scholarly journals Effects of land cover on ecosystem services in Tanzania: A spatial assessment of soil organic carbon

Geoderma ◽  
2016 ◽  
Vol 263 ◽  
pp. 274-283 ◽  
Author(s):  
Leigh Winowiecki ◽  
Tor-Gunnar Vågen ◽  
Jeroen Huising
Keyword(s):  
Ecosystem Services ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Land Cover ◽  
Spatial Assessment

Modelling long-term soil organic carbon dynamics under the impact of land cover change and soil redistribution

CATENA ◽  
2017 ◽  
Vol 151 ◽  
pp. 63-73 ◽  
Author(s):  
Samuel Bouchoms ◽  
Zhengang Wang ◽  
Veerle Vanacker ◽  
Sebastian Doetterl ◽  
Kristof Van Oost
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Land Cover ◽  
Land Cover Change ◽  
Carbon Dynamics ◽  
Soil Redistribution ◽  
The Impact ◽  
Soil Organic Carbon Dynamics

scholarly journals DYNAMIC OF LAND DEGRADATION NEUTRALITY BASELINE INDCATORS IN THE REPUBLIC OF MACEDONIA

2019 ◽  
Vol 40 (1) ◽  
pp. 39
Author(s):  
Dusko Mukaetov Mukaetov ◽  
Ivan Blinkov ◽  
Hristina Poposka
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Land Cover ◽  
Land Degradation ◽  
Natural Capital ◽  
Data Sets ◽  
Land Productivity ◽  
Status And Trends ◽  
Global Data Sets ◽  
Global Data

Land degradation neutrality (LDN) is defined as a "state whereby the amount and quality of land resources nec-essary to support ecosystem functions and services and enhance food security remain stable or increase within specified temporal and spatial scales and ecosystems". The baseline is expressed as the initial (t0) estimated value of each of the three indicators, used as proxies of land-based natural capital and the ecosystem services that flow from that land base: land cover/land use change, land productivity status and trends, soil organic carbon status and trends. The baseline of LDN was calculated with estimation of the average values across the 10 years baseline period of the following indica-tors: Land Cover/Land Cover change (LC/LCC), Land Productivity Dynamics (LPD) and Soil Organic Carbon (SOC). Three tier approaches for computation of the selected indicators were used: Tier 1: Global/regional Earth observation, geospatial information and modelling; Tier 2: National statistics (only for LC/LCC) and Tier 3: Field survey. Most sig-nificant changes in LC for the period 2000/2012 are in the categories of Forest land and Shrubs/grasslands. According the global data sets used for analysis of LPD, the total affected area with depletion of Land productivity for the period 2000/2010 is identified on a only 2.35 % of the country territory. The available global data sets gives a model SOC lev-els for the period 2000/2010. According these data, the total loss of SOC in our country is estimated on 3951 t.

scholarly journals Climate and Land-Use Change Effects on Soil Carbon Stocks over 150 Years in Wisconsin, USA

2019 ◽  
Vol 11 (12) ◽  
pp. 1504 ◽  
Author(s):  
Jingyi Huang ◽  
Alfred E. Hartemink ◽  
Yakun Zhang
Keyword(s):  
Environmental Factors ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Land Cover ◽  
Soil Carbon ◽  
Land Cover Change ◽  
Soil Management ◽  
Carbon Stocks ◽  
The State ◽  
Time Substitution

Soil organic carbon is a sink for mitigating increased atmospheric carbon. The international initiative “4 per 1000” aims at implementing practical actions on increasing soil carbon storage in soils under agriculture. This requires a fundamental understanding of the soil carbon changes across the globe. Several studies have suggested that the global soil organic carbon stocks (SOCS) have decreased due to global warming and land cover change, while others reported SOCS may increase under climate change and improved soil management. To better understand how a changing climate, land cover, and agricultural activities influence SOCS across large extents and long periods, the spatial and temporal variations of SOCS were estimated using a modified space-for-time substitution method over a 150-year period in the state of Wisconsin, USA. We used legacy soil datasets and environmental factors collected and estimated at different times across the state (169,639 km2) coupled with a machine-learning algorithm. The legacy soil datasets were collected from 1980 to 2002 from 550 soil profiles and harmonized to 0.30 m depth. The environmental factors consisted of 100-m soil property maps, 1-km annual temperature and precipitation maps, 250-m remote-sensing (i.e., Landsat)-derived yearly land cover maps and a 30-m digital elevation model. The model performance was moderate but can provide insights on understanding the impacts of different factors on SOCS changes across a large spatial and temporal extent. SOCS at the 0–0.30 m decreased at a rate of 0.1 ton ha−1 year−1 between 1850 and 1938 and increased at 0.2 ton ha−1 year−1 between 1980 and 2002. The spatial variation in SOCS at 0–0.30 m was mainly affected by land cover and soil types with the largest SOCS found in forest and wetland and Spodosols. The loss between 1850 and 1980 was most likely due to land cover change while the increase between 1980 and 2002 was due to best soil management practices (e.g., decreased erosion, reduced tillage, crop rotation and use of legume and cover crops).

