Dry Mixed Forest Research Articles

Inventory of tiger- and ground-beetles (Coleoptera, Caraboidea, Cicindelidae and Carabidae) in two sampling seasons of the Gorongosa National Park, Mozambique.

The Gorongosa National Park (Mozambique) is one of the most emblematic protected areas in Africa, well known for its vertebrate biodiversity and restoration ecology efforts following the Mozambican civil war in 1992. The invertebrate biodiversity of Gorongosa National Park is still poorly studied, although the scarce information available indicates the existence of a rich number of species, namely in the case of tiger- and ground-beetles (Coleoptera, Caraboidea). Moreover, the study of arthropod assemblages is key for designing conservation practices since they are potentially accurate biodiversity and ecological indicators. Hence, the diversity assessment of Caraboidea beetles using standardised methodologies is likely to provide a new insight for future conservation planning and help to quantify the effects of climate change in areas identified as vulnerable to anthropogenic pressures, such as the Gorongosa National Park. We report the occurrence of five tiger beetles (Cicindelidae) and 93 ground-beetles (Carabidae) species/morphospecies in Gorongosa National Park from a field survey funded by the ECOASSESS project. Sampling was performed in the four main habitat types present in the Park (miombo tropical forest, mixed dry forest, transitional forest and grasslands) between 25 October and 25 November 2019. In this sampling window, the turnover of Caraboidea species from the dry season to the wet season was recorded for the first time. Twenty-eight species of ground-beetles are new records to Mozambique, including three new subgenera and three new genera. Additional information on species phenology and habitat preferences is also provided.

Camera trap data reveal the habitat associations, activity patterns and population density of Indian pangolin (Manis crassicaudata) in Maduru Oya National Park, Sri Lanka

The Indian pangolin (Manis crassicaudata) is a solitary, medium–sized mammal native to South Asia. In this study we used camera trap data recorded during a meso–mammal survey conducted from January 2019 to January 2021 to assess the occupancy, habitat associations, population density and activity patterns of Indian pangolins in Maduru Oya National Park (MONP), Sri Lanka. The preferred habitat of the species was dry–mixed forest with an occupancy probability of 0.42 ± 0.19. Occupancy modeling revealed the association of the species with the forested habitats of the park with rich canopy cover, high NDVI scores and abundant termite mounds. Activity of this pangolin was highly nocturnal, reaching a peak after midnight. We observed a considerable spatiotemporal overlap in Indian pangolin activity and human activity, possibly increasing hunting pressure on the species. We estimated occupancy and abundance–based population density (0.73 ± 0.21 indiv./km2) using the random encounter model for the first time in the study area. These findings could be useful for conservation and management decisions concerning the survival and vital habitats of one of the most trafficked mammals in the world, the Indian pangolin.

Modeling tree canopy height using machine learning over mixed vegetation landscapes

Although the random forest algorithm has been widely applied to remotely sensed data to predict characteristics of forests, such as tree canopy height, the effect of spatial non-stationarity in the modeling process is oftentimes neglected. Previous studies have proposed methods to address the spatial variance at local scales, but few have explored the spatial autocorrelation pattern of residuals in modeling tree canopy height or investigated the relationship between canopy height and model performance. By combining Light Detection and Ranging (LiDAR) and Landsat datasets, we used spatially-weighted geographical random forest (GRF) and traditional random forest (TRF) methods to predict tree canopy height in a mixed dry forest woodland in complex mountainous terrain. Comparisons between TRF and GRF models show that the latter can lower predefined extreme residuals, and thus make the model performance relatively stronger. Moreover, the relationship between model performance and degree of variation of true canopy height can vary considerably within different height quantiles. Both models are likely to present underestimates and overestimates when the corresponding tree canopy heights are high (>95% quantile) and low (<median), respectively. This study provides a critical insight into the relationship between tree canopy height and predictive abilities of random forest models when taking account of spatial non-stationarity. Conclusions indicate that a trade-off approach based on the actual need of project should be taken when selecting an optimal model integrating both local and global effects in modeling attributes such as canopy height from remotely sensed data.

Understanding the relationship between soil properties and litter chemistry in three forest communities in tropical forest ecosystem.

In this study, we investigated the relationship between soil properties and litter chemistry in three forest communities, i.e., Sal mixed forest (SMF), dry mixed forest (DMF), and teak plantation forest (TPF), in tropical deciduous forest ecosystem in North India. Fresh leaf litter and soil samples were collected at two soil depths (0-15 and 15-30 cm) from all these three forest communities. Litter bag experiment was also conducted to know differences in litter nutrients after its decomposition. The concentrations (mg kg-1) of different nutrients such as sodium (Na) 2.6, potassium (K) 38.5, calcium (Ca) 425, and carbon (C) 45.54% were highest in fresh litter collected from DMF. Total organic carbon (g kg-1) was significantly higher in SMF (19.23) in comparison to DMF (18.41) and TPF (13.61) at 0-15-cm soil depth. Na, K, Ca, available P, total P, available N, and total N were highest in DMF soil. We observed significantly positive correlation between all nutrients of litter and soil. Although soil bulk density (BD) and particle density (PD) showed their significant negative correlation with litter C, total porosity was positively correlated. Similarly, litter Na has its significant negative correlation with BD and positive correlation with PD. The litter chemistry played a significant role in changing soil pH and TOC. All litter nutrients, except total P, have their significant positive correlation with soil pH. Total P, C, and N of litter have their significant positive correlation with total soil organic carbon. This indicates that litter chemistry and soil properties have specific relation among them despite unique species composition in each forest community.

