How effective are on-farm conservation land management strategies for preserving ecosystem services in developing countries? A systematic map protocol

Background An extensive body of literature in the field of agro-ecology claims to show the positive effects that maintenance of ecosystem services can have on sustainably meeting future food demand, by making farms more productive and resilient, and contributing to better nutrition and livelihoods of farmers. In Africa alone, some research has estimated a two-fold yield increase if food producers capitalize on new and existing knowledge from science and technology. Site-specific strategies adopted with the aim of improving ecosystem services may incorporate principles of multifunctional agriculture, sustainable intensification and conservation agriculture. However, a coherent synthesis and review of the evidence of these claims is largely absent, and the quality of much of this literature is questionable. Moreover, inconsistent effects have commonly been reported, while empirical evidence to support assumed improvements is largely lacking. Objectives This systematic map is stimulated by an interest to (1) collate evidence on the effectiveness of on-farm conservation land management for preserving and enhancing ecosystem services in agricultural landscapes, by drawing together the currently fragmented and multidisciplinary literature base, and (2) geographically map what indicators have been used to assess on-farm conservation land management. For both questions, we will focus on 74 low-income and developing countries, where much of the world’s agricultural expansion is occurring, yet 80% of arable land is already used and croplands are yielding well below their potential. Methods/Design To this end, reviewers will systematically search bibliographic databases for peer-reviewed research from Web of Science, SCOPUS, AGRICOLA, AGRIS databases and CAB abstracts, and grey literature from Google Scholar, and 22 subject-specific or institutional websites. Boolean search operators will be used to create search strings where applicable. Ecosystem services included in the study are pollination services; pest-, carbon-, soil-, and water-regulation; nutrient cycling; medicinal and aromatic plants; fuel wood and cultural services. Outputs of the systematic map will include a database, technical report and an online interactive map, searchable by topic. The results of this map are expected to provide clarity about synergistic outcomes of conservation land management, which will help support local decision-making

Assessment of regional best‐fit probability density function of annual maximum rainfall using CFSR precipitation data

The upper Cross River basin (UCRB) fits a true description of a data scarce watershed in respect of climatic data. This paper seeks to determine the best‐fit probability density function (PDF) of annual maximum rainfall for the UCRB using the Climate Forecast System Reanalysis (CFSR) precipitation data. Also, to evaluate the performance of the Intergovernmental Panel on Climate Change (IPCC) Coupled Model Inter‐comparison Project (CMIP3) Fourth Assessment Report (AR4) Global Circulation Models (GCMs) in simulating the monthly precipitation in the UCRB considering 1979–2014 data. For the determination of the best‐fit PDF, the models under review included the generalized extreme value (GEV), normal, gamma, Weibull and log‐normal (LN) distributions. Twenty‐four weather station datasets were obtained and subjected to frequency distribution analysis on per station basis, and subsequently fitted to the respective PDFs. Also, simulated monthly precipitation data obtained from 16 AR4 GCMs, for weather station p6191, were subjected to frequency distribution analysis. The results showed the percentages of best‐fit to worst‐fit PDFs, considering the total number of stations, as follows: 54.17%, 45.83%, 37.50%, 45.83%, and 50%/50%. These percentages corresponded to GEV, Weibull, gamma, gamma, and LN/normal, respectively. The comparison of the predicted and observed values using the Chi‐square goodness‐of‐fit test revealed that the GEV PDF is the best‐fit model for the UCRB. The correlation coefficient values further corroborated the correctness of the test. The PDF of the observed data (weather station p6191) and the simulations of the 16 GCMs computed using monthly rainfall datasets were compared using a mean square error (MSE) dependent skill score. The result from this study suggested that the CGCM3.1 (T47) and MRI‐CGCM2.3.2 provide the best representations of precipitation, considering about 36 years trend for station p6191. The results have no influence on how well the models perform in other geographical locations

Kernel-based robust tracking for objects undergoing occlusion

Visual tracking has been a challenging problem in computer vision over the decades. The applications of Visual Tracking are far-reaching, ranging from surveillance and monitoring to smart rooms. Occlusion is one of the major challenges that needs to be handled in tracking. In this work, we propose a new method to track objects undergoing occlusion using both sum-of-squared differences (SSD) and color-based mean-shift (MS) trackers which complement each other by overcoming their respective disadvantages. The rapid model change in SSD tracker is overcome by the MS tracker module, while the inability of MS tracker to handle large displacements is circumvented by the SSD module. Mean-shift tracker, which gained more attention recently, is known for tracking objects in a cluttered environment. Since the MS tracker relies on the global object parameters such as color, the performance of the tracker degrades when the object undergoes partial occlusion. To avoid the adverse effect of this global model, we use the MS tracker so as to track the local object properties instead of a global one. Further a likelihood ratio weighting is used for SSD tracker to avoid drift during partial occlusion and to update the MS tracking modules. The proposed tracker outperforms the traditional MS tracker, as illustrated in the instances applied