ending civil conflict through rebel demobilization

We examine the role of FM radio in mitigating violent conflict. We collect original data on radio broadcasts encouraging defections during the Lord's Resistance Army (LRA) insurgency. This constitutes the first quantitative evaluation of an active counterinsurgency policy that encourages defections through radio messages. Exploiting random topography-driven variation in radio coverage along with panel variation at the grid-cell level, we identify the causal effect of messaging on violence. Broadcasting defection messages increases defections and reduces fatalities, violence against civilians, and clashes with security forces. Income shocks have opposing effects on both the conflict and the effectiveness of messaging.publishersversionpublishe

Experimental evidence from Mozambique

Natural resources can have a negative impact on the economy through corruption and civil conflict. This paper tests whether information can counteract this political resource curse. We implement a large-scale field experiment following the dissemination of information about a substantial natural gas discovery in Mozambique. We measure outcomes related to the behavior of citizens and local leaders through georeferenced conflict data, behavioral activities, lab-in-The-field experiments, and surveys. We find that information targeting citizens and their involvement in public deliberations increases local mobilization and decreases violence. By contrast, when information reaches only local leaders, it increases elite capture and rent-seeking.authorsversionpublishe

Demand Fluctuations and Innovation Investments: Evidence from the Great Recession in Spain

Fluctuations in aggregate demand can influence the decision to invest in innovation. This paper focuses on this choice when fluctuations are heterogeneous across productive strata of the economy. To guide the empirical analysis, we model firms’ decision to invest in innovation. In our framework, firms are heterogeneous and demand shocks are exogenous. We show that drops in aggregate expenditure reduce the proportion of firms investing in innovation. We then study investment behaviour in a panel of Spanish innovative manufacturing firms. These firms are all investing in internal R&D in 2004 and are yearly surveyed until 2013. During the Great Recession, firms experienced large contractions in aggregate consumption. The reduction reached 10% of its pre-crisis trend. We proxy heterogeneous fluctuations in demand with entry and exit rates in the productive stratum of each firm. Rates incorporate all firms, including non-innovative firms. Higher exit rates are associated with reductions of 2 to 3% in the share of firms investing in innovation. The drop is larger for smaller firms, which also experience larger decreases in sales. These results are in line with our theoretical predictions. Our estimates are robust to the inclusion of indicators of time-varying credit constraints. For these constraints, we observe a marginal role among innovative firms

Demand Fluctuations and Innovation Investments: Evidence from the Great Recession in Spain

Fluctuations in aggregate demand can influence the decision to invest in innovation. This paper focuses on this choice when fluctuations are heterogeneous across productive strata of the economy. To guide the empirical analysis, we model firms’ decision to invest in innovation. In our framework, firms are heterogeneous and demand shocks are exogenous. We show that drops in aggregate expenditure reduce the proportion of firms investing in innovation. We then study investment behaviour in a panel of Spanish innovative manufacturing firms. These firms are all investing in internal R&D in 2004 and are yearly surveyed until 2013. During the Great Recession, firms experienced large contractions in aggregate consumption. The reduction reached 10% of its pre-crisis trend. We proxy heterogeneous fluctuations in demand with entry and exit rates in the productive stratum of each firm. Rates incorporate all firms, including non-innovative firms. Higher exit rates are associated with reductions of 2 to 3% in the share of firms investing in innovation. The drop is larger for smaller firms, which also experience larger decreases in sales. These results are in line with our theoretical predictions. Our estimates are robust to the inclusion of indicators of time-varying credit constraints. For these constraints, we observe a marginal role among innovative firms

Analysis of the Dynamics of Vegetation Cover and Land Use in Forest Management Unit 00-004 and its Surroundings on the Coast of Cameroon

In Cameroon, the government gives serious attention to protect Forest Management Units (FMU). Unfortunately, vegetation cover of FMU 00-004 decreases in the area as years ago due to anthropogenic pressures. The present study aimed to analyse the dynamics of the vegetation cover and land use of the FMU 00-004 and its surroundings in Cameroon, in the period between 1988-2020. Landsat images (1988, 2001 and 2020) and field investigations were used and processed by ENVI 5.3 software. 175 people around the forest were interviewed to obtain their perceptions on the causes of forest landscape degradation. In 1988, the FMU 00-004 and its surroundings consisted of seven types of land cover, the most important being dense forest, open forest and woody savannah. Cropland, building area, water area and eroded soil were less than 2%. In 2020, building area and croplands surface areas increased while dense and open forests cover decreased. Change in vegetation was more pronounced between 1988 and 2020 and the deforestation rate was 2.55%. The degradation main causes were settlements of the forest exploitation companies and agricultural practices. For sustainable production systems, landscape planning should be put in place by logging company to reduce Land use / Land cover challenges.

