Global Drivers of Land Degradation and Improvement

Abstract

Identification of factors catalyzing sustainable land management (SLM) could provide insights for national policies and international efforts to address land degradation. Building on previous studies, and using novel datasets, this chapter identifies major drivers of land degradation at global and regional levels. The findings of this study confirm the earlier insights in the literature on the context-specific nature of the drivers of land degradation. This context-dependence explains the previous contradictions in the literature on the effects of various socio-economic and institutional factors on land degradation. It also calls for the localized diagnostic of the drivers of land degradation. The drivers of land degradation are predominantly local, so actions to address them should be based on the understanding of the local interplay of various factors and how they affect land degradation.

Economics of sustainable land management

“…global pixel level, or at the level of administrative divisions, or at household level), the methodologies applied and the nature of the dependent variable standing for land degradation or sustainable land management. To illustrate, [42,44] conduct global level analyses of the drivers of land degradation using broadly the same set of explanatory variables, considering the same time period between 1982 and 2006, and in both cases their dependent variables are obtained from the Normalized Difference Vegetation Index (NDVI) from the Global Inventory Modeling and Mapping Studies (GIMMS) [46]. However, [42] use the values of the NDVI directly as given in the NDVI database, while [44] use these values after processing by [10 ], who remove from the NDVI values potential biases emanating from rainfall dynamics, atmospheric and chemical fertilization 3 .…”

“…At the same time, clustering countries of the world by similar institutional, economic and technical characteristics [44], find that the effects of the drivers of land degradation may follow some generalizable patterns within the clusters. For example, SLM is positively associated with land tenure security, especially in middle-income and advanced economies, and less so in lower income countries, where lack of secure land tenure is not associated with unsustainable land management [44]. Secure land tenure may provide with additional benefits and opportunities with relatively well-functioning markets, including output, input and financial markets.…”

“…Secure land tenure may provide with additional benefits and opportunities with relatively well-functioning markets, including output, input and financial markets. Where they do not function well or are very thin, secure land tenure may have much less effect on SLM [44]. Population pressure may not lead to land degradation if public policies provide for increases in non-farm jobs [45].…”

“…Higher population may induce agricultural innovations and lead to wider use of labor-intensive sustainable land management practices. Better rule of law may lead to sustainable land management in lower income countries, whereas the effects of further improved rule of law in more advanced economies seem non-significant, potentially due to nonlinearities at higher levels [44].…”

“…For instance, some well-known points of debate on the drivers of land degradation include whether higher population causes land degradation [33][34][35], or leads to SLM [36]; whether poverty is the driver of land degradation [37][38][39], or not [40]; would higher market access lead to SLM [41,42], or to land degradation [43]. Mirzabaev et al [44], using newly available datasets at global level on land degradation hotspots [10 ], and various socioeconomic and institutional indicators, find that the causal patterns of individual drivers of land degradation vary across geographic locations. Similar conclusions are also reached by [3 ,4].…”