ABSTRACT
Agroforestry parklands are an age-old traditional land use practice that integrates crop cultivation under scattered woody plants. This practice is widespread in West African savannas providing many essential ecological and socio-economic benefits to people such as food, fuelwood, and medicine. Currently, parklands are decreasing due to changes in agriculture and land use practices, often associated with human population growth. Understanding spatial patterns as well as identifying reliable methods of sampling to estimate the density of woody plants is necessary for the sustainable management of parklands. In this study, a comparative analysis of select plotless sampling methods was performed using field and simulated datasets with known spatial patterns from field assessments. Results of spatial indices tests indicated that woody plants in parklands exhibited two spatial patterns: i.e., aggregate and random, the latter being the dominant pattern observed in field datasets. Based on relative measure statistics (i.e., RRMSE and RBIAS), the ordered distance (OD), point-centered quarter (PCQ), and closest individual (CI) methods performed well when woody plants were located in a random pattern while the variable area transect (VAT) method was better at estimating density under patterns of spatial aggregation. Overall, OD and VAT methods are recommended for density estimation in parklands because they are relatively more accurate, less biased, and practical and computations are easy to undertake.
Subject(s)
Environmental Monitoring , Grassland , Humans , Agriculture , Plants , WoodABSTRACT
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.