Land Productivity Dynamics

Global land productivity dynamics
Global land productivity dynamics showing 5 classes of persistent land productivity trajectories from 1999-2013. The map is compiled from phenological metrics, such as growing season productivity, derived from time series of the Copernicus Global Land SPOT VGT products of normalized difference vegetation index (NDVI), composited in 10-day intervals at a spatial resolution of 1 km. Phenological metrics can be derived from other Earth-observation modelled vegetation indices such as fAPAR. The period here is constrained by the operational life of the SPOT satellite. The map shows 5 classes indicating areas of negative or positive change or stability, and is an indicator of change or stasis of the land’s capacity to sustain the dynamic equilibrium of primary production from 1999 to 2013. Declining trends do not indicate land degradation per se, nor do increasing trends indicate recovery.
Source: WAD3-JRC, 2018, Cherlet, M., 2014.

Tracking some consequences of global land transformations

Humans need increasingly more biomass for food, fodder, fibre and energy. Meeting these demands changes global ecosystems. Tracking changes in total biomass production or land productivity is an essential part of monitoring land transformations that are typically associated with land degradation1. The state of the Earth’s vegetation cover and its development over time is one reliable and accepted measure associated with land productivity. The state of vegetation cover and is a good reflection of the integrated ecological conditions as well as the impact of natural and anthropogenic environmental change. Persistent land productivity changes point to long-term alteration of the health and productive capacity of the land.
Trends in land productivity have been adopted as one of three land-based UNCCD progress indicators. These are used for mandatory reporting and have been proposed as one sub-indicator for monitoring and assessing progress towards achieving Sustainable Development. Goal (SDG) target 15.3.
A persistent reduction in land productivity will directly and indirectly impact almost all terrestrial ecosystem services and benefits that form the basis for sustainable livelihoods of all human communities. But declining productivity is certainly not the sole indicator of possible land degradation. Increased productivity is sometimes achieved at the cost of other land resources, such as water or soil, in which case it can lead to degradation, which is observable only in later stages. To identify critical land degradation zones, land productivity must be analysed within the context of anthropogenic land use and other environmental changes. One approach to bringing many disparate measures together is the convergence of evidence framework. Land productivity as presented here refers to observed changes of above-ground biomass and is conceptually different from, and not necessarily related to, agricultural production or income per unit area.
Between 1999 and 2013, approximately 20.4 % of the Earth’s vegetated land surface showed persistent declining trends in land productivity. However, the level to which the different continents display persistent productivity decline (classes 1 and 2), instability or stress in the land’s productive capacity (class 3) varies significantly, as shown in the graph.
Africa, Australia and South America show, proportionally, declines or stressed productivity dynamics for larger areas that the rest of the globe. The vegetated continental land surface that shows a decline or unstable land productivity reaches approximately 22 % in Africa, 37 % in Australia and Oceania and 27 % in South America. This is much higher when compared to Asia with 14 %, Europe with 12 % and Northern America with 18 % of their vegetated area showing a declining or unstable land productivity. Further differentiation of the extent and significance of land productivity changes can made for within land cover/land use classes (see graph on the right page). It is alarming that 20 % of the world’s croplands show declining or stressed land productivity, particularly considering that immense effort and resources are being committed to maintain and enhance the productivity of arable and permanent cropland, as well as the fact that there are clear limitations to the further expansion of cropland.
Land productivity dynamics:
Land productivity dynamics (LPD) are used as an indicator of change or stability of the land’s capacity to sustain primary production. The primary productivity of a stable land system is not a steady state, but may be highly variable between different years and vegetation growth cycles due to natural variation and/ or human intervention. This recognises that land productivity changes cannot be assessed meaningfully by comparing land productivity values of single reference years or averages of a few years, and underscores the need for approaches based on longer-term trends. The map presented here depicts the persistent trajectories of land productivity dynamics over the period of 1999 to 2013, rather than a single summary measure of land productivity over that period. Analyses of trends and changes in land productivity may detect areas with persistent and active declines in primary productivity. These trends might point to ongoing land degradation rather than areas which have already reached a new equilibrium prior to the observation period.
Global monitoring of land productivity
Global monitoring of land productivity relies on multitemporal and thematic evaluation of long-term time series of remotely sensed vegetation indices, computed from continuous spectral measurements of the vegetation photosynthetic activity. Research has shown that time series of remotely sensed vegetation indices are correlated with biophysically meaningful vegetation characteristics such as photosynthetic capacity and primary production. These characteristics are closely related to global land surface changes that can be associated with processes of land degradation and recovery (see Figures on the left page). There is broad agreement that they are adapted to studying vegetation dynamics at global, continental and subcontinental levels.
Global data sets describing vegetation response are now operationally provided by national and international Earth observation systems, such as the EU Copernicus Earth observation programme and the NASA Land Data Products and Services programme, harmonised through intergovernmental frameworks such as the Group on Earth Observation implementing the Global Earth Observation Systems of Systems (GEOSS). A number of recent products analyse global biomass trajectories by using trends and change metrics of remote-sensing time series. Main divergences are related to the differences of the input time series (e.g. time period and spatial resolution) and in the way processing chains attempt to account for external environmental factors, such as rainfall, atmospheric fertilisation and land-use practices. To relate these trends to land degradation, these approaches try to incorporate other factors into the analysis, some rely on doing this in a second step, however, biomass trends alone reflect only one aspect of land degradation.

Global and continental area percentages affected by persistent declines or unstable land productivity between 1999 and 2013.
Source: WAD3-JRC, 2018.

Schematic trajectory of a curve (hysteresis) illustrating that, with increasing pressure, productivity declines to reach point B until the stress is reduced. When stress is reduced, productivity increases again. A fully resilient system (green curve) will go back to its original state (A) and will oscillate between stages A and B. If the system has decreased resilience (red curve) it will return to lower productivity at point C and possibly reach a new equilibrium at that lower productivity level. The resilience of the system, R, is related to the distance between A and C.
Source: Yengoh, G.T., (2015).

Proportional global land productivity by land cover/land use class. (Cropland includes arable land, permanent crops and mixed classes with over 50 % crops; Grassland includes natural grassland and managed pasture land; Rangelands include shrub land, herbaceous and sparsely vegetated areas; Forestland includes all forest categories and mixed classes with tree cover greater than 40 %).
Source: WAD3-JRC, 2018.

The relationship between NDVI and primary production is directly related to chlorophyll abundance and energy absorption. Comparison of integrated gross primary production from 21 Fluxnet forest flux towers and integrated NDVI (Normalised Difference Vegetation Index) from MODIS Terra, shows a reasonable correlation between NDVI and Gross Primary Production (GPP).
Source: Hashimoto, H. et al., 2012.