Carbon stocks in coffee agroforests and mixed dry tropical forests in the western highlands of Guatemala

Tree removal in Latin American coffee agroforestry systems has been widespread due to complex and interacting factors that include fluctuat- ing international markets, government-supported agri- cultural policies, and climate change. Despite shade tree removal and land conversion risks, there is currently no widespread policy incentive encouraging the maintenance of shade trees for the benefit of carbon sequestration. In facilitation of such incentives, an understanding of the capacity of coffee agroforests to store carbon relative to tropical forests must be developed. Drawing on ecological inventories con- ducted in 2007 and 2010 in the Lake Atitlan region of Guatemala, this research examines the carbon pools of smallholder coffee agroforests (CAFs) as they com- pare to a mixed dry forest (MDF) system. Data from 61 plots, covering a total area of 2.24 ha, was used to assess the aboveground, coarse root, and soil carbon reservoirs of the two land-use systems. Results of this research demonstrate the total carbon stocks of CAFs to range from 74.0 to 259.0 Megagrams (Mg) C ha -1 with a mean of 127.6 ± 6.6 (SE) Mg C ha -1 . The average carbon stocks of CAFs was significantly lower than estimated for the MDF (198.7 ± 32.1 Mg C ha -1 ); however, individual tree and soil pools were not significantly different suggesting that agro- forest shade trees play an important role in facilitating carbon sequestration and soil conservation. This research demonstrates the need for conservation-based initiatives which recognize the carbon sequestration benefits of coffee agroforests alongside natural forest systems.

The Forgotten ‘Coastal Forests’ of Mtwara, Tanzania: A Biologically Impoverished and Yet Important Ecosystem

ABSTRACT Biodiversity surveys and the compilation of indigenous knowledge were conducted in eight previously unstudied proposed and already gazetted Forest Reserves of Mtwara Region, south-eastern Tanzania, from April to August of 2005. The results indicate relatively low biodiversity and endemism values in these forests, and high levels of forest disturbance. In most areas the original vegetation has been converted by clearance for cultivation and by fire, and has regenerated into degraded forms of Swahilian/Coastal Mixed Dry Forest, Swahilian/Coastal Brachystegia Forest and floristically impoverished Zambezian-Swahilian Brachystegia Woodland. Some Coastal Forest endemic and threatened species, however, occur in the degraded forest patches, such as east coast akalat Sheppardia gunningi, Reichenow's batis Batis mixta reichenowi, spotted flat-lizard Platysaurus maculatus, woodland toad Mertensophryne micranotis and the shrub Gardenia transvenulosa. The low proportion of endemic and threatened species recor...

Development of equations for predicting Puerto Rican subtropical dry forest biomass and volume

Carbon accounting, forest health monitoring and sustainable management of the subtropical dry forests of Puerto Rico and other Caribbean Islands require an accurate assessment of forest aboveground biomass (AGB) and stem volume. One means of improving assessment accuracy is the development of predictive equations derived from locally collected data. Forest inventory and analysis (FIA) measured tree diameter and height, and then destructively sampled 30 trees from 6 species at an upland deciduous dry forest site near Ponce, Puerto Rico. This data was used to develop best parsimonious equations fit with ordinary least squares procedures and additive models fit with nonlinear seemingly unrelated regressions that estimate subtropical dry forest leaf, woody, and total AGB for Bucida buceras and mixed dry forest species. We also fit equations for estimating inside and outside bark total and merchantable stem volume using both diameter at breast height (d.b.h.) and total height, and diameter at breast height alone for B. buceras and Bursera simaruba. Model fits for total and woody biomass were generally good, while leaf biomass showed more variation, possibly due to seasonal leaf loss at the time of sampling. While the distribution of total AGB into components appeared to remain relatively constant across diameter classes, AGB variability increased and B. simaruba and B. buceras allocated more carbon into branch biomass than the other species. When comparing our observed and predicted values to other published dry forest AGB equations, the equation developed in Mexico and recommended for areas with rainfall >900 mm/year gave estimates substantially lower than our observed values, while equations developed using dry forest data from forest in Australia, India and Mexico were lower than our observed values for trees with d.b.h. <25 cm and slightly higher for trees with d.b.h. >30 cm. Although our ability to accurately estimate merchantable stem volume and live tree AGB for subtropical dry forests in Puerto Rico and other Caribbean islands has been improved, much work remains to be done to sample a wider range of species and tree sizes.

