Simple measures of climate, soil properties and plant traits predict national-scale grassland soil carbon stocks

Soil carbon (C) storage is a key ecosystem service. Soil C stocks play a vital role in soil fertility and climate regulation, but the factors that control these stocks at regional and national scales are unknown, particularly when their composition and stability are considered. As a result, their mapping relies on either unreliable proxy measures or laborious direct measurements. Using data from an extensive national survey of English grasslands, we show that surface soil (0–7 cm) C stocks in size fractions of varying stability can be predicted at both regional and national scales from plant traits and simple measures of soil and climatic conditions. Soil C stocks in the largest pool, of intermediate particle size (50–250 μm), were best explained by mean annual temperature (MAT), soil pH and soil moisture content. The second largest C pool, highly stable physically and biochemically protected particles (0·45–50 μm), was explained by soil pH and the community abundance-weighted mean (CWM) leaf nitrogen (N) content, with the highest soil C stocks under N-rich vegetation. The C stock in the small active fraction (250–4000 μm) was explained by a wide range of variables: MAT, mean annual precipitation, mean growing season length, soil pH and CWM specific leaf area; stocks were higher under vegetation with thick and/or dense leaves. Testing the models describing these fractions against data from an independent English region indicated moderately strong correlation between predicted and actual values and no systematic bias, with the exception of the active fraction, for which predictions were inaccurate. Synthesis and applications. Validation indicates that readily available climate, soils and plant survey data can be effective in making local- to landscape-scale (1–100 000 km2) soil C stock predictions. Such predictions are a crucial component of effective management strategies to protect C stocks and enhance soil C sequestration.

Deforestation and forest degradation monitoring and assessment of biomass and carbon stock of lowland rainforest in the Analanjirofo region, Madagascar

Madagascar is currently developing a policy and strategies to enhance the sustainable management of its natural resources, encouraged by United Nations Framework Convention on Climate Change (UNFCCC) and REDD. To set up a sustainable financing scheme methodologies have to be provided that estimate, prevent and mitigate leakage, develop national and regional baselines, and estimate carbon benefits. With this research study this challenge was tried to be addressed by analysing a lowland rainforest in the Analanjirofo region in the district of Soanierana Ivongo, North East of Madagascar. For two distinguished forest degradation stages: “low degraded forest” and “degraded forest” aboveground biomass and carbon stock was assessed. The corresponding rates of carbon within those two classes were calculated and linked to a multi-temporal set of SPOT satellite data acquired in 1991, 2004 and 2009. Deforestation and particularly degradation and the related carbon stock developments were analysed. With the assessed data for the 3 years 1991, 2004 and 2009 it was possible to model a baseline and to develop a forest prediction for 2020 for Analanjirofo region in the district of Soanierana Ivongo. These results, developed applying robust methods, may provide important spatial information regarding the priorities in planning and implementation of future REDD+ activities in the area.

Inverse modelling of the 14C bomb pulse in stalagmites to constrain the dynamics of soil carbon cycling at selected European cave sites

The decomposition of soil organic matter (SOM) is temperature dependent, but its response to a future warmer climate remains equivocal. Enhanced rates of decomposition of SOM under increased global temperatures might cause higher CO2 emissions to the atmosphere, and could therefore constitute a strong positive feedback. The magnitude of this feedback however remains poorly understood, primarily because of the difficulty in quantifying the temperature sensitivity of stored, recalcitrant carbon that comprises the bulk (>90%) of SOM in most soils. In this study we investigated the effects of climatic conditions on soil carbon dynamics using the attenuation of the 14C ‘bomb’ pulse as recorded in selected modern European speleothems. These new data were combined with published results to further examine soil carbon dynamics, and to explore the sensitivity of labile and recalcitrant organic matter decomposition to different climatic conditions. Temporal changes in 14C activity inferred from each speleothem was modelled using a three pool soil carbon inverse model (applying a Monte Carlo method) to constrain soil carbon turnover rates at each site. Speleothems from sites that are characterised by semi-arid conditions, sparse vegetation, thin soil cover and high mean annual air temperatures (MAATs), exhibit weak attenuation of atmospheric 14C ‘bomb’ peak (a low damping effect, D in the range: 55–77%) and low modelled mean respired carbon ages (MRCA), indicating that decomposition is dominated by young, recently fixed soil carbon. By contrast, humid and high MAAT sites that are characterised by a thick soil cover and dense, well developed vegetation, display the highest damping effect (D = c. 90%), and the highest MRCA values (in the range from 350 ± 126 years to 571 ± 128 years). This suggests that carbon incorporated into these stalagmites originates predominantly from decomposition of old, recalcitrant organic matter. SOM turnover rates cannot be ascribed to a single climate variable, e.g. (MAAT) but instead reflect a complex interplay of climate (e.g. MAAT and moisture budget) and vegetation development.

