Size and stochasticity in irrigated social-ecological systems

Stochasticity-induced persistence in coupled social-ecological systems

Stochasticity is often associated with negative consequences for population dynamics since a population may die out due to random chance during periods when population size is very low (stochastic fade-out). Here we develop a coupled social-ecological model based on stochastic differential equations that includes natural expansion and harvesting of a forest ecosystem, and dynamics of conservation opinions, social norms and social learning in a human population. Our objective was to identify mechanisms that influence long-term persistence of the forest ecosystem in the presence of noise. We found that most of the model parameters had a significant influence on the time to extinction of the forest ecosystem. Increasing the social learning rate and the net benefits of conservation significantly increased the time to extinction, for instance. Most interestingly, we found a parameter regime where an increase in the amount of system stochasticity caused an increase in the mean time to extinction, instead of causing stochastic fade-out. This effect occurs for a subset of realizations, but the effect is large enough to increase the mean time to extinction across all realizations. Such "stochasticity-induced persistence" occurs when stochastic dynamics in the social system generates benefits in the forest system at crucial points in its temporal dynamics. We conclude that studying relatively simple social-ecological models has the benefit of facilitating characterization of dynamical states and thereby enabling us to formulate new hypothesis about mechanisms that could be operating in empirical social-ecological systems.

Optimal Allocation Model for Water Resources Coupled with Ecological Value Factors—A Case Study of Dalian, China

The surface water ecosystem has important ecological value and plays an important supporting and guarantee role in the sustainable development of human society. In this study, an inexact two-stage stochastic programming (ITSP) model was developed for supporting water resource allocation for the four main water sectors (industry, municipal, agriculture, and ecological environment). Several scenarios corresponding to different flow patterns, which reflect different probabilities of water resource availability and environmental carrying capacity, were examined. On the basis of traditional water resource allocation, this model adds consideration of ecological value factors, which is conducive to the synergistic efficiency of socio-economic and ecological water consumption. Results revealed that the water resource carrying capacity, ecological value factors, and water environmental capacity are the main factors affecting the optimal allocation of water resources. Furthermore, the optimal allocation scheme for water resources coupled with ecological value factors were determined to realize the coordinated development of social economic benefits and ecological benefits. The current study findings are of great significance for establishing a rational water resource management system for water resource exploitation and utilization. This model can be used to guide various departments in Dalian to formulate an optimal water resources allocation scheme by considering ecological value factors, and provide a basis for realizing the coordinated development of Dalian’s socio-economic development goals, water resource utilization, and environmental quality improvement.

Irrigated areas drive irrigation water withdrawals

A sustainable management of global freshwater resources requires reliable estimates of the water demanded by irrigated agriculture. This has been attempted by the Food and Agriculture Organization (FAO) through country surveys and censuses, or through Global Models, which compute irrigation water withdrawals with sub-models on crop types and calendars, evapotranspiration, irrigation efficiencies, weather data and irrigated areas, among others. Here we demonstrate that these strategies err on the side of excess complexity, as the values reported by FAO and outputted by Global Models are largely conditioned by irrigated areas and their uncertainty. Modelling irrigation water withdrawals as a function of irrigated areas yields almost the same results in a much parsimonious way, while permitting the exploration of all model uncertainties. Our work offers a robust and more transparent approach to estimate one of the most important indicators guiding our policies on water security worldwide.

Irrigated areas grow faster than the population

Unfolding regularities between population and irrigated agriculture might increase our capacity to predict their coevolution and better ensure food security and environmental welfare. Here I use three different data sets with detailed information at the national level for ~70% of the countries of Africa, Asia, the Americas, and Europe between 1950 and 2017 to show that irrigated areas might grow disproportionally for a given increase in population, e.g., with β > 1. The results are robust across continents, time series, population cut-offs, and variations in the area accounted for irrigation by official institutions and independent scholars. This systematic pattern suggests the existence of an underlying law driving the growth rate of irrigated areas that transcends local particularities and can be well approximated by a power function of population, specially in the case of the Americas, Asia, and Europe. Nonlinearities derived from the open-ended growth rate of irrigated areas should be taken into consideration when designing irrigation policies in order to avoid unexpected environmental costs.