Modified Whittaker plots as an assessment and monitoring tool for vegetation in a lowland tropical rainforest

Resource exploitation in lowland tropical forests is increasingand causing loss of biodiversity. Effective evaluation and management of the impacts of development on tropical forests requires appropriate assessment and monitoring tools. We proposethe use of 0.1-ha multi-scale, modified Whittaker plots (MWPs) to assess and monitor vegetation in lowland tropical rainforests.We established MWPs at 4 sites to: (1) describe and comparecomposition and structure of the sites using MWPs, (2) compare these results to those of 1-ha permanent vegetation plots (BDPs),and (3) evaluate the ability of MWPs to detect changes in populations (statistical power). We recorded more than 400 species at each site. Species composition among the sites was distinctive, while mean abundance and basal area was similar. Comparisons between MWPs and BDPs show that they record similarspecies composition and abundance and that both perform equallywell at detecting rare species. However, MWPs tend to record morespecies, and power analysis studies show that MWPs were more effective at detecting changes in the mean number of species of trees 10 cm in diameter at breast height (dbh) and in herbaceous plants. Ten MWPs were sufficient to detect a change of 11% in the mean number of herb species, and they were able to detect a 14% change in the mean number of species of trees 10 cm dbh. The value of MWPs for assessment and monitoringis discussed, along with recommendations for improving the sampling design to increase power.     

Large-scale carbon stock assessment of woody vegetation in tropical dry deciduous forest of Sathanur reserve forest,Eastern Ghats,India

Tropical dry forests are one of the most widely distributed ecosystems in tropics, which remain neglected in research, especially in the Eastern Ghats. Therefore, the present study was aimed to quantify the carbon storage in woody vegetation (trees and lianas) on large scale (30, 1 ha plots) in the dry deciduous forest of Sathanur reserve forest of Eastern Ghats. Biomass of adult (≥10 cm DBH) trees was estimated by species-specific allometric equations using diameter and wood density of species whereas in juvenile tree population and lianas, their respective general allometric equations were used to estimate the biomass. The fractional value 0.4453 was used to convert dry biomass into carbon in woody vegetation of tropical dry forest. The mean aboveground biomass value of juvenile tree population was 1.86 Mg/ha. The aboveground biomass of adult trees ranged from 64.81 to 624.96 Mg/ha with a mean of 245.90 Mg/ha. The mean aboveground biomass value of lianas was 7.98 Mg/ha. The total biomass of woody vegetation (adult trees + juvenile population of trees + lianas) ranged from 85.02 to 723.46 Mg/ha, with a mean value of 295.04 Mg/ha. Total carbon accumulated in woody vegetation in tropical dry deciduous forest ranged from 37.86 to 322.16 Mg/ha with a mean value of 131.38 Mg/ha. Adult trees accumulated 94.81% of woody biomass carbon followed by lianas (3.99%) and juvenile population of trees (1.20%). Albizia amara has the greatest biomass and carbon stock (58.31%) among trees except for two plots (24 and 25) where Chloroxylon swietenia contributed more to biomass and carbon stock. Similarly, Albizia amara (52.4%) showed greater carbon storage in juvenile population of trees followed by Chloroxylon swietenia (21.9%). Pterolobium hexapetalum (38.86%) showed a greater accumulation of carbon in liana species followed by Combretum albidum (33.04%). Even though, all the study plots are located within 10 km radius, they show a significant spatial variation among them in terms of biomass and carbon stocks which could be attributed to variation in anthropogenic pressures among the plots as well as to changes in tree density across landscapes. Total basal area of woody vegetation showed a significant positive (R ² = 0.978; P = 0.000) relationship with carbon storage while juvenile tree basal area showed the negative relationship (R ² = 0.4804; P = 0.000) with woody carbon storage. The present study generates a large-scale baseline data of dry deciduous forest carbon stock, which would facilitate carbon stock assessment at a national level as well as to understand its contribution on a global scale.     

