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Yield effects of agricultural cooperative membership in developing countries: A meta-analysis
Get PDFThis study uses a meta-analysis to synthesize the effects of agricultural cooperative membership on the yield of crops and livestock. It collects 158 estimated yield effects from 42 studies, covering 19 developing countries. Our analysis finds evidence that there exists positive publication bias in the empirical literature, confirming that researchers and journals have a preference to publish articles that report positive and significant results. After correcting for publication bias, we find that cooperative membership has a small-sized and insignificant effect on the yield. The meta-regression analysis reveals that variation in the reported yield effects can be largely explained by the study attributes such as the sample type (full sample vs. subsample), membership ratio, econometric approaches (instrumental-variable based parametric approach, non-parametric approach or ordinary least square regression), effect size types (average treatment effects on the treated, average treatment effects, or coefficient), agro-product type (grain or others), and climate zones (tropical or non-tropical)
Small acts with big impacts: Does garbage classification improve subjective well-being in rural China?
Get PDFSolid waste has surged in rural China, home to more than 540 million people. To preserve the environment, the Chinese government has piloted garbage classification programs. However, little is known about whether and to what extent classifying garbage affects people's subjective well-being—should its effects be positive, people would be more amenable to classifying garbage, making it easier to entrench garbage classification practices and programs and ultimately improve the environment. Accordingly, we analyze the impact of garbage classification on subjective well-being using the 2020 China Land Economic Survey data. An endogenous treatment regression model is utilized to address self-selection into garbage classification programs. We find that this simple and somewhat mundane practice can significantly improve people's happiness and life satisfaction. These results reaffirm the compound benefits of allocating more public resources to accelerate the adoption of garbage classification in rural areas
Assessing the degradation of environmental DNA and RNA based on genomic origin in a metabarcoding context
No full textMolecular tools of species identification based on eNAs (environmental nucleic acids; environmental DNA [eDNA] and environmental RNA [eRNA]) have the potential to greatly transform biodiversity science. However, the ability of eNAs to obtain “real-time” biodiversity estimates may be complicated by the differential persistence and degradation dynamics of the molecular template (eDNA or eRNA) and the barcode marker used. Here, we collected water samples over a 28-day period to comparatively assess species detection using eDNA and eRNA metabarcoding of two distinct barcode markers—a mitochondrial mRNA marker (COI) and a nuclear rRNA marker (18S)—following complete removal of Arthropoda taxa in a semi-natural freshwater system. Our findings demonstrate that Arthropoda community composition was largely influenced by marker choice, rather than molecular template, individual microcosm, or sampling time point. Furthermore, although eRNA may capture similar species diversity as the established eDNA method, this finding may be marker-dependent. Although we found little to no difference in decay rates observed among sample groups (COI eDNA, COI eRNA, 18S eDNA, 18S eRNA), this result is likely due to limitations in the ability of eNA-based metabarcoding to provide a strong correlation between true eNA copy numbers present in the environment and final read counts obtained (following the metabarcoding workflow). Collectively, our findings provide further support for the use of multi-marker assessments in metabarcoding surveys to unravel the broadest taxonomic diversity possible, highlight the limitations of eNA metabarcoding methods in providing accurate decay rate estimates, as well as establish the need for further comparative studies using both metabarcoding and single-species detection methods to assess the persistence and degradation dynamics of eNAs for a diverse range of taxa
Contemporaneous and lagged R² decomposed connectedness approach: New evidence from the energy futures market
No full textIn this study, we investigate the return propagation mechanism across six energy futures, namely, Crude Oil, Heating Oil, Gasoline, Natural Gas, Kerosene, and Propane ranging from November 21st, 2014 until April 6th, 2023 by using a novel R² decomposed connectedness approach. This framework allows to efficiently decompose connectedness measures into contemporaneous and lagged components. We find that the dynamic total connectedness is heterogeneous over time and economic-event dependent. Furthermore, the empirical results highlight that the contemporaneous effects are more pronounced on average while a significant amount of lagged spillovers occur in the case of Kerosene and Propane. We find that Heating Oil is the main net transmitter of shocks followed by Gasoline and Crude Oil while the main net receiver of shocks is Kerosene followed by Propane and Natural Gas. Finally, robust R² connectedness measures are provided
Dynamic connectedness between COVID-19 news sentiment, capital and commodity markets
No full textThis study investigates the dynamic transmission mechanism between COVID-19 news sentiment (Google Trends Index), and S&P100, crude oil and gold volatility indices using the recently developed time-varying parameter vector autoregressive (TVP-VAR)-based extended joint connectedness approach. This framework corrects for the Generalized Forecast Error Variance Decomposition (GFEVD) normalization problem. The obtained empirical results suggest that dynamic total connectedness is heterogeneous over time and severely affected by COVID-19. More importantly, we identify COVID-19 news sentiment to be the main driver of spillover shocks indicating that it is indeed an important predictor of the volatility indices employed in our study. Thus, our findings have important implications for policymakers, private investors, as well as for portfolios and risk managers
A taxonomy-free diatom eDNA-based technique for assessing lake trophic level using lake sediments