Conservation evaluation for birds of Brachylaena woodland and mixed dry forest in north-east Tanzania

Three forest and woodland sites were surveyed in the lowlands of the East Usambara mountains, Tanzania, from August to October, 1996. Bombo East I and II Proposed Forest Reserves (PFR) and Bombo West FR were previously unknown biologically. Our fieldwork revealed several records of conservation interest. Four species of global conservation concern (Amani Sunbird Anthreptes pallidigaster, Southern Banded Snake Eagle Circaetus fasciolatus, Fischer's Turaco Tauraco fischeri and Plain-backed Sunbird Anthreptes reichenowi) were recorded, with a further seven species of regional concern. These sites were not as rich in bird species as other East Usambara lowland forests. Bombo East I PFR had the highest richness, which included the presence of three montane species that were most likely cold-season visitors. The Endangered Sokoke Scops Owl Otus ireneae, otherwise known from similar woodland habitat in Kenya as well as lowland forest in the East Usambaras, was apparently absent at these sites. It is also clear from our survey that at least four threatened mammals and one possibly endemic snake inhabit the Brachylaena woodlands and mixed dry forest. Thus, our results indicate that the previously unexplored Brachylaena woodlands and mixed dry forest in north-east Tanzania are an additional habitat to some fauna of threatened status and do, therefore, merit conservation attention. The Brachylaena tree is highly favoured for charcoal production and the enormous demand for this product is increasing the degradation of these woodland patches. Larger tracts of unprotected Brachylaena woodland should receive immediate conservation attention.

APPLICATION OF REMOTE SENSING TO STUDY THE ENVIRONMENT AND ECOSYSTEM. A CASE STUDY FOR PRIMARY ANALYSIS OF VEGETATION

Four major types of forest vegetation viz, moist sal forest, moist mixed forest, dry mixed forest and. seral vegetation were identified at the Kanha National Park using remote sensing data products viz., satellite imageries (Landsat - TM-FCC 1:50,000 scale) and aerial photographs (B/W panchromatic 1:10,000 scale). Primary analysis of the vegetation has revealed that sal (Shorea robusta) was more abundant (60.13) with highest importance value index (IVI) of 180.11 followed by Terminalia tomentosa in moist sal group of forests in valleys. T.tomentosa was found to be a close associate of sal. In moist miked forests (on hill slopes), I. tomentosa were abundant with high frequency, density and highest IVI (94.88). Total absence of sal and less abundance of 1, tomentosa were the significant aspects in characterizing the dry mixed forest. In dry mixed forest, Bosewellia serrata and Lagerstroemia parviflora are the most abundant species constituting the ridge vegetation. The seral vegetation was dominated by Butea monosperma and L. parviflora which were invading the grasslands in pure patches, respectively, into meadows and dadar grasslands.

APPLICATION OF REMOTE SENSING TO STUDY THE ENVIRONMENT AND ECOSYSTEM. A CASE STUDY FOR SECONDARY ANALYSIS OF VEGETATION

Four types of vegetation viz. moist sal forest, moist mixed forest, dry mixed forest and seral vegetation were identified at the Kanha National Park using remote sensing data products viz. satellite imageries (Landsat -TM-FCC 1:50,000 scale) and aerial photographs (B/W Panchromatic 1:10,000 scale). Secondary analysis of the vegetation interms of index of similarity has revealed that there was highest similarity between Terminalia tomentosa and moist mixed forest as T. tomentosa was the most abundant and dominant tree species in moist mixed forest. Also there were more similarity between Sal (Shorea robusta) and T. tomentosa forests. S. robusta forest was the most dominant among all the vegetation in the study area. The dry mixed and moist mixed forests were having greater diversity, indicating the richness of the tree species, compared to sal forest and seral vegetation

APPLICATION OF REMOTE SENSING TO STUDY ENVIRONMENT AND ECOSYSTEM. A CASE STUDY OF FOREST VEGETATION USING DIGITAL ANALYSIS

Seven types of vegetations viz., sal forest, sal mixed forest, moist mixed forest, dry mixed forest, seral vegetation, high grass and low grass, were identified and delineated by visual interpretation of satellite data (Landsat TM-FCC 1:50,000 scale). However, there was difficulty in delineating agricultural/fallow lands by visual interpretation. But in computer aided digital analysis, in addition to all the seven vegetations identified through visual interpretation, agricultural fallow lands were identified and demarcated in view of better separability of tonal variations. Comparison of visual interpretation and digital analysis methods revealed that there was no significant difference between these two methods of analysis as far as total areal extent of the study area was concerned. However, there were differences between the two methods of analysis regarding the areal extent of different vegetation/forest types identified within the study area. If situations warrants use of single band data for vegetation studies, we can use band 5 data of Landsat TM as it was able to give better spectral separability among different vegetations.