Large gaps remain in our understanding of the vulnerability of specific animal taxa and regions to climate change, especially regarding extreme climate impact events. Here, we assess African apes, flagship and highly important umbrella species for sympatric biodiversity. We estimated past (1981–2010) and future exposure to climate change impacts across 363 sites in Africa for RCP2.6 and RCP6.0 for near term (2021–2050) and long term (2071–2099). We used fully harmonized climate data and data on extreme climate impact events from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). Historic data show that 171 sites had positive temperature anomalies for at least nine of the past ten years with the strongest anomalies (up to 0.56°C) estimated for eastern chimpanzees. Climate projections suggest that temperatures will increase across all sites, while precipitation changes are more heterogeneous. We estimated a future increase in heavy precipitation events for 288 sites, and an increase in the number of consecutive dry days by up to 20 days per year (maximum increase estimated for eastern gorillas). All sites will be frequently exposed to wildfires and crop failures in the future, and the latter could impact apes indirectly through increased deforestation. 84% of sites are projected to be exposed to heatwaves and 78% of sites to river floods. Tropical cyclones and droughts were only projected for individual sites in western and central Africa. We further compiled available evidence on how climate change impacts could affect apes, for example, through heat stress and dehydration, a reduction in water sources and fruit trees, and reduced physiological performance, body condition, fertility, and survival. To support necessary research on the sensitivity and adaptability of African apes to climate change impacts, and the planning and implementation of conservation measures, we provide detailed results for each ape site on the open-access platform A.P.E.S. Wiki.

Models estimating tree volume from stump diameter are important forest-management tools when volume estimation is needed postharvest, and dbh values are unavailable, for example the incidence of timber trespass. However, the use of stump diameter as the only independent variable for predicting tree volume has been limited. Therefore, in this article, stump diameter was used to estimate stem volume of Tectona grandis Linn. f, and this was compared with volume estimated from diameter at breast height. Five functions were considered each for the two stem diameters: simple linear, semilogarithmic, zero-intercept, power, and growth. Model assessment was based on least values of the root mean square error and Akaike information criterion. The results showed that the growth model had the best overall performance for both sets of volume models. A paired-sample t-test was used to compare volume estimated by stump diameter and volume estimated by diameter at breast height at 5 percent significance level. The results showed that there were no significant differences (P = .087) between timber volumes estimated from both stem diameters. Therefore, both diameters can be used interchangeably for modeling tree volume.

Data and information are required to manage a renewable natural resource (such as forest) sustainably. This information is largely obtained through forest inventories. Forest inventory is very important in forest management since it provides the data for planning, monitoring, evaluation, research, growth and yield, biodiversity, and timber sale. Inadequate and/or irregular forest inventory has resulted to paucity of data on which forest management decisions can be based. This study aimed at enlightening conservationists, ecologists, environmentalists, and forest managers on the need to carryout diversity assessment and inventory of flora and fauna resources within their forest ecosystems. This will help to ensure sustainable yield and prevent the extinction of economic trees and endangered animal species in the tropical dry forests. The study therefore recommended that inventory should be carryout among the tropical dry forests at regular intervals.

Crown-Stump Diameter Model for Parkia biglobosa Benth. Species in Makurdi, Benue State, Nigeria

Illegal logging has continued to be a major cause of depletion of the tropical forests in developing countries. However, empirical means of estimating the growth characteristics of a removed tree, which will facilitate the conviction of illegal loggers in judicial proceedings, are lacking. This study aimed at developing a model that can predict individual tree slenderness coefficients (SC) from stump diameter (Ds) for Tectona grandis stands in Omo Forest Reserve, Nigeria, for timber valuation in case of illegal felling. Diameter at breast height (DBH; cm), Ds (cm) and total height Ht (m) were measured from all T. grandis stands with a DBH ≥ 5.0 cm, within 35 temporary sample plots (TSPs) randomly laid out in 6 age series (26, 23, 22, 16, 14 and 12 years). The least squares regression method was used to model tree SC from Ds. Six SC-Ds models were fitted and evaluated. The relationship was best described by the single logarithmic function which gave best-fit values for the adjusted coefficient of determination, the Furnival’s index and the standard error of the estimate. This study showed that tree SC estimations were possible even when the only information available was the Ds. The single logarithmic model was validated using independent data and was found to be suitable for estimating the SC of T. grandis stands in Omo Forest Reserve, south-western Nigeria. Future studies should consider developing models for predicting other tree growth variables from Ds.

Forests are important plant communities that consist of trees and other woody vegetation that performs life-supporting functions on Earth. This chapter presents the application concepts necessary to link remote sensing data and geographic information system to conservation, restoration, and sustainable management of tropical forests. Despite the rising global concern, there is still continuous destruction of tropical forests at an alarming rate. This chapter assessed various approaches for conservation, restoration, and sustainable management of tropical forests using remote sensed data and geographic information system. This involves their applications to biodiversity conservation, forest ecophysiology, forest trees' disease and insect interactions, forest mensuration, forest resources monitoring and evaluation, forest fires, land use and land cover dynamics, and vegetation cover.