Natural Resources Forum

doi: 10.1111/1477-8947.12228pmid: N/A

Aryal, Jeetendra Prakash; Sapkota, Tek Bahadur; Rahut, Dil Bahadur; Gartaula, Hom Nath; Stirling, Clare

doi: 10.1111/1477-8947.12259pmid: N/A

The adverse impacts of climate change, in many cases, aggravate existing gender inequalities and hinder developing countries from achieving the targets set by the United Nations Sustainable Development Goals (SDGs). It is, therefore, crucial to understand whether there exists a gender gap in climate change adaptation and investigate the factors explaining the gap to reduce the vulnerability of the farming households to surging climatic risks. Using data from 2279 farm households in Ethiopia and applying a multivariate probit model and exogenous switching treatment effect regression method, this study examines the existing gender gap in climate change adaptations among farmers in Ethiopia and factors contributing to this relationship. The results show a significant gender gap in climate change adaptation in farming households due to the differences in both observable and unobservable characteristics of male‐ and female‐headed households. It indicates that reducing the gap can enhance climate change adaptation by female‐headed households by almost 19%. Women's workload in household chores significantly reduces their likelihood to adopt climate change adaptation measures. Therefore, unless policies proposed target institutional factors, including social and cultural barriers, traditional gender norms and division of labor, and other intrinsic behavioral issues, addressing only observed characteristics may not fully address the gender gap. To bring about transformational changes in the existing gender norms and social attitudes, long‐term gender‐informed policies are essential, along with short‐term projects, to address the gender gap in climate change adaptation through the provision of equitable opportunities for all.

Lee, Chien‐Chiang; Yuan, Ying; Wen, Huwei

doi: 10.1111/1477-8947.12258pmid: N/A

The existing literature mainly focuses on the impact of information communication technologies on carbon emissions, but little attention has been paid to the role of the digital economy in transporting carbon emissions. This paper calculates the index of the digital economy through the entropy weight Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method and constructs the panel data of 30 provinces in China from 2008 to 2017. By extending the Stochastic Impacts by Regression on Population, Affluence and Technology model, this study explores the potential linear and non‐linear relationship between digital economy and carbon emissions in the transport sector. Empirical results show that the digital economy has the alleviating effect on carbon emissions in the transportation sector, and a change in the digital economy of one unit standard deviation resulted in a 6.14% reduction in carbon emissions. In terms of sub‐regions, the digital economy has a significant negative impact on transport carbon emissions in the eastern and central regions, while it is insignificant in the western regions. This paper further investigates the threshold effect of urbanization on the relationship between the digital economy and transportation‐related carbon emissions. The digital economy accelerates the transport sector's carbon emissions in the low urbanization stage, while it reduces the carbon emissions in the high urbanization stage.

Hamidi, Ali; Mehrabi, Aliakbar; Javadi, Seyed Akbar; Imani, Aliakbar

doi: 10.1111/1477-8947.12257pmid: N/A

Natural resources development cooperatives (NRDCs) are leading enterprises that develop sustainable community‐based solutions. Basically, such cooperatives attempt to engage beneficiaries in environmental conservation through collective action. However, there exist remarkable shortcomings in administering these types of cooperatives. This paper aims to investigate beneficiaries' willingness to participate and invest in NRDCs based on three educational, economic, and social sections, each represented by their corresponding components, which represent the variables (sub‐factors) of each section. The current research was performed using a descriptive‐survey approach. Semi‐structured interviews were conducted with 63 cooperatives' board members located in Ardabil Province in Iran. Results discovered that three variables of information, participation acceptance rate and top‐down planning from educational factors alongside those of conservation effectiveness and projected outlook from the economic factor significantly affect participation levels in NRDCs. Similarly, the lack of rangeland ownership, cooperatives' limited problem‐solving capabilities, and concerns about environmental conservation of formerly demolished lands, all components of the social section investigated in this study, highly influenced beneficiaries' participation in cooperatives. Correlation coefficient analysis between the efficient factors showed that education levels have no significant relationship with the two remaining factors; however, the economic and social factors positively and significantly (p < 0.01) relate to beneficiaries' participation level. Nonparametric correlation analysis determined that variables from the economic factor analysis, such as the financial capital size, awareness levels, indigenous culture, people's experiences interacting with the administrative bodies of NRDCs, the state‐run economy, and the lack of support for beneficiaries by cooperatives from the social factor analysis each have independent and distinct relationships that affect participation in cooperatives. However, from the educational factor analysis, all variables were influenced reciprocally and were of inferior importance to participation in NRDCs.

Mishra, Sweta; Kumar, Shailesh; Acharya, Suresh

doi: 10.1111/1477-8947.12260pmid: N/A

The untapped divergence of pigeonpea has remained unutilized for ages. Pigeonpea is an important natural resource with a great divergence that can be explored in the field of sustainable agricultural development. This study was undertaken to assess the nutritional divergence available in 104 cultivated and wild pigeonpea genotypes from India and Africa. Pigeonpea is studied to identify suitable genotypic groups to enhance nutritional traits for future breeding programs. Genotypes of pigeonpea exhibited highly significant differences in terms of seed iron and, zinc concentrations, protein content, phytic acid levels, lipid content, moisture content, fiber content and seed weight. Our D2 analysis grouped 104 different pigeonpea accessions into eleven clusters. Five of the eight characters including seed phytic acid levels, iron, fiber, lipid and protein contents were the predominant characters that contributed towards the pigeonpea's total divergence. Cluster II exhibited the maximum seed iron concentration. Cluster IV exhibited the maximum seed zinc concentration, lipid and moisture content; it exhibited the least phytic acid and fiber content which is desirable with regards to the bioavailability of iron and zinc. The accessions in clusters II, III, IV, V and XI are diverse and have desirable content levels of traits found beneficial for enhancing seed iron and zinc concentrations in pigeonpea. A D2 analysis revealed that Indo‐African C. cajan, C. platycarpus and R. rothii had the maximum mean seed iron concentration and R. bracteata had the maximum mean seed zinc concentration. The promising genotypes identified in the present study can contribute towards selecting suitable starting material for biofortification in pigeonpea improvement programmes.

Xu, Xiumei; Tan, Yilan; Feng, Chao

doi: 10.1111/1477-8947.12261pmid: N/A

Although emergy theory has made progress in the field of eco‐compensation research, there is still a lack of review articles, summarizing the existing knowledge structure in this area of study. Accordingly, the objective of this paper is to provide a reference for researchers by characterizing the current status of emergy theory in the field of eco‐compensation and to establish the internal logic structure among existing studies, based upon a qualitative analysis of textual data. Inspired by the grounded theory, twelve concepts within five categories of emergy theory were extracted by open, axial, and selective coding of relevant literature. Concepts were extracted from the texts and categories were determined according to the inherent logical relationships among those concepts. The “knowledge structure model of emergy theory in the field of eco‐compensation” was constructed and the following five principal categories were identified: “emergy indicators system,” the “integration of methods and theories,” “research subjects,” “calculation of compensation standards,” and “research concerns.” Moreover, core and supporting genera were also identified from these five axial codes. Finally, the research focuses and hotspots were explored according to the theoretical frameworks as indicated by the core and supporting genera. The findings of this paper provide a reference for researchers to further promote innovation in the application of emergy theory in the field of eco‐compensation.