Asian Journal of Environment & Ecology

A preliminary survey of bird species and habitat in the Karmajhiri Range, Pench Tiger Reserve was conducted during March 2014 - May 2014. The aim of this study was assessment of avian population by addressing some ecological status such as faunal type, phenological traits, trophic status, occurence and protection status of birds species. 221 species of birds were recorded from study area. Out of 26 order in India 16 order of birds were presented in and around Pench Tiger Reserve (PTR) which comprises 61 families. PTR provides habitat for three critically endangered species, namely White-rumped Vulture (Gyps bengalensis Gmelin, 1788), Red-headed Vulture (Sarcogyps calvus Scopoli, 1786) and Indian Vulture (Gyps indicus Scopoli, 1786). Regarding species protected by Berne convention 34 species are listed in Appendix 2 (strickly protected fauna) and only one are represented in Appendix 3 (Protected fauna) House Sparrow (Passer domesticus Linnaeus, 1758). Based on the AEWA (African-Europian Migratory Waterbird Agreement) bird list, 18 bird species are noted in the study area. The dominance of Oriental faunal type provide information on the relationship of the surveyed avifauna to the biogeographical zones. We were recorded 28 biome restricted bird species.  This assessment also supports and justifies its classification as an Important Bird Area “IBA” because of the importance and abundance of avian species. Its provide shelter and hosts to birds. To conserve birds species in tropical deciduous forest in PTR, it will be necessary to preserve large areas of contiguous forest and monitor the effect of Habitat fragmentation and other development activities in and around forest area will have impact on their foraging, breeding and subsequently their population. These scientific findings will help to evaluate the effectiveness of legislation and policies for bird protection and will under in future conservation action for birds and their habitats.

Aim: Agricultural production is directly affected by climate change. This means that access to climate information would help the farmers’ preparedness for farming activities and the decision on the types of crops to grow, when to grow them and the types of farm management activities to adopt. As such, this study analysed farmers’ preference for seasonal climate forecasts and their willingness-to-pay for these information.

Place and Duration: The study was conducted in the Savelugu Municipality in the Northern region of Ghana. A single period data was collected for analysis.

Methodology: A total of 300 farmers were selected through a two stage sampling procedure and used for the study. From the theory of contingent valuation, a descriptive statistic and Heckman model were used in analysing the data.

Results: From the results, the majority of farmers were willing-to-pay for seasonal climate information, especially, climate forecasts on rainfall. The farmers preferred that these seasonal climate forecasts should be disseminated to them through the radio. The farmers exhibit positive willingness-to-pay for seasonal climate forecasts to about 20 Ghana cedis. A number of factors influenced the farmers’ decision and amount they were willing-to-pay and these include gender, age, perception of climate change experience, ownership of radio, off-farm activity and participation in planting for food and jobs (PFFJ) program.

Conclusions: The findings of this study highlighted the need for climate information by farmers and how this can be effectively disseminated to them. Generally, government institutions and other private agencies should take up the challenge and opportunity to provide climate information, especially seasonal rainfall forecast, to the farmers at a fee.  This fee must be determined at an optimal or at least a breakeven price considering the farmer’s ability to pay. The study also recommended that climate information dissemination should be integrated into government’s PFFJ program.

Atmospheric pollution due to carbon dioxide emission from different fossil fuels and deforestations are considered as a great and important international challenge to the societies. This study is to investigate carbon dioxide (CO₂) distributions in selected points in Nigeria using neural network. Neural network model were used to estimate daily values of carbon dioxide, study spatial temporal variations of carbon dioxide, and study the annual variations of estimated and observed carbon dioxide in Nigeria. The study areas used in this work are thirty six (36) points location over Nigeria. The data used in this work is a satellite carbon dioxide () data were obtained from Global Monitoring for Environment and Security (GMES) under the programme of Monitoring Atmospheric Composition And Climate (MACC) www.gmes-atmosphere.eu/data between 2009-2014. The neural network architecture used comprises of three main layers; an input layer, a hidden layer and an output layer. Four input data were considered which include year, day of year (DOY) representing the time, latitude and longitude. Twenty hidden neurons were employed, while the output is the desired data of carbon dioxide. The results show that the increase in trend of CO₂ in dry season in every part of the country is on yearly bases. In the wet season, the concentration of CO₂ in Nigeria is not as much as in the dry season case, probably due to absorption of the gas by precipitation. The continuous annual increase of CO₂ distribution suggests continuous increase of the greenhouse gas in Nigeria. This reveals continuous contribution of CO₂ in Nigeria. The similarity in the estimated and observed signatures reveals that neural network model performance were excellent and efficient in determination of spatial distribution of CO₂, thereby proving to be useful tool in modeling the greenhouse gases. The results show that neural network model has the capacity of investigating greenhouse gases variations in Nigeria.

The study was conducted to assess the contribution of Odoba forest reserve to rural livelihoods of the communities in Ogbadibo Local Government Area of Benue State, Nigeria. Pre-tested semi-structured questionnaires were administered to three hundred and seventy-six respondents in 188 households in four communities. Data collected were analyzed using descriptive and inferential statistics. Fifteen different wood and non-wood products were collected by the respondents from the forest reserve with fuel wood products being the product mostly collected from the reserve (65.5%)  followed by water supply from the streams in the forest reserve  (59%). Others were edible vegetable (56.6%), folder (53.6%), mush room (53.3%), medicinal herbs (52.6%) and timber (50.3%), Bush Meat (46.7%), Chewing stick (43.0%), Pole (40.5%), Honey (37.8%), Snail (27%), Caterpillar (25%), Cricket (20.4%) and Climbers (19%). The result also shows that forest resources contributed very high to the livelihood of the people in the areas of food for household consumption, additional income, medicinal values, water supply and trading of forest products. Furthermore, the study results showed that the most need met by the people from the sale of forest products is feeding of households (19.4%) and investing in farming activities (13.8%). The communities differ significantly (P=0.05) in the contribution of the forest reserve to their livelihoods. The study recommends that State Government, local authorities and aid agencies should provide alternative sources of fuel energy by establishing village owned solar power plants and fuelwood efficient stoves. This will reduce dependence on the forest reserve for energy and also curtail deforestation of the reserve. Modified Taungya system in the reserve to engage households in forest regeneration efforts as well as the sharing of benefits from such efforts should be included in policies of the Government.

Accumulation of some heavy metals (Cu, Zn, Cd and Cr) was determined in selected fish; Moon fish (Citharinus citharus), Tilapia fish (Oreochronus niloticus), Mud fish (Clarias anguillaris), Cat fish (Clarias gariepinus) and Carp fish (Labeo coulbie) and water samples from Onuimo River in Imo State in Nigeria. Accumulation order of heavy metals in fish samples comprised of Moon fish > Cling fish > Mud fish > Tilapia fish > Cat fish. Bioconcentration factor model used in the present study showed the following order; Moon fish = Carp fish > Cat fish > Mud fish > Tilapia fish and Moon fish = Carp fish > Tilapia >Mud fish > Cat fish for copper and zinc metals respectively. The concentration of cadmium and chromium in water samples were below detection limits of the Atomic Absorption Spectrophotometer (AAS) Machine. Concentrations of Cu, Cd, Zn and Cr were also below permissible limits of some international regulatory bodies.