regional forest management should be localized and should consider the effects of climate change through time in their planning schemes.

Biomass and dominance of conservative species drive above-ground biomass productivity in a mediterranean-type forest of Chile

BackgroundForest productivity has a pivotal role in human well-being. Vegetation quantity, niche complementarity, mass-ratio, and soil resources are alternative/complementary ecological mechanisms driving productivity. One challenge in current forest management depends on identifying and manipulating these mechanisms to enhance productivity. This study assessed the extent to which these mechanisms control above-ground biomass productivity (AGBP) of a Chilean mediterranean-type matorral. AGBP measured as tree above-ground biomass changes over a 7-years period, was estimated for twelve 25 m × 25 m plots across a wide range of matorral compositions and structures. Variables related to canopy structure, species and functional diversity, species and functional dominance, soil texture, soil water and soil nitrogen content were measured as surrogates of the four mechanisms proposed. Linear regression models were used to test the hypotheses. A multimodel inference based on the Akaike’s information criterion was used to select the best models explaining AGBP and for identifying the relative importance of each mechanism.ResultsVegetation quantity (tree density) and mass-ratio (relative biomass of Cryptocarya alba, a conservative species) were the strongest drivers increasing AGBP, while niche complementarity (richness species) and soil resources (sand, %) had a smaller effect either decreasing or increasing AGBP, respectively. This study provides the first assessment of alternative mechanisms driving AGBP in mediterranean forests of Chile. There is strong evidence suggesting that the vegetation quantity and mass-ratio mechanisms are key drivers of AGBP, such as in other tropical and temperate forests. However, in contrast with other studies from mediterranean-type forests, our results show a negative effect of species diversity and a small effect of soil resources on AGBP.ConclusionAGBP in the Chilean matorral depends mainly on the vegetation quantity and mass-ratio mechanisms. The findings of this study have implications for matorral restoration and management for the production of timber and non-timber products and carbon sequestration.

Mangrove Mapping and Above-Ground Biomass Change Detection using Satellite Images in Coastal Areas of Thai Binh Province, Vietnam

Mangroves are recognized as a highly valuable resource due to their provision of multiple ecosystem services. Therefore, mangrove ecosystems mapping and monitoring is a crucial objective, especially for tropical regions. Thai Binh province is one of the most important mangrove ecosystems in Vietnam. The mangrove ecosystem in this province has faced threats of deforestation from urban development, land reclamation, tourism activities, and natural disasters. Recently, to maintain the fundamental functions of the ecosystems, a large mangrove area was planted in Thai Binh. The aim of this research is to detect the change in the mangrove areas and to create an aboveground biomass map for mangrove forests in Thai Binh province. Landsat and Sentinel-2 satellite images from 1998 to 2018 were analysed using the supervised classification method to detect mangrove area change. Mangrove Above-ground Biomass (AGB) was estimated using linear regression between vegetation indices and field AGB survey. The accuracy assessment for the classified images of 1998, 2003 and 2007, 2013 and 2018 are 93%, 86%, 96%, 94% and 91% respectively with kappa of 0.8881, 0.7953, 0.9357, 0.9114 and 0.8761. The mangrove cover in the study area was estimated at 5874.93 ha in 1998. This figure decreased significantly to 4433.85 ha in 2007, before recovery began to take place in the study area, which was estimated at 6587.88 ha in 2018. In 1998, the average AGB in this study area was 22.57 ton/ha, and in 2018 it was 37.74 ton/ha with a standard error of 12.41 ton/ha and the root mean square error (RMSE) was ±12.08 ton/ha.

Increased precipitation offsets the negative effect of warming on plant biomass and ecosystem respiration in a Tibetan alpine steppe

