2024年3月16日发(作者：)

农村扶贫脱贫中英文

英文

Effective alleviation of rural poverty depends on the interplay between productivity, nutrients,

water and soil quality

Sonja Radosavljevic， L. JamilaHaider，

Steven ，MajaSchlüter

Abstract

Most of the world's poorest people come from rural areas and depend on their local

ecosystems for food production. Recent research has highlighted the importance of

self-reinforcing dynamics between low soil quality and persistent poverty but little is known on

how they affect poverty alleviation. We investigate how the intertwined dynamics of household

assets, nutrients (especially phosphorus), water and soil quality influence food production and

determine the conditions for escape from poverty for the rural poor. We have developed a suite of

dynamic, multidimensional poverty trap models of households that combine economic aspects of

growth with ecological dynamics of soil quality, water and nutrient flows to analyze the

effectiveness of common poverty alleviation strategies such as intensification

through agrochemical inputs, diversification of energy sources and conservation tillage. Our

results show that (i) agrochemical inputs can reinforce poverty by degrading soil quality, (ii)

diversification of household energy sources can create possibilities for effective application of

other strategies, and (iii) sequencing of interventions can improve effectiveness of conservation

tillage. Our model-based approach demonstrates the interdependence of economic and ecological

dynamics which preclude blanket solution for poverty alleviation. Stylized models as developed

here can be used for testing effectiveness of different strategies given biophysical and economic

settings in the target region.

Keywords：Poverty trap，Dynamical system，Multistability，Agroecosystem，Phosphorus，

Soil quality

1. Introduction

How to alleviate global poverty and eradicate hunger in places with low agricultural

productivity are among humanity's greatest challenges. The concept of poverty traps as situations

characterized by persistent, undesirable and reinforcing dynamics (Haider et al., 2018) is

increasingly being used to understand the relationship between persistent poverty and

environmental sustainability (Barrett and Bevis, 2015, Barrett and Constas, 2014, Lade et al.,

2017). How poverty and environmental degradation are conceptualized and represented in models

can inform development interventions and thereby influence the effectiveness of those

interventions (Lade et al., 2017). Previous poverty trap models have focused on environmental

quality or pollution (Barro and Sala-i Martin, 2004, Smulders, 2000, Xepapadeas, 2005),

neglecting social-ecological interactions; have illustrated how positive feedback between wealth

and technology can increase inequality and result in poverty traps through resource degradation

(Mirza et al., 2019); have investigated relations between human health and poverty (Ngonghala et

al., 2017); have used one-dimensional models that can lead to simplified conclusions and

inappropriate policy outcomes (Kraay and Raddatz, 2005); have been static models that cannot

capture dynamic phenomena such as traps and feedbacks (Barrett and Bevis, 2015); or have been

highly abstracted (Lade et al., 2017).

Biophysical complexity is not often considered in poverty trap models and relations between

agricultural interventions and social-ecological poverty trap dynamics remain unexplored.

Partially because of this, development efforts tend to focus on blanket solutions, such as the ‘big

push’: promoting external asset inputs, while neglecting a multitude of other factors affecting

poverty. Lade et al. (2017)highlighted the importance of linking economic, natural and human

factors in explaining poverty traps and concluded that the usefulness of interventions depends on

context, particularly the relationship between poverty and environmental degradation. We build on

this study as a conceptual framework to address knowledge gaps regarding the interplay between

poverty and the biophysical environment in three ways: (1) we explore how biophysical

complexity of the household-farm social-ecological system influences the dynamics of poverty

traps in agro ecosystems, (2) we assess the impact of development interventions on the dynamics

of the system, and (3) we test the effectiveness of interventions. To this end we have developed a

series of dynamical systems models that we use to test diverse sequences of interventions for

alleviating poverty.

We describe biophysical complexity through factors that affect crop growth and limit food