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Modelling the impacts of anthropogenic activities on forest biomass and dependent wildlife population

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The depletion of forest biomass and declining of forest-dependent wildlife populations are ur gent ecological and societal issues resulting from human activities such as deforestation and land-use changes. This study aims to comprehend the influence of anthropogenic activities on forest biomass and the population of wildlife dependent on forests, and to formulate appropri ate management measures. Specific objectives include forecasting forest land loss in Tanzania, analysing mathematical model describing the impact of human activities on forests and wildlife, examining the influence of fuzzy parameters on model dynamics, and evaluating the effects of economic measures and technological efforts on conservation. The study considered Tanzania where local communities heavily rely on forest resources for their livelihoods. This region also supports a rich biodiversity of wildlife species, where the forest provides essential habitats and resources for their survival. Furthermore, the study also acknowledged the existence of vari ous human activities carried out in the area which may have a significant impact on the forest ecosystem and the wildlife populations that depend on it. Four models are presented: a time series model and three dynamical system models. The key findings include: (i) The univariate time series model accurately predicts an increase in forest land loss in Tanzania with a 96.2% accuracy rate (MAPE = 0.0377), highlighting the urgency for sustainable forest management practices and conservation policies. (ii) Depletion of forest biomass due to human activities has severe implications for wildlife survival and ecological balance. Achieving this balance re quires ensuring the growth rate of forest biomass and wildlife populations exceeds their rates of utilisation and depletion, respectively. (iii) Incorporating fuzzy parameters improves model re liability by accounting for uncertainties in climate, geography, and human activities, enhancing decision-making processes. (iv) Economic measures and technological efforts have the po tential to conserve forest biomass and wildlife populations. However, careful implementation and comprehensive understanding of forest ecosystem dynamics are crucial to prevent desta bilisation. The study emphasises the need for interdisciplinary collaboration and stakeholders engagement to ensure sustainable forest use and conservation, considering the complexities and uncertainties of natural systems. Balancing forest conservation with socio-economic needs is key for the well-being of local communities and future generations.
The Nelson Mandela African Institution of Science and Technology
Title: Modelling the impacts of anthropogenic activities on forest biomass and dependent wildlife population
Description:
The depletion of forest biomass and declining of forest-dependent wildlife populations are ur gent ecological and societal issues resulting from human activities such as deforestation and land-use changes.
This study aims to comprehend the influence of anthropogenic activities on forest biomass and the population of wildlife dependent on forests, and to formulate appropri ate management measures.
Specific objectives include forecasting forest land loss in Tanzania, analysing mathematical model describing the impact of human activities on forests and wildlife, examining the influence of fuzzy parameters on model dynamics, and evaluating the effects of economic measures and technological efforts on conservation.
The study considered Tanzania where local communities heavily rely on forest resources for their livelihoods.
This region also supports a rich biodiversity of wildlife species, where the forest provides essential habitats and resources for their survival.
Furthermore, the study also acknowledged the existence of vari ous human activities carried out in the area which may have a significant impact on the forest ecosystem and the wildlife populations that depend on it.
Four models are presented: a time series model and three dynamical system models.
The key findings include: (i) The univariate time series model accurately predicts an increase in forest land loss in Tanzania with a 96.
2% accuracy rate (MAPE = 0.
0377), highlighting the urgency for sustainable forest management practices and conservation policies.
(ii) Depletion of forest biomass due to human activities has severe implications for wildlife survival and ecological balance.
Achieving this balance re quires ensuring the growth rate of forest biomass and wildlife populations exceeds their rates of utilisation and depletion, respectively.
(iii) Incorporating fuzzy parameters improves model re liability by accounting for uncertainties in climate, geography, and human activities, enhancing decision-making processes.
(iv) Economic measures and technological efforts have the po tential to conserve forest biomass and wildlife populations.
However, careful implementation and comprehensive understanding of forest ecosystem dynamics are crucial to prevent desta bilisation.
The study emphasises the need for interdisciplinary collaboration and stakeholders engagement to ensure sustainable forest use and conservation, considering the complexities and uncertainties of natural systems.
Balancing forest conservation with socio-economic needs is key for the well-being of local communities and future generations.

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