Ethnobotanical Study of Fuelwood and Timber Wood Consumption and Replenishment in Ogbomoso, Oyo State, Nigeria

A survey of both urban and rural communities in five Local Government Areas (LGA) of Oyo State in Nigeria showed that 76% of households depend on fuelwood for cooking. The total annual wood consumption for fuelling by bread bakers, food sellers and in domestic cooking was 5984 metric tons for the region. The sawmills in the study area also convert 79 889 metric tons of wood yearly into boards of different grades. Total wood consumption outstrips the quantity of wood extracted from the forests. The balance of over 60 000 metric tons of wood is sourced from neighbouring forest locations. The quantity of wood harvested for various purposes did not show a significant difference (p < 0.05) among the five LGAs. However, a significant difference at p > 0.05 existed in the quantity of wood actually consumed in the various LGAs. Moreover. the number of trees cut down outstrips the number of trees planted with a significant difference (p > 0.05) between the mean quantity of wood removed from the forests and the mean quantity replaced by reforestation. The practice in the study area was that of 'cut-eight-plant-one' which is at variance to the much publicized operation 'cut-one-plant-one'. The study concludes that residents of Ogbomoso in Nigeria have not shown positive disposition to tree planting. It therefore suggests scientific tree conservation strategies aimed at improved burning of fuel wood and maximized use of timber products as complementary efforts to enforced tree planting for conservation of our forests.     

Use of forest inventories and geographic information systems to estimate biomass density of tropical forests: Application to tropical Africa

One of the most important databases needed for estimating emissions of carbon dioxide resulting from changes in the cover, use, and management of tropical forests is the total quantity of biomass per unit area, referred to as biomass density. Forest inventories have been shown to be valuable sources of data for estimating biomass density, but inventories for the tropics are few in number and their quality is poor. This lack of reliable data has been overcome by use of a promising approach that produces geographically referenced estimates by modeling in a geographic information system (GIS). This approach has been used to produce geographically referenced, spatial distributions of potential and actual (circa 1980) aboveground biomass density of all forests types in tropical Africa. Potential and actual biomass density estimates ranged from 33 to 412 Mg ha^–1 (10⁶g ha^–1) and 20 to 299 Mg ha^–1, respectively, for very dry lowland to moist lowland forests and from 78 to 197 Mg ha^–1 and 37 to 105 Mg ha^–1, respectively, for montane-seasonal to montane-moist forests. Of the 37 countries included in this study, more than half (51%) contained forests that had less than 60% of their potential biomass. Actual biomass density for forest vegetation was lowest in Botswana, Niger, Somalia, and Zimbabwe (about 10 to 15 Mg ha^–1). Highest estimates for actual biomass density were found in Congo, Equatorial Guinea, Gabon, and Liberia (305 to 344 Mg ha^–1). Results from this research effort can contribute to reducing uncertainty in the inventory of country-level emission by providing consistent estimates of biomass density at subnational scales that can be used with other similarly scaled databases on change in land cover and use.     

An assessment of the optimal scale for monitoring of MODIS and FIA NPP across the eastern USA

Robust monitoring of carbon sequestration by forests requires the use of multiple data sources analyzed at a common scale. To that end, model-based Moderate Resolution Imaging Spectroradiometer (MODIS) and field-based Forest Inventory and Analysis (FIA) data of net primary productivity (NPP) were compared at increasing levels of spatial aggregation across the eastern USA. A total of 52,167 FIA plots and colocated MODIS forest cover NPP pixels were analyzed using a hexagonal tiling system. A protocol was developed to assess the optimal scale as an optimal size of landscape patches at which to map spatially explicit estimates of MODIS and FIA NPP. The optimal mapping resolution (hereafter referred to as optimal scale) is determined using spatially scaled z-statistics as the tradeoff between increased spatial agreement as measured by Pearson’s correlation coefficient and decreased details of coverage as measured by the number of hexagons. Spatial sensitivity was also assessed using land cover assessment and forest homogeneity using spatially scaled z-statistics. Pearson correlations indicate that MODIS and FIA NPP are most highly correlated when using large hexagons, while z-statistics indicate an optimal scale at an intermediate hexagon size of 390 km². This optimal scale had more spatial detail than was obtained for larger hexagons and greater spatial agreement than was obtained for smaller hexagons. The z-statistics for land cover assessment and forest homogeneity also indicated an optimal scale of 390 km².     

Sampling The Soil In Long-Term Forest Plots: The Implications Of Spatial Variation

Long-term monitoring of forest soils as part of a pan-European network to detect environmental change depends on an accurate determination of the mean of the soil properties at each monitoring event. Forest soil is known to be very variable spatially, however. A study was undertaken to explore and quantify this variability at three forest monitoring plots in Britain. Detailed soil sampling was carried out, and the data from the chemical analyses were analysed by classical statistics and geostatistics. An analysis of variance showed that there were no consistent effects from the sample sites in relation to the position of the trees. The variogram analysis showed that there was spatial dependence at each site for several variables and some varied in an apparently periodic way. An optimal sampling analysis based on the multivariate variogram for each site suggested that a bulked sample from 36 cores would reduce error to an acceptable level. Future sampling should be designed so that it neither targets nor avoids trees and disturbed ground. This can be achieved best by using a stratified random sampling design.     