A systems biology framework integrating GWAS and RNA-seq to shed light on the molecular basis of sperm quality in swine

Background Genetic pressure in animal breeding is sparking the interest of breeders for selecting elite boars with higher sperm quality to optimize ejaculate doses and fertility rates. However, the molecular basis of sperm quality is not yet fully understood. Our aim was to identify candidate genes, pathways and DNA variants associated to sperm quality in swine by analysing 25 sperm-related phenotypes and integrating genome-wide association studies (GWAS) and RNA-seq under a systems biology framework. Results By GWAS, we identified 12 quantitative trait loci (QTL) associated to the percentage of head and neck abnormalities, abnormal acrosomes and motile spermatozoa. Candidate genes included CHD2, KATNAL2, SLC14A2 and ABCA1. By RNA-seq, we identified a wide repertoire of mRNAs (e.g. PRM1, OAZ3, DNAJB8, TPPP2 and TNP1) and miRNAs (e.g. ssc-miR-30d, ssc-miR-34c, ssc-miR-30c-5p, ssc-miR-191, members of the let-7 family and ssc-miR-425-5p) with functions related to sperm biology. We detected 6128 significant correlations (P-value ≤ 0.05) between sperm traits and mRNA abundances. By expression (e)GWAS, we identified three trans-expression QTL involving the genes IQCJ, ACTR2 and HARS. Using the GWAS and RNA-seq data, we built a gene interaction network. We considered that the genes and interactions that were present in both the GWAS and RNA-seq networks had a higher probability of being actually involved in sperm quality and used them to build a robust gene interaction network. In addition, in the final network we included genes with RNA abundances correlated with more than four semen traits and miRNAs interacting with the genes on the network. The final network was enriched for genes involved in gamete generation and development, meiotic cell cycle, DNA repair or embryo implantation. Finally, we designed a panel of 73 SNPs based on the GWAS, eGWAS and final network data, that explains between 5% (for sperm cell concentration) and 36% (for percentage of neck abnormalities) of the phenotypic variance of the sperm traits. Conclusions By applying a systems biology approach, we identified genes that potentially affect sperm quality and constructed a SNP panel that explains a substantial part of the phenotypic variance for semen quality in our study and that should be tested in other swine populations to evaluate its relevance for the pig breeding sector.info:eu-repo/semantics/publishedVersio

A pilot RNA-seq study in 40 pietrain ejaculates to characterize the porcine sperm microbiome

The microbiome plays a key role in homeostasis and health and it has been also linked to fertility and semen quality in several animal species including swine. Despite the more than likely importance of sperm bacteria on the boar's reproductive ability and the dissemination of pathogens and antimicrobial resistance genes, the high throughput characterization of the swine sperm microbiome remains scarce. We carried RNA-seq on 40 ejaculates each from a different Pietrain boar and found that a proportion of the sequencing reads did not map to the Sus scrofa genome. The current study aimed at using these reads not belonging to pig to carry a pilot study to profile the boar sperm bacterial population and its relation with 7 semen quality traits. We found that the boar sperm contains a broad population of bacteria. The most abundant phyla were Proteobacteria (39.1%), Firmicutes (27.5%), Actinobacteria (14.9%) and Bacteroidetes (5.7%). The predominant species contaminated sperm after ejaculation from soil, faeces and water sources (Bacillus megaterium, Brachybacterium faecium, Bacillus coagulans). Some potential pathogens were also found but at relatively low levels (Escherichia coli, Clostridioides difficile, Clostridium perfringens, Clostridium botulinum and Mycobacterium tuberculosis). We also identified 3 potential antibiotic resistant genes from E. coli against chloramphenicol, Neisseria meningitidis against spectinomycin and Staphylococcus aureus against linezolid. None of these genes were highly abundant. Finally, we classified the ejaculates into categories according to their bacterial features and semen quality parameters and identified two categories that significantly differed for 5 semen quality traits and 13 bacterial features including the genera Acinetobacter, Stenotrophomonas and Rhodobacter. Our results show that boar semen contains a bacterial community, including potential pathogens and putative antibiotic resistance genes, and that these bacteria may affect its reproductive performance.info:eu-repo/semantics/acceptedVersio