Plant diversity drives soil microbial biomass carbon in grasslands irrespective of global environmental change factors

Soil microbial biomass is a key determinant of carbon dynamics in the soil. Several studies have shown that soil microbial biomass significantly increases with plant species diversity, but it remains unclear whether plant species diversity can also stabilize soil microbial biomass in a changing environment. This question is particularly relevant as many global environmental change (GEC) factors, such as drought and nutrient enrichment, have been shown to reduce soil microbial biomass. Experiments with orthogonal manipulations of plant diversity and GEC factors can provide insights whether plant diversity can attenuate such detrimental effects on soil microbial biomass. Here, we present the analysis of 12 different studies with 14 unique orthogonal plant diversity × GEC manipulations in grasslands, where plant diversity and at least one GEC factor (elevated CO2, nutrient enrichment, drought, earthworm presence, or warming) were manipulated. Our results show that higher plant diversity significantly enhances soil microbial biomass with the strongest effects in long-term field experiments. In contrast, GEC factors had inconsistent effects with only drought having a significant negative effect. Importantly, we report consistent non-significant effects for all 14 interactions between plant diversity and GEC factors, which indicates a limited potential of plant diversity to attenuate the effects of GEC factors on soil microbial biomass. We highlight that plant diversity is a major determinant of soil microbial biomass in experimental grasslands that can influence soil carbon dynamics irrespective of GEC.

Spatial assessment of carbon stocks of living vegetation at the national level in Lao PDR

The international mechanism for Reducing Greenhouse Gas Emissions from Deforestation and Forest Degradation (REDD) supposedly offers new opportunities for combining climate mitigation, conservation of the environment, and socio-economic development for development countries. In Laos REDD is abundantly promoted by the government and development agencies as a potential option for rural development. Yet, basic information for carbon management is missing: to date no knowledge is available at the national level on the quantities of carbon stored in the Lao landscapes. In this study we present an approach for spatial assessment of vegetation-based carbon stocks. We used Google Earth, Landsat and MODIS satellite imagery and refined the official national land cover data to assess carbon stocks. Our study showed that more than half (52%) of carbon stock of Laos is stored in natural forests, but that 70% of this stock is located outside of national protected areas. On the basis of two carbon-centered land use scenarios we calculated that between 30 and 40 million tons of carbon could be accumulated in shifting cultivation areas; this is less than 3% of the existing total stock. Our study suggests that the main focus of REDD in Laos should be on the conservation of existing carbon stocks, giving highest priority to the prevention of deforestation outside of national protected areas.

Carbon pools and poverty peaks in Lao PDR

Reducing Emissions from Deforestation and forest Degradation and enhancing forest carbon stocks in developing countries (REDD+) is heavily promoted in Laos. REDD+ is often perceived as an opportunity to jointly address climate change and poverty and, therefore, could come timely for Laos to combine its prominent national target of poverty eradication with global climate mitigation efforts. Countrywide planning of the right approaches to REDD+ combined with poverty alleviation requires knowledge of the spatial combination of poverty and carbon stocks at the national level. This study combined spatial information on carbon stored in vegetation and on poverty and created carbon-poverty typologies for the whole country at the village level. We found that 11% of the villages of Laos have high to very high average village-level carbon stock densities and a predominantly poor population. These villages cover 20% of the territory and are characterized by low population density. Shifting cultivation areas in the northwestern parts of the country have a higher carbon mitigation potential than areas in the central and eastern highlands due to a more favorable climate. Finally, we found that in Laos the majority (58%) of poor people live in areas with low carbon stock densities without major potential to store carbon. Accordingly, REDD+ cannot be considered a core instrument for poverty alleviation. The carbon-poverty typologies presented here provide answers to basic questions related to planning and managing of REDD+. They could serve as a starting point for the design of systems to monitor both socioeconomic and environmental development at the national level.

