Rain-fed agriculture is the main source of livelihood for most of Burundi’s population, especially in the northeastern part of the country. This research is aimed at examining how smallholder farmers in the Northeastern region of Burundi perceive climate change and variability and at identifying the methods that are used to adapt, based on data from 200 small farmers and on actual weather data recorded between 1986 and 2017. We find that the majority of farmers (54%) perceive significant increases in temperature and unpredictability of rainfall duration and intensity and are making adjustments to adapt their agriculture in response to changes in climate. Over 80% of farmers have implemented at least one adaptation strategy among the nine evaluated. Changing crop varieties, changing fertilizers, and planting shade trees are the main adaptation strategies that were being implemented by farmers across the study area. The results of a binary regression model showed that the agricultural education and experience of farmers, as well as farm and family size, livestock ownership, climate information access, credit access, and farm income, strongly influence smallholder farmers’ decisions to adapt to climate change. The main obstacles are the lack of information on climate and adaptation strategies, and poverty, which makes it difficult to cope with the increased costs of farming. Understanding farmers’ perceptions of climate change and variability on a local level would provide information on how to develop adaptation strategies. The present study suggests the need for strengthening farmers’ capacities and improving the policy framework for adaptation to climate change in order to improve farmers’ livelihoods. Implications for policymakers will, therefore, include making flexible credit facilities, and investing in training extension agents on both climate change outreach and coping strategies.
Au Burundi, les aires protégées continuent d’être menacées. Il en découle une dégradation de la biodiversité se manifestant par des pertes des écosystèmes et des espèces, et par conséquent des services écosystémiques y associés. La présente étude poursuit l’objectif d’examiner dans quelle mesure les principales parties prenantes à la conservation des aires protégées du Burundi perçoivent les différents services écosystémiques fournis et d‘apprécier l’utilisation des espèces de ces aires protégées par la population riveraine. Les données ont été collectées au moyen d’une enquête qualitative auprès des gestionnaires des aires protégées du Burundi, des représentants de l’administration (communale et collinaire) et des populations riveraines à ces aires protégées. Ces données ont été soumises au calcul des proportions pour des analyses comparées des perceptions des différentes catégories de répondants selon les différents services écosystémiques. Les résultats ont montré que toutes les catégories de répondants identifient l’existence de quatre types de services écosystémiques (approvisionnement, régulation, support et socio-culturel) fournis par les aires protégées burundaises bien que les réponses varient d’une catégorie à une autre. Les résultats ont en outre montré une utilisation illicite des espèces aussi bien végétales qu’animales par les populations riveraines. Les initiatives de sensibilisation à l’endroit de toutes les parties prenantes à la conservation (en particulier les populations riveraines) restent essentielles pour la pérennité de ces services écosystémiques. In Burundi, protected areas continue to be threatened. This results in biodiversity degradation manifested by losses of ecosystems and species, and therefore of associated ecosystem services. This study aims to examine the extent to which primary stakeholders in the conservation of the protected areas of Burundi perceive the different ecosystem services provided and assessing the use of the species of theses protected areas by the local population. Face to face interviews with protected area managers, representatives of the administration (at community and hill level) and local populations were carried out to capture stakeholders’perceptions of ecosystem services from Burundian protected areas. These data were subjected to the calculation of proportions for comparative analyses of the perceptions of the different categories of respondents according to the different ecosystem services. The results showed that all categories of respondents identified the existence of four types of ecosystem services (provisioning, regulating, supporting and socio-cultural) provided by Burundian protected areas, although the answers vary from category to category. The results of the assessment of the species use have highlighted that these categories of respondents also note the illicit use of both plant and animal species by local populations. Awareness-raising initiatives for all conservation stakeholders (especially surrounding populations) remain essential for the sustainability of these ecosystem services.
In this paper, we study the strong consistency of a bias reduced kernel density estimator and derive a strongly consistent Kullback-Leibler divergence (KLD) estimator. As application, we formulate a goodness-of-fit test and an asymptotically standard normal test for model selection. The Monte Carlo simulation show the effectiveness of the proposed estimation methods and statistical tests.
In this paper, we study a bias reduced kernel density estimator and derive a nonparametric \(\phi\)-divergence estimator based on this density estimator. We investigate the asymptotic properties of these two estimators and we formulate an asymptotically standard normal test for model selection.
Recently in [1,2], Ali-Akbar Bromideh introduced the Kullback-Leibler Divergence (KLD) test statistic in discriminating between two models. It was found that the Ratio Minimized Kulback-Leibler Divergence (RMKLD) works better than the Ratio of Maximized Likelihood (RML) for small sample size. The aim of this paper is to generalize the works of Ali-Akbar Bromideh by proposing a hypothesis testing based on Bregman divergence in order to improve the process of choice of the model. Our aproach differs from him. After observing n data points of unknown density f ; we firstly measure the closness between the bias reduced kernel density estimator and the first estimated candidate model. Secondly between the bias reduced kernel density estimator and the second estimated candidate model. In these two cases Bregman Divergence (BD) and the bias reduced kernel estimator [3] focuses on improving the convergence rates of kernel density estimators are used. Our testing procedure for model selection is thus based on the comparison of the value of model selection test statistic to critical values from a standard normal table. We establish the asymptotic properties of Bregman divergence estimator and approximations of the power functions are deduced. The multi-step MLE process will be used to estimate the parameters of the models. We explain the applicability of the BD by a real data set and by the data generating process (DGP). The Monte Carlo simulation and then the numerical analysis will be used to interpret the result.
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