Most General Circulation Models predict more infrequent but larger precipitation events in the eastern United States combined with a warmer climate. This could have a negative effect on maize production. To understand the sensitivity of maize production to future changes in precipitation, we analyzed growing season precipitation and average state maize yields in the eastern United States for the period 1963–2011. Growing season precipitation did not show a strong trend during this period. However, crop yields increased at 3.90% in the southern, 2.62% in the central, and 2.31% in the northern part of the eastern United States, which we attributed to technology and management. To separate technology and management effects from precipitation variability, we corrected maize yields for these yield trends. We then correlated maize yield corrected for advances in technology and management with total growing season precipitation and precipitation in the critical month of pollination, from the regional to state scale. Maize yield - precipitation relationships showed that moisture shortage rather than excess determined maize yield in the Eastern United States. The relationship between total growing season precipitation-maize yield was stronger in the southeastern than in the northeastern U.S., but the critical month precipitation-maize yield relationship was stronger in the northeastern than in the southeastern U.S. If climate model predictions are accurate and total growing season precipitation will not decrease in this region but variability will, it is likely that maize yields in the northeastern U.S. will be more significantly affected.

Purpose: Forestry carbon sink (FCS) is not only an important measure to deal with the current global climate change but also an effective way to build an ecological civilization. As an important form of implementation of FCS, the afforestation and reforestation projects under the clean development mechanism (CDM A/R) have important functions such as ecological protection and economic growth. This paper aims to evaluate the short-term and long-term impact of CDM on the county economy and its impact mechanism. Design/methodology/approach: This paper first uses propensity score matching to match the county (treatment group). Second, this paper uses difference in difference to estimate the net effect of CDM A/R project on county economic development to reduce estimation error. Finally, the impact mechanism of implementing CDM A/R project on county economic development was tested. Findings: The CDM A/R project has significantly promoted the development of real gross domestic product (GDP) and per capita real GDP in the region. Because of the long project cycle, this promotion is not immediate in the short term and has an obvious hysteresis effect. The longer the implementation time, the greater the promotion of the local economy will develop. The results are robust after the robustness test that uses the single-difference method. The CDM A/R project has promoted local economic growth by optimizing the local industrial structure, increasing the regional capital stock and raising the regional government’s fiscal revenue and expenditure. Originality/value: This paper provides a critical overview of the relationship between clean development mechanism and local economic development.

We used the data of the China Labor-force Dynamics Survey 2014 to examine the effects of livelihood capitals which include natural, material, human, financial, and social capitals on total household income, per capita income, agricultural income, wage income, operational income, and property income inequality among rural households in China. Results showed that different kinds of livelihood capitals have different effects on different types of rural households’ income. Specifically; (1) although, the area of cultivated land reduces agricultural income inequality, it increases per capita income inequality. (2) Forest land area enlarges per capita income inequality and total household income inequality. (3) Tractor variable reduces inequality in agricultural income and total household income. (4) While reducing the property income inequality, education variable enlarges the wage income inequality, the per capita income inequality and the total household income inequality. (5) Book variable reduces property income inequality. (6) Loan variable increases inequality in agricultural incomes. (7) Party variable reduces the agricultural income inequality. (8) Although, the internet variable increases agricultural income inequality, and property income inequality, it reduces wage income inequality, operational income inequality, per capita income, and total household income inequality.

This review paper focused on the correlation between land degradation and poverty. Pakistan is an agricultural country and agriculture is the backbone of Pakistan`s economy. For the rapid growth of population food security should be under guarantee as well as the food production. In that farmers overused agrarian inputs, such as fertilizer, pesticide and water, environment and farmers were affected from the perspective of contamination and disease increase respectively. Due to over-exploitation of fertilizer and irrigation, ground water was contaminated, soil fertility weakening,salinity increasing and waterlogged. Consequently, soil was hard to be cultivated. In Pakistan 70% of people live in rural areas who are directly or indirectly involved in agriculture. As a result of land degradation farmers can not gain much benefit from agricultural activities and they are also unable to feed their children. Many of them became criminals, therefore, poverty deepened day after day. In order to alleviate poverty, Pakistan government should subsidize farmers on environmentally friendly inputs and; government should also open agricultural training schools to engage farmers in modern methods of cultivation, and provide modern technologies with subsidy rate. When the farmers are aware of how to increase the fertility of soil by employing modern methods, they can gain higher production, and obvious higher production is critical for living a better life and reducing poverty.