CIFOR-ICRAF aborda desafios e oportunidades locais ao mesmo tempo em que oferece soluções para problemas globais para florestas, paisagens, pessoas e o planeta.

Fornecemos evidências e soluções acionáveis ​​para transformer a forma como a terra é usada e como os alimentos são produzidos: conservando e restaurando ecossistemas, respondendo ao clima global, desnutrição, biodiversidade e crises de desertificação. Em suma, melhorar a vida das pessoas.

O CIFOR-ICRAF publica mais de 750 publicações todos os anos sobre agrossilvicultura, florestas e mudanças climáticas, restauração de paisagens, direitos, política florestal e muito mais – em vários idiomas..

CIFOR-ICRAF aborda desafios e oportunidades locais ao mesmo tempo em que oferece soluções para problemas globais para florestas, paisagens, pessoas e o planeta.

Fornecemos evidências e soluções acionáveis ​​para transformer a forma como a terra é usada e como os alimentos são produzidos: conservando e restaurando ecossistemas, respondendo ao clima global, desnutrição, biodiversidade e crises de desertificação. Em suma, melhorar a vida das pessoas.

CIFOR–ICRAF publishes over 750 publications every year on agroforestry, forests and climate change, landscape restoration, rights, forest policy and much more – in multiple languages.

CIFOR–ICRAF addresses local challenges and opportunities while providing solutions to global problems for forests, landscapes, people and the planet.

We deliver actionable evidence and solutions to transform how land is used and how food is produced: conserving and restoring ecosystems, responding to the global climate, malnutrition, biodiversity and desertification crises. In short, improving people’s lives.

Better estimates of soil carbon from geographical data: a revised global approach

Exportar a citação

Soils hold the largest pool of organic carbon (C) on Earth; yet, soil organic carbon (SOC) reservoirs are not well represented in climate change mitigation strategies because our database for ecosystems where human impacts are minimal is still fragmentary. Here, we provide a tool for generating a global baseline of SOC stocks. We used partial least square (PLS) regression and available geographic datasets that describe SOC, climate, organisms, relief, parent material and time. The accuracy of the model was determined by the root mean square deviation (RMSD) of predicted SOC against 100 independent measurements. The best predictors were related to primary productivity, climate, topography, biome classification, and soil type. The largest C stocks for the top 1 m were found in boreal forests (254 ± 14.3 t ha-1) and tundra (310 ± 15.3 t ha-1). Deserts had the lowest C stocks (53.2 ± 6.3 t ha-1) and statistically similar C stocks were found for temperate and Mediterranean forests (142 - 221 t ha-1), tropical and subtropical forests (94 - 143 t ha-1) and grasslands (99-104 t ha-1). Solar radiation, evapotranspiration, and annual mean temperature were negatively correlated with SOC, whereas soil water content was positively correlated with SOC. Our model explained 49% of SOC variability, with RMSD (0.68) representing approximately 14% of observed C stock variance, overestimating extremely low and underestimating extremely high stocks, respectively. Our baseline PLS predictions of SOC stocks can be used for estimating the maximum amount of C that may be sequestered in soils across biomes.

DOI:
https://doi.org/10.1007/s11027-018-9815-y
Pontuação Altmetric:
Dimensões Contagem de citações:

Publicações relacionadas