The Tibetan Plateau has become warmer and wetter in recent decades, and the warming of more than 2 °C has been considered as a risk threshold that may lead to irreversible changes in arid and semi-arid grassland ecosystems. However, few data have examined the extent to which the projected increase of precipitation may offset the negative effect of 2 °C warming on aboveground biomass (AGB) and ecosystem respiration (Re) in the vast alpine grasslands. We conducted a field manipulative experiment to investigate the combined effects of 2 °C warming plus 15% and 30% increased precipitation on AGB and Re in an alpine steppe. We observed vegetation cover, AGB, Re, soil temperature (ST), soil moisture (SM), and soil organic carbon (SOC) in the growing seasons of 2013 and 2014. Thornthwaite moisture index (MI) in the growing season (May–September) was calculated for each experimental treatment. Experimental warming generally increased ST and reduced SM and MI, and consequently caused significant reductions in vegetation cover, AGB and Re. Increased precipitation typically stimulated AGB and Re. Compared to the control, relative changes in AGB and Re increased from a negative value under warming with ambient precipitation to a positive value under warming plus 15% and 30% increased precipitation. In pooled data across treatments and years, the changes of AGB and Re showed a positive linear relation to the warming/watering induced variation of MI. The structural equation modeling indicated that AGB and SM rather than ST and SOC were the major factors driving Re during the growing season. In addition, experimental warming decreased the temperature sensitivity of Re (Q10), whereas increased precipitation had a positive effect on Q10. Our data demonstrate that the water deficit induced by 2 °C warming and its negative effect on AGB and Re can be offset by >15% increased precipitation in a semi-arid alpine grassland on the Tibetan Plateau. The change in balance of precipitation and evapotranspiration is an ecologically meaningful metric for generally describing the spatiotemporal variability of soil water availability and ecosystem function under climate change.

Classifications of Forest Change by Using Bitemporal Airborne Laser Scanner Data

Changes in forest areas have great impact on a range of ecosystem functions, and monitoring forest change across different spatial and temporal resolutions is a central task in forestry. At the spatial scales of municipalities, forest properties and stands, local inventories are carried out periodically to inform forest management, in which airborne laser scanner (ALS) data are often used to estimate forest attributes. As local forest inventories are repeated, the availability of bitemporal field and ALS data is increasing. The aim of this study was to assess the utility of bitemporal ALS data for classification of dominant height change, aboveground biomass change, forest disturbances, and forestry activities. We used data obtained from 558 field plots and four repeated ALS-based forest inventories in southeastern Norway, with temporal resolutions ranging from 11 to 15 years. We applied the k-nearest neighbor method for classification of: (i) increasing versus decreasing dominant height, (ii) increasing versus decreasing aboveground biomass, (iii) undisturbed versus disturbed forest, and (iv) forestry activities, namely untouched, partial harvest, and clearcut. Leave-one-out cross-validation revealed overall accuracies of 96%, 95%, 89%, and 88% across districts for the four change classifications, respectively. Thus, our results demonstrate that various changes in forest structure can be classified with high accuracy at plot level using data from repeated ALS-based forest inventories.

Estimating aboveground net biomass change for tropical and subtropical forests: Refinement of IPCC default rates using forest plot data.

As countries advance in greenhouse gas (GHG) accounting for climate change mitigation, consistent estimates of aboveground net biomass change (∆AGB) are needed. Countries with limited forest monitoring capabilities in the tropics and subtropics rely on IPCC 2006 default ∆AGB rates, which are values per ecological zone, per continent. Similarly, research into forest biomass change at a large scale also makes use of these rates. IPCC 2006 default rates come from a handful of studies, provide no uncertainty indications and do not distinguish between older secondary forests and old‐growth forests. As part of the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories, we incorporate ∆AGB data available from 2006 onwards, comprising 176 chronosequences in secondary forests and 536 permanent plots in old‐growth and managed/logged forests located in 42 countries in Africa, North and South America and Asia. We generated ∆AGB rate estimates for younger secondary forests (≤20 years), older secondary forests (>20 years and up to 100 years) and old‐growth forests, and accounted for uncertainties in our estimates. In tropical rainforests, for which data availability was the highest, our ∆AGB rate estimates ranged from 3.4 (Asia) to 7.6 (Africa) Mg ha−1 year−1 in younger secondary forests, from 2.3 (North and South America) to 3.5 (Africa) Mg ha−1 year−1 in older secondary forests, and 0.7 (Asia) to 1.3 (Africa) Mg ha−1 year−1 in old‐growth forests. We provide a rigorous and traceable refinement of the IPCC 2006 default rates in tropical and subtropical ecological zones, and identify which areas require more research on ∆AGB. In this respect, this study should be considered as an important step towards quantifying the role of tropical and subtropical forests as carbon sinks with higher accuracy; our new rates can be used for large‐scale GHG accounting by governmental bodies, nongovernmental organizations and in scientific research.