Adaptation of global land use and management intensity to changes in climate and atmospheric carbon dioxide

Abstract

Land use contributes to environmental change, but is also influenced by such changes. Climate and atmospheric carbon dioxide (CO 2) levels’ changes alter agricultural crop productivity, plant water requirements and irrigation water availability. The global food system needs to respond and adapt to these changes, for example, by altering agricultural practices, including the crop types or intensity of management, or shifting cultivated areas within and between countries. As impacts and associated adaptation responses are spatially specific, understanding the land use adaptation to environmental changes requires crop productivity representations that capture spatial variations. The impact of variation in management practices, including fertiliser and irrigation rates, also needs to be considered. To date, models of global land use have selected agricultural expansion or intensification levels using relatively aggregate spatial representations, typically at a regional level, that are not able to characterise the details of these spatially differentiated responses. Here, we show results from a novel global modelling approach using more detailed biophysically derived yield responses to inputs with greater spatial specificity than previously possible. The approach couples a dynamic global vegetative model (LPJ‐GUESS) with a new land use and food system model (PLUMv2), with results benchmarked against historical land use change from 1970. Land use outcomes to 2100 were explored, suggesting that increased intensity of climate forcing reduces the inputs required for food production, due to the fertilisation and enhanced water use efficiency effects of elevated atmospheric CO 2 concentrations, but requiring substantial shifts in the global and local patterns of production. The results suggest that adaptation in the global agriculture and food system has substantial capacity to diminish the negative impacts and gain greater benefits from positive outcomes of climate change. Consequently, agricultural expansion and intensification may be lower than found in previous studies where spatial details and processes consideration were more constrained.

Integrated Solutions for the Water-Energy-Land Nexus: Are Global Models Rising to the Challenge?

“…GGCs assess crop productivity as well as agricultural water and fertilizer requirements based on a combination of the biophysical properties (e.g., soil, climate) and human-driven management decisions (e.g., water interventions, fertilization, crop choice). However, these models do not typically have an explicit economic component and thus cannot optimize management responses to changes in climate and food demands [33,34]. Rather, they estimate static productivity impacts under pre-specified management regimes or, alternatively, the resource requirements required to alleviate gridded resource constraints (e.g., the fertilizer and irrigation required to avoid nitrogen and water stress, respectively).…”

Impacts of future agricultural change on ecosystem service indicators

“…future are discussed in Alexander et al (2018). Here, after extending the historical run to 2010, we feed PLUM's projections of 2011-2100 land use, nitrogen fertilizer application, and irrigation intensity back into LPJ-GUESS to simulate their impacts over that period.…”

“…In addition to the input data provided by the SSPs, and following the approach described in Alexander et al (2018), PLUM parameters-such as input and transport costs, tariffs, and minimum non-agricultural area-were also affected by the SSP narratives. Values were estimated for each SSP based on an interpretation of the storylines (O'Neill et al, 2015;Engström et al, 2016a) and can be found in Table SM6.…”

“…Previously, we used the PLUM land-use model to estimate future land use and management change, based on changing so-35 cioeconomic conditions as well as climate effects on agricultural yield provided by the vegetation model LPJ-GUESS (Alexander et al, 2018). This coupled model system-the Land System Modular Model, or LandSyMM-is unique among global land-use change models in the high level of spatial detail that it considers in the response of agricultural yields to management inputs, as well as in allowing short-term over-and under-supply of commodities relative to demand (rather than assuming market equilibrium in every year).…”

“…(2018), by around 500% for cropland and 700% for pasture. The primary reason for this increase in inter-scenario variation is that Alexander et al (2018) used the SSP2 socioeconomic scenario for all RCPs, whereas here we compare different SSPs paired with appropriate RCPs. Even with this increased spread, however, the LandSyMM trajectories are more closely clustered than those from some other land use models.…”