Transient simulations of the carbon and nitrogen dynamics in northern peatlands: from the Last Glacial Maximum to the 21st century

The development of northern high-latitude peatlands played an important role in the carbon (C) balance of the land biosphere since the Last Glacial Maximum (LGM). At present, carbon storage in northern peatlands is substantial and estimated to be 500 ± 100 Pg C (1 Pg C = 1015 g C). Here, we develop and apply a peatland module embedded in a dynamic global vegetation and land surface process model (LPX-Bern 1.0). The peatland module features a dynamic nitrogen cycle, a dynamic C transfer between peatland acrotelm (upper oxic layer) and catotelm (deep anoxic layer), hydrology- and temperature-dependent respiration rates, and peatland specific plant functional types. Nitrogen limitation down-regulates average modern net primary productivity over peatlands by about half. Decadal acrotelm-to-catotelm C fluxes vary between −20 and +50 g C m−2 yr−1 over the Holocene. Key model parameters are calibrated with reconstructed peat accumulation rates from peat-core data. The model reproduces the major features of the peat core data and of the observation-based modern circumpolar soil carbon distribution. Results from a set of simulations for possible evolutions of northern peat development and areal extent show that soil C stocks in modern peatlands increased by 365–550 Pg C since the LGM, of which 175–272 Pg C accumulated between 11 and 5 kyr BP. Furthermore, our simulations suggest a persistent C sequestration rate of 35–50 Pg C per 1000 yr in present-day peatlands under current climate conditions, and that this C sink could either sustain or turn towards a source by 2100 AD depending on climate trajectories as projected for different representative greenhouse gas concentration pathways.

DYPTOP: a cost-efficient TOPMODEL implementation to simulate sub-grid spatio-temporal dynamics of global wetlands and peatlands

Simulating the spatio-temporal dynamics of inundation is key to understanding the role of wetlands under past and future climate change. Earlier modelling studies have mostly relied on fixed prescribed peatland maps and inundation time series of limited temporal coverage. Here, we describe and assess the the Dynamical Peatland Model Based on TOPMODEL (DYPTOP), which predicts the extent of inundation based on a computationally efficient TOPMODEL implementation. This approach rests on an empirical, grid-cell-specific relationship between the mean soil water balance and the flooded area. DYPTOP combines the simulated inundation extent and its temporal persistency with criteria for the ecosystem water balance and the modelled peatland-specific soil carbon balance to predict the global distribution of peatlands. We apply DYPTOP in combination with the LPX-Bern DGVM and benchmark the global-scale distribution, extent, and seasonality of inundation against satellite data. DYPTOP successfully predicts the spatial distribution and extent of wetlands and major boreal and tropical peatland complexes and reveals the governing limitations to peatland occurrence across the globe. Peatlands covering large boreal lowlands are reproduced only when accounting for a positive feedback induced by the enhanced mean soil water holding capacity in peatland-dominated regions. DYPTOP is designed to minimize input data requirements, optimizes computational efficiency and allows for a modular adoption in Earth system models.

Effects of elevation and land use on the biomass of trees, shrubs and herbs at Mount Kilimanjaro

The protection and sustainable management of forest carbon stocks, particularly in the tropics, is a key factor in the mitigation of global change effects. However, our knowledge of how land use and elevation affect carbon stocks in tropical ecosystems is very limited. We compared aboveground biomass of trees, shrubs and herbs for eleven natural and human-influenced habitat types occurring over a wide elevation gradient (866–4550 m) at the world's highest solitary mountain, Mount Kilimanjaro. Thanks to the enormous elevation gradient, we covered important natural habitat types, e.g., savanna woodlands, montane rainforest and afro-alpine vegetation, as well as important land-use types such as maize fields, grasslands, traditional home gardens, coffee plantations and selectively logged forest. To assess tree and shrub biomass with pantropical allometric equations, we measured tree height, diameter at breast height and wood density and to assess herbaceous biomass, we sampled destructively. Among natural habitats, tree biomass was highest at intermediate elevation in the montane zone (340 Mg ha−1), shrub biomass declined linearly from 7 Mg ha−1 at 900 m to zero above 4000 m, and, inverse to tree biomass, herbaceous biomass was lower at mid-elevations (1 Mg ha−1) than in savannas (900 m, 3 Mg ha−1) or alpine vegetation (above 4000 m, 6 Mg ha−1). While the various land-use types dramatically decreased woody biomass at all elevations, though to various degrees, herbaceous biomass was typically increased. Our study highlights tropical montane forest biomass as important aboveground carbon stock and quantifies the extent of the strong aboveground biomass reductions by the major land-use types, common to East Africa. Further, it shows that elevation and land use differently affect different vegetation strata, and thus the matrix for other organisms.

