Biophysical Effects of Vegetation Transformations

The impact of land degradation on local climate

The type of vegetation covering the landscape has a direct influence on local climate through its control of water and energy fluxes. The albedo (brightness) of the vegetation cover will determine how much energy is reflected back into space as shortwave radiation. Its roughness determines how much mixing of air occurs between the atmosphere and the vegetation canopy.
The depth and structure of its rooting system can determine how much soil moisture and groundwater might be tapped and thus how much heat can be dissipated through evapotranspiration or latent heat flux. The balance of all these surface properties determines the direct influence of vegetation on the surface energy budget and ultimately on the local temperature.

When vegetation cover is altered following processes of land degradation or land-use change, resulting changes in surface properties can lead to a local warming or cooling, depending on which biophysical forces dominate. Both the sign and magnitude of this change depends on the specific vegetation transition, its timing and location, as well as the background climate. Local changes in temperature are potentially more perceptible by people because its consequences are felt more immediately than those that result from global greenhouse gas emissions. However, these effects have been largely ignored in shaping global policy and climate treaties due in part to the difficulty in capturing the biophysical changes that drive them.

Several data-driven diagnostics have been developed based on satellite observations. However, only recently has it been possible to generate a comprehensive assessment of the effect of multiple vegetation transitions on the full surface energy balance at a global scale. Based on a combination of data products derived from MODIS and CERES instruments with recent land-cover maps, a dataset has been created which allows exploration of the consequences of vegetation cover change on energy fluxes and on the resulting land-surface temperature, as measured from space.

Local biophysical effects of land degradation shows the potential consequences of conversion of forest to grasses or crops on surface energy fluxes. Shortwave reflected radiation increases generally everywhere (a), but more in drier areas. Longwave emitted radiation increases in dry areas and decreases in northern latitudes (b). Latent heat flux is strongly reduced (c), particularly in the tropics and the residual flux composed of sensible and ground heat fluxes (d) shows a general decrease, with a major exception around south-eastern Brazil.
Source: Duveiller, G. et al., 2018.

Mean temperatures increases. The effect of a potential conversion of forests to grasses or crops on a) daytime land surface temperature (LST), which is close to the daily maximum; b) nighttime LST, which is close to the daily minimum and c) the daily amplitude in LST.
Source: Duveiller, G. et al., 2018

Deforestation generally leads to local warming, except in borealareas. The map shows average annual change in mean land surface temperature (LST) following potential conversion of forest to grasses or crops. Mean LST is the average of daytime and nighttime LST estimated from the MODIS instrument on-board of the AQUA platform.
Source: Duveiller, G. et al., 2018

Cumulative changes in energy for each component of the surface energy balance resulting from recent major vegetation transitions
Transitions are sorted according to decreasing absolute change in the surface energy balance. The changed area per transition, calculated based on the ESA CCI land cover maps of 2015 and 2000, are reported in megahectares on the right. Transitions involve the following vegetation classes: evergreen broadleaf forests (EBF), deciduous broadleaf forests (DBF), savannas (SAV), shrublands (SHR) and croplands (CRO

Source: Duveiller, G. et al., 2018

Average surface energy balance over vegetated areas Values on the arrows indicate the mean annual values over vegetated areas between 2008-2012, along with the mean of the monthly standard deviation. The source of the radiative fluxes is CERES EBAL surface dataset Ed2.8, latent heat comes from the MOD16A2 dataset and the combined sensible and ground heat fluxes are the balance of the other fluxes.

Source: Duveiller, G. et al., 2017

Global summary of mean annual potential change in surface energy balance and temperature for transitions in vegetation type derived from satellite observations. Transitions involve the following vegetation classes: evergreen broadleaf forests (EBF), deciduous broadleaf forests (DBF), evergreen needleleaf forests (ENF), savannas (SAV), shrublands (SHR), grasslands (GRA), croplands (CRO) and wetlands (WET). Because transitions are symmetric, reverse transitions can be derived by inverting the sign. A striking pattern emerges between the column representing tropical evergreen broadleaf forests (EBF) and the rows representing agricultural expansion (CRO and GRA). They consistently show warming, irrespective of which transition is considered. (changes are FROM - top of graph - TO right of graph)
Source: Duveiller, G. et al., 2018