No full textAnthropogenic eutrophication is one of the most pressing issues facing lakes globally. Our ability to manage lake eutrophication is hampered by the limited spatial and temporal extents of monitoring records, stemming from the time-consuming and expensive nature of physiochemical and biological monitoring. Diatom-based biomonitoring presents an alternative to traditional eutrophication monitoring, yet it is restricted by the high degree of taxonomic expertise required. Environmental DNA metabarcoding, while providing a promising substitute for diatom community enumeration, is plagued by inadequate taxonomic coverage of reference databases and methodological bias, limiting its use for biomonitoring. Here we show that taxonomy-free diatom-biomonitoring, in which environmental DNA metabarcoding data is utilised but not assigned to specific taxonomic classes, presents an accurate, fast, and relatively automated alternative to taxonomically assigned eutrophication biomonitoring. Our taxonomy-free index accounted for 85% of trophic level variability across 89 lakes and had the lowest average prediction error of the three approaches tested. By not relying on taxonomic identification or metabarcoding reference databases, taxonomy-free biomonitoring maintains diatom diversity that is lost in taxonomic assignment using molecular approaches. Furthermore, by utilising lake sediments, the approach outlined here presents a time-integrated estimation of lake trophic level and thus does not require time-consuming seasonal sampling. Taxonomy-free biomonitoring addresses the limitations of traditional physicochemical eutrophication monitoring and taxonomic biomonitoring alternatives and can be used to extend the spatial and temporal extents of eutrophication monitoring
Soil moisture is a primary driver of comammox Nitrospira abundance in New Zealand soils
Get PDFThe objectives of this study were to investigate the abundance and community composition of comammox Nitrospira under: (i) pasture-based dairy farms from different regions, and (ii) different land uses from the same region and soil type. The results clearly showed that comammox Nitrospira were most abundant (3.0 × 10⁶ copies) under the west coast dairy farm conditions, where they were also significantly more abundant than canonical ammonia oxidisers. This was also true in the Canterbury dairy farm. The six land uses investigated were pine monoculture, a long term no input ecological trial, sheep + beef and Dairy, both irrigated and non-irrigated. It was concluded that comammox Nitrospira was most abundant under the irrigated dairy farm (2.7 × 10⁶ copies). Contrary to the current industry opinion, the relatively high abundance of comammox Nitrospira under fertile irrigated dairy land suggests that comammox Nitrospira found in terrestrial ecosystems may be copiotrophic. it was also determined that comammox Nitrospira was more abundant under irrigated land use than their non-irrigated counterparts, suggesting that soil moisture is a key environmental parameter influencing comammox abundance. Comammox abundance was also positively correlated with annual rainfall, further supporting this theory. Phylogenetic analysis of the comammox Nitrospira detected determined that 17 % of the comammox community belonged to a newly distinguished subclade, clade B.2. The remaining 83 % belonged to clade B.1. No sequences from clade A were found
Integration and risk transmission in the market for crude oil: New evidence from a time-varying parameter frequency connectedness approach
No full textIn this study, we introduce a novel time-varying parameter vector autoregressive frequency connectedness approach to obtain refined measures of the frequency transmission mechanism and dynamic integration among six well-established crude oil benchmarks. The period of investigation ranges from May 14th, 1996 to December 3rd, 2020 and focuses on the differences between short-term (1–5 days) and long-term (6–100 days) crude oil volatility connectedness. Findings are suggestive of relatively strong co-movements among crude oil volatility over time. For most part of the sample period, connectedness occurs in the short-run; nonetheless, starting approximately in 2010, long-run connectedness gains much prominence until at least the end of 2015. Long-run connectedness is also prevalent at the beginning of 2020 caused by the COVID-19 pandemic. We opine that periods of increased long-run connectedness relate to deeper changes in the market for crude oil that bring about new dynamics and associations within the specific network
Identification, mapping, and characterisation of a mature artificial mole channel network using ground-penetrating radar
No full textMole channel drainage is a cost-effective and efficient way to drain slowly permeable agricultural soils. Artificial drainage has the potential to significantly influence catchment hydrology and contaminant source areas, but there is little information available about the extent, connectivity, layout, density or longevity of mole channel networks, which are commonly estimated to deteriorate within 5–20 years. Such information is important for understanding landscape hydrodynamics but, currently, there are no established techniques for calibrating estimates of mole network characteristics at the paddock or larger scale. This study characterised a 30-plus-year-old mole channel network in a small agricultural basin in Southland, New Zealand, and tested the utility of ground-penetrating radar (GPR) for identifying, mapping, and characterising mole channel drainage. A dual frequency GPR antenna (700 and 250 MHz), connected to a high-precision, real-time kinematic global positioning system, was tested and proved effective at locating mole channels and a tile drain with high lateral precision and accuracy. Surveying of six plots demonstrated that the mole network was complex in design and had a high density (1.6 m m−2) of interconnected, multidirectional mole channels. Significantly, the mole channels were predominantly in good condition and spatially well connected. Visual observations found no evidence that the blade slot and secondary soil fractures, formed by the mole plough during installation, persisted after 30 years. However, root growth and worm burrowing into the mole channels suggest they are hydraulically connected to the surrounding soil through natural macropores. Our results provide the first attempt at mapping and characterising mature, multi-generational mole channel networks in slowly permeable loess soils. The results have significance for understanding catchment-scale hydrodynamics in mole-drained landscapes, especially considering that the life span of these artificial drainage networks is shown to be considerably longer than previous estimates for loess-derived, silt loam soils
Emigrants’ visit home and remittance inflows nexus
No full textImmigrants have created better living standards by emigrating, and they also contribute to their homeland in one of two ways: by visiting as tourists or by sending remittances back home. In this paper, we examine the nexus between these two crucial channels: remittance inflows and emigrants' visits home. We model the emigrants' visits back home and show that remittances inflows per emigrant have a strong impact on emigrants' visits home. However, the relationship is mixed among different regions. For emigrants from Africa and Latin America and Asia, the remittances have a negative impact on home visits, indicating that emigrants send more money and skip visiting their homes subsequently. For emigrants from MENA, there is a significant positive impact of the remittance inflows on home visits