Biogeochemical indicators of peatland degradation – a case study of a temperate bog in Northern Germany

Organic soils in peatlands store a great proportion of the global soil carbon pool and can lose carbon via the atmosphere due to degradation. In Germany, most of the greenhouse gas (GHG) emissions from organic soils are attributed to sites managed as grassland. Here, we investigated a land use gradient from near-natural wetland (NW) to an extensively managed (GE) to an intensively managed grassland site (GI), all formed in the same bog complex in northern Germany. Vertical depth profiles of δ13C, δ15N, ash content, C / N ratio and bulk density as well as radiocarbon ages were studied to identify peat degradation and to calculate carbon loss. At all sites, including the near-natural site, δ13C depth profiles indicate aerobic decomposition in the upper horizons. Depth profiles of δ15N differed significantly between sites with increasing δ15N values in the top soil layers paralleling an increase in land use intensity owing to differences in peat decomposition and fertilizer application. At both grassland sites, the ash content peaked within the first centimetres. In the near-natural site, ash contents were highest in 10–60 cm depth. The ash profiles, not only at the managed grassland sites, but also at the near-natural site indicate that all sites were influenced by anthropogenic activities either currently or in the past, most likely due to drainage. Based on the enrichment of ash content and changes in bulk density, we calculated the total carbon loss from the sites since the peatland was influenced by anthropogenic activities. Carbon loss at the sites increased in the following order: NW < GE < GI. Radiocarbon ages of peat in the topsoil of GE and GI were hundreds of years, indicating the loss of younger peat material. In contrast, peat in the first centimetres of the NW was only a few decades old, indicating recent peat growth. It is likely that the NW site accumulates carbon today but was perturbed by anthropogenic activities in the past. Together, all biogeochemical parameters indicate a degradation of peat due to (i) conversion to grassland with historical drainage and (ii) land use intensification.

Environmental correlates of species rank − abundance distributions in global drylands

Theoretical models predict lognormal species abundance distributions (SADs) in stable and productive environments, with log-series SADs in less stable, dispersal driven communities. We studied patterns of relative species abundances of perennial vascular plants in global dryland communities to: (i) assess the influence of climatic and soil characteristics on the observed SADs, (ii) infer how environmental variability influences relative abundances, and (iii) evaluate how colonisation dynamics and environmental filters shape abundance distributions. We fitted lognormal and log-series SADs to 91 sites containing at least 15 species of perennial vascular plants. The dependence of species relative abundances on soil and climate variables was assessed using general linear models. Irrespective of habitat type and latitude, the majority of the SADs (70.3%) were best described by a lognormal distribution. Lognormal SADs were associated with low annual precipitation, higher aridity, high soil carbon content, and higher variability of climate variables and soil nitrate. Our results do not corroborate models predicting the prevalence of log-series SADs in dryland communities. As lognormal SADs were particularly associated with sites with drier conditions and a higher environmental variability, we reject models linking lognormality to environmental stability and high productivity conditions. Instead our results point to the prevalence of lognormal SADs in heterogeneous environments, allowing for more evenly distributed plant communities, or in stressful ecosystems, which are generally shaped by strong habitat filters and limited colonisation. This suggests that drylands may be resilient to environmental changes because the many species with intermediate relative abundances could take over ecosystem functioning if the environment becomes suboptimal for dominant species.

Prediction of soil organic carbon for Ethiopian highlands using soil spectroscopy

Soil spectroscopy was applied for predicting soil organic carbon (SOC) in the highlands of Ethiopia. Soil samples were acquired from Ethiopia’s National Soil Testing Centre and direct field sampling. The reflectance of samples was measured using a FieldSpec 3 diffuse reflectance spectrometer. Outliers and sample relation were evaluated using principal component analysis (PCA) and models were developed through partial least square regression (PLSR). For nine watersheds sampled, 20% of the samples were set aside to test prediction and 80% were used to develop calibration models. Depending on the number of samples per watershed, cross validation or independent validation were used.The stability of models was evaluated using coefficient of determination (R2), root mean square error (RMSE), and the ratio performance deviation (RPD). The R2 (%), RMSE (%), and RPD, respectively, for validation were Anjeni (88, 0.44, 3.05), Bale (86, 0.52, 2.7), Basketo (89, 0.57, 3.0), Benishangul (91, 0.30, 3.4), Kersa (82, 0.44, 2.4), Kola tembien (75, 0.44, 1.9),Maybar (84. 0.57, 2.5),Megech (85, 0.15, 2.6), andWondoGenet (86, 0.52, 2.7) indicating that themodels were stable. Models performed better for areas with high SOC values than areas with lower SOC values. Overall, soil spectroscopy performance ranged from very good to good.