Double sampling for stratification for the monitoring of sparse tree populations: the example of Populus euphratica Oliv. forests at the lower reaches of Tarim River, Southern Xinjiang, China

Desertification is a pressing issue in the dry Tarim River basin, which is under anthropogenic stresses. In this study, double sampling for stratification (DSS) is employed to inventory Populus euphratica Oliv. forests in the lower reaches of the Tarim River Basin in Xinjiang, China. The two objectives were evaluating DSS as a sampling technique for monitoring desertification and generating baseline information for permanent observation. Here, DSS consists of two phases: in phase 1, crown cover is observed on a large sample of plots on a high resolution satellite image, and these photo-plots are stratified into five crown cover strata. Phase 2 is a stratified random sample from these photo-plots and the sampled plots are field observed. Approximately 32% of the study area is without P. euphratica trees. As expected, estimated mean poplar tree density and basal area increase with crown cover. DSS takes advantages of stratification (fieldwork efficiency and statistical precision) without the need for a priori strata delineation. It proves feasible for inventory the sparse poplar population and holds promise for the assessment of trees outside the forest, where density varies considerably and pre-stratification is intractable. It can be integrated into permanent observation systems for monitoring vegetation changes.     

Systematic monitoring of heathy woodlands in a Mediterranean climate—a practical assessment of methods

Practical and useful vegetation monitoring methods are needed, and data compatibility and validation of remotely sensed data are desirable. Methods have not been adequately tested for heathy woodlands. We tested the feasibility of detecting species composition shifts in remnant woodland in South Australia, comparing historical (1986) plot data with temporal replicates (2010). We compared the uniformity of species composition among spatially scattered versus spatially clustered plots. At two sites, we compared visual and point-intercept estimation of cover and species diversity. Species composition (presence/absence) shifted between 1986 and 2010. Species that significantly shifted in frequency had low cover. Observations of decreasing species were consistent with predictions from temperature response curves (generalised additive models) for climate change over the period. However, long-term trends could not be distinguished from medium-term dynamics or short-term changes in visibility from this dataset. Difficulties were highlighted in assessing compositional change using historical baselines established for a different purpose in terms of spatial sampling and accuracy of replicate plots, differences in standard plot methods and verification of species identifications. Spatially clustered replicate plots were more similar in species composition than spatially scattered plots, improving change detection potential but decreasing area of inference. Visual surveys detected more species than point-intercepts. Visual cover estimates differed little from point-intercepts although underestimating cover in some instances relative to intercepts. Point-intercepts provide more precise cover estimates of dominant species but took longer and were difficult in steep, heathy terrain. A decision tree based on costs and benefits is presented assessing monitoring options based on data presented. The appropriate method is a function of available resources, the need for precise cover estimates versus adequate species detection, replication and practical considerations such as access and terrain.     

A gis-based assessment on the vulnerability and future extent of the tropical forests of the congo basin

This paper examines the vulnerability of the Congo Basin's forests through a GIS platform, taking into consideration the variables of population growth, road density, logging concession, and forest fragmentation. The assessment indicates that the forests will continue to shrink towards the interior over the next 50 years. Current contiguous forests will fragment into three large blocks, including one on the west side of the Congo River and two in the Democratic Republic of Congo, while a large number of small forest patches will retain in the periphery of the large blocks. The study shows that integrated GIS assessment of the driving forces of tropical deforestation can shed light on the future forest distribution and provide a tool to address the broader implications of social and economic development for tropical deforestation.     

evaluation of a measurement method for forest vegetation in a large-scale ecological survey

We evaluate a field method for determining species richness andcanopy cover of vascular plants for the Forest Health MonitoringProgram (FHM), an ecological survey of U.S. forests. Measurementsare taken within 12 1-m² quadrats on 1/15 ha plots in FHM.Species richness and cover are determined for four height classes(strata) within each quadrat and aggregated by stratum over the entireplot. We estimated (1) the agreement between experienced trainers andinexperienced technicians who collected the data on this survey(accuracy) and (2) the agreement among the technicians (precision) forresults on species richness and cover from 3 test plots at 3 timeintervals. The methods appear to be highly precise, although somediscrepancies with the values obtained by the trainers were found.Trainers found significantly more species in the ground stratum (0–0.6 m) and measured significantly more cover in the uppermost stratum(>4.9 m). The proportion of variation due to measurement error andtemporal variability was less than 13% for species richness (all strata)and cover (all but one stratum). This indicates that the method issuitable for monitoring changes in species richness and canopy coverfor a large-scale synoptic monitoring project such as FHM.