This study investigated the effects of climatic variables, particularly, rainfall and temperature, on malaria incidence using time series analysis. Our preliminary analysis revealed that malaria incidence in the study area decreased at about 0.35% annually. Also, the month of November recorded approximately 21% more malaria cases than the other months while September had a decreased effect of about 14%. The forecast model developed for this investigation indicated that mean minimum (P = 0.01928) and maximum (P = 0.00321) monthly temperatures lagged at three months were significant predictors of malaria incidence while rainfall was not. Diagnostic tests using Ljung-Box and ARCH-LM tests revealed that the model developed was adequate for forecasting. Forecast values for 2016 to 2020 generated by our model suggest a possible future decline in malaria incidence. This goes to suggest that intervention strategies put in place by some nongovernmental and governmental agencies to combat the disease are effective and thus should be encouraged and routinely monitored to yield more desirable outcomes.

Abstract:Ectoparasites are an important factor in bat health due to emergent diseases and their associated threats to global public health. The diverse foraging habits of bats expose them to different surfaces which may influence ectoparasite infestations. In spite of these, most studies often overlook dietary specialisations when observing ectoparasite loads. The present paper quantitatively investigates whether foraging strategies as well as other host characteristics (sex, age, trunk and patagial area) influence ectoparasite (nycteribiids and mites) loads of bats. Ectoparasite counts and morphometric data were taken from mist net captures of bats. We then developed and compared models for modeling bat ectoparasite abundance under various distributions using generalised linear models. The negative binomial distribution consistently proved to be adequate for modeling mite, nycteribiid and total ectoparasite abundance based on information-theoretic approaches. Generally, females and frugivores had higher ectoparasite loads conditional on bat sex and diet, respectively. Contrary to nycteribiid abundance, mite abundance was positively related to patagial area. Thus, our findings suggest that dietary guild, sex and patagia of hosts (as well as age-nycteribiid abundance) are significant determinants of ectoparasite abundance.

Article history Tenure systems Land management Traditional areas Tree chiefs Ghana KeywordsParkia biglobosa is a multipurpose species found in Savannah agroforestry parklands of West Africa. The species is important as it prevents against land degradation while providing food and other products. This study focuses on how land and tree tenure arrangements affect tree populations in three traditional areas in the Northern Region of Ghana (Dagomba, Gonja and Mamprusi) and the implications that these arrangements have for sustainable land management. Focus group discussions and key informant interviews were held in the three communities to provide information on the tenural arrangements of Parkia biglobosa. A tree census was conducted to estimate the densities of Parkia biglobosa in crop and fallow fields. The study shows that differences in tenure systems in the three traditional areas have implications for Parkia biglobosa populations and also for sustainable land management. It is concluded that traditional tenure systems along with regulation protect the trees from destruction as observed in the Dagomba and Gonja areas compared to the open access system identified in Kperiga in the Mamprusi area.

IntroductionInsectivorous bats constitute about 70% of all bats and are characterized by generally using echolocation to detect prey items (Simmons and Conway, 2003). Nearly all insectfeeding bats are nocturnal (Speakman, 1995), occupy a diversity of habitat types, and exploit a wide variety of prey (Altringham, 1996;Kalko et al., 1996). Some authors have suggested that insect prey abundance influences the local occurrence of insectivorous bats (Rautenbach et al., 1996;Pavey et al., 2001). In other words, changes in the activity level of insects may influence the foraging behavior and activity levels of the bats. Hence, insectivorous bats time their foraging flight patterns to coincide with maximum nocturnal activity of their prey.Abiotic factors such as light, temperature (Russ et al., 2003;Barros et al., 2014), and wind speed (Russo and Jones, 2003;Johnson et al., 2011) exhibit high diurnal fluctuations and are thus likely to influence predator (bats) and prey (insects) activities directly or indirectly. The activity patterns of many nocturnal animals comprise trade-offs between prey availability and predation risk, which are likely to be modulated by light conditions in connection with the lunar cycle. Some studies have shown that moonlight decreases nocturnal activity in animals, including birds (Nelson, 1989), insects (Williams et al., 1956), and rodents (Clarke, 1983). This reduction in activity during periods of high lunar illumination is assumed to hold true for many other bat species (Erkert, 1974(Erkert, , 1978. In addition, Saldaña-Vásquez and Munguía-Rosas (2013) reported that the negative effect of moonlight on tropical bats is higher than on temperate species.According to Findley (1993) and Humphrey (1975), areas that offer a variety of trees and roosts often support the largest numbers of bat species and individuals. In recent years, croplands, plantations, and pastures have significantly expanded globally (Foley et al., 2005). Transformations of land-use types (e.g., forests) via anthropogenic activities are the major drivers behind species loss regionally and globally, through habitat destruction and modification. One such driver that occurs on a global scale is agricultural intensification. This system of farming, which is characterized by high tillage operations, synthetic fertilizers, and pesticide (i.e. agrochemicals) use, is accompanied by loss of

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Logging and mining are widespread in most West African countries and considering their socio-economic importance, little is known about their ecological impacts. In this study, we investigated the effects of chainsaw milling (logging) and artisanal mining on terrestrial small mammal communities in a tropical forest in Ghana. For this, we compared abundance, diversity measures and community composition of small mammals active at the forest floor in logged, mined and undisturbed forest sites. We found that abundance was higher in logged and undisturbed forest sites than in mined sites. Small mammal species richness, Shannon diversity and Pielou’s evenness did not differ significantly among the three forest disturbance categories. Community composition of small mammals varied between mined and undisturbed sites as well as between mined and logged sites, suggesting differential species responses to altered environments. This may be due to the presence of pits in mined forest sites, hence a reduction in exploitable ground habitat structures for shelter, nesting or food. Overall, our results suggest that artisanal mining has strong impacts on community composition of forest floor small mammals in tropical forests while the effect of logging by chainsaw milling activities is minimal, especially when practiced at low intensity. This effect was moderated by elevation and distance to streams that equally shaped small mammal communities. More research on the effects of specific forms of logging and mining activities on small mammals are urgently needed to better protect species in forests impacted by logging and mining.

Forecasting plays an essential role in policy formulation and implementation especially in the management of fisheries resources. In this paper, various techniques of forecasting using time series analysis were evaluated on annual fishery production data. In addition to the Box-Jenkins approach, other methods such as the feed forward neural network and exponential smoothing approaches were also examined. A parsimonious model for each forecasting approach was then selected using penalized likelihoods. The chosen models were then evaluated based on their ability to produce accurate forecasts. Implications of the findings as discussed revealed that no particular method was ideal for modeling all landings. Hence when forecasting fishery landings, it is recommended that different structural approaches be compared before selecting an appropriate one for use.

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