Landscape-scale variability in soil organic carbon storage in the central Canadian Arctic

2014 ◽  
Vol 94 (4) ◽  
pp. 477-488 ◽  
Author(s):  
A. Brett Campeau ◽  
Peter M. Lafleur ◽  
Elyn R. Humphreys
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Land Cover ◽  
Carbon Storage ◽  
Canadian Arctic ◽  
Landscape Scale ◽  
Soil Organic Carbon Storage ◽  
Landscape Unit ◽  
Organic Carbon Storage ◽  
Up Scaling

Campeau, A. B., Lafleur, P. M. and Humphreys, E. R. 2014. Landscape-scale variability in soil organic carbon storage in the central Canadian Arctic. Can. J. Soil Sci. 94: 477–488. Arctic soils constitute a vast, but poorly quantified, pool of soil organic carbon (SOC). The uncertainty associated with pan-Arctic SOC storage estimates – a result of limited SOC and land cover data – needs to be reduced if we are to better predict the impact of future changes to Arctic carbon stocks resulting from climate warming. In this study landscape-scale variability in SOC at a Southern Arctic Ecozone site in the central Canadian Arctic was investigated with the ultimate goal of up-scaling SOC estimates with a land cover classification system. Total SOC was estimated to depths of 30 cm and 50 cm for 76 soil pits, together representing eight different vegetation communities in seven different broad landscape units. Soil organic carbon to 50 cm was lowest for the xerophytic herb community in the esker complex landscape unit (7.2±2.2 SD kg m−2) and highest in the birch hummock terrain in the lowland tundra landscape unit (36.4±2.8 kg m−2), followed by wet sedge and dry sedge communities in the wetland complex (29.8±9.9 and 22.0±2.0 kg m−2, respectively). The up-scaled estimates of mean SOC for the study area (excluding water) were 15.8 kg m−2 (to 50 cm) and 11.6 kg m−2 (to 30 cm). On a landscape scale, soil moisture content was found to have an important influence on SOC variability. Overall, this study highlights the importance of SOC variability at fine scales and its impact on up-scaling SOC in Arctic landscapes.

Using a data-driven network to understand the drivers of soil organic carbon dynamics across the tropic

2020 ◽  
Author(s):  
Leigh Winowiecki ◽  
Tor-Gunnar Vågen
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Land Cover ◽  
Soil Properties ◽  
Carbon Content ◽  
Land Management ◽  
Land Degradation ◽  
Soil Health ◽  
Carbon Dynamics ◽  
Soil Organic Carbon Dynamics

<p>Maintaining soil organic carbon (SOC) content is recognized as an important strategy for a well-functioning soil ecosystem. The UN Convention to Combat Desertification (UNCCD) recognizes that reduced SOC content can lead to land degradation, and ultimately low land and agricultural productivity. SOC is almost universally proposed as the most important indicator of soil health, not only because SOC positively influences multiple soil properties that affect productivity, including cation exchange capacity and water holding capacity, but also because SOC content reflects aboveground activities, including especially agricultural land management. To be useful as an indicator, it is crucial to assess the importance of both inherent soil properties as well as external factors (climate, vegetation cover, land management, etc.) on SOC dynamics across space and time. This requires large, reliable and up-to-date soil health data sets across diverse land cover classes. The Land Degradation Surveillance Framework (LDSF), a well-established method for assessing multiple biophysical indicators at georeferenced locations, was employed in nine countries across the tropics (Burkina Faso, Cameron, Honduras, India, Indonesia, Kenya, Nicaragua, Peru, and South Africa) to assess the influence of land use, tree cover and inherent soil properties on soil organic carbon dynamics. The LDSF was designed to provide a biophysical baseline at landscape level, and monitoring and evaluation framework for assessing processes of land degradation and the effectiveness of rehabilitation measures over time. Each LDSF site has 160 – 1000 m<sup>2</sup> plots that were randomly stratified among 16 - 1 km<sup>2</sup> sampling clusters. A total of 6918 soil samples were collected (3478 topsoil (0-20 cm) and 3435 subsoil (20-50 cm)) within this study. All samples were analyzed using mid-infrared spectroscopy and 10% of the samples were analyzed using traditional wet chemistry to develop calibration prediction models.  Validation results for soil properties (soil organic carbon (SOC), sand, and total nitrogen) showed good accuracy with R<sup>2</sup> values ranging between 0.88 and 0.96. Mean organic carbon content was 21.9 g kg<sup>-1</sup> in topsoil and 15.2 g kg<sup>-1</sup> in subsoil (median was 18.3 g kg<sup>-1</sup>  for topsoil and 10.8 g kg<sup>-1</sup> in subsoil). Forest and grassland had the highest and similar carbon content while bushland/shrubland had the lowest. Sand content played an important role in determining the SOC content across the land cover types. Further analysis will be conducted and shared on the role of trees, land cover and texture on the dynamics of soil organic carbon and the implications for LDN reporting, land restoration initiatives as well as sustainable land management recommendations.</p>

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