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Plot-based monitoring has yielded much information on the taxonomic diversity and carbon (C) storage in tropical lowland forests of the Amazon basin. This has resulted in an improved understanding of the relationship between lowland forest biomass dynamics and global change drivers, such as climate change and atmospheric CO2 concentration. Much less attention has been paid to the mountain ecosystems of South America that comprise montane forests and alpine vegetation (páramo, puna, high Andean grasslands, wetlands, and alpine heath). This vegetation complex provides a variety of ecosystem services and forms a natural laboratory along various physiographic, geological and evolutionary history/biogeography, and land use history gradients. Here, we review existing empirical understanding and model-based approaches to quantify the contribution of mountain ecosystems to ecosystem service provision in the rapidly changing socioecological setting of the South American mountains. The objective of this paper is to outline a broad road map for the implementation of mountain vegetation into dynamic global vegetation models (DGVM) for use in Earth System Models (ESM), based on our current understanding of their structure and function and of their responsiveness to global change drivers. We also identify treeline processes, critical in mountain ecosystems, as key missing elements in DGVMs/ESMs, and thus explore in addition a treeline model. Stocktaking of the availability of empirical data was undertaken from eight research sites along the Andes and in south-eastern Brazil. Out of eight sites, two (one each in Venezuela and Brazil) had some climate, ecological and ecophysiological data potentially suitable to parametrise a DGVM. Tree biomass data were available for six sites. A preliminary assessment of the Joint UK Land Environment Simulator (JULES) DGVM was made to identify gaps in available data and their impacts on model parametrisation and calibration. Additionally, the potential climate-determined elevation of the treeline was modelled to check the DGVM for its ability to identify the transition between the montane forest and alpine vegetation. Outcomes of the evaluation of the JULES land surface model identified the following key processes in montane forests: temperature-related decrease in net primary production, respiration, and allocation to above-ground biomass and increase in soil C stocks with elevation. There was a variable agreement between simulated biomass and those derived from field measurements via allometric equations. We identified major gaps between data availability and the needs for process-based modelling of South American mountain vegetation and its dynamics in DGVMs. To bridge this gap, we propose a transdisciplinary network, composed of members of the theoretical/modelling and empirical scientific communities, to study the natural dynamics of mountain ecosystems and their responses to global change drivers locally, regionally and at the continental scale, within a social-ecological system framework. The work presented here forms the basis for the design of data collection from field measurements and instrumental monitoring stations to parametrise and verify DGVMs. The network is designed to collaborate with and complement existing long-term research initiatives in the region and will adopt existing standard field protocols. Complementary protocols will ensure compatibility between field data collection and data needed for process-based and empirical models. [ABSTRACT FROM AUTHOR]

This paper presents new allometric models for woody savanna of the dry Sudanian zone of the southern part of Senegal and contributes to the needs for accurate and precise carbon estimates through improved statistical models and methods. The results are based on statistical relationships between the total dry biomass and either tree diameter at breast height (DBH) or tree height for a set of 101 individuals of different sizes from 13 dominant species in 6 protected forests. The statistical regression (cubic order 3) generated for DBH (5-41.5 cm) and tree height (2.5-15.6 m) showed significant R of 0.934 and 0.813, respectively. Using the same database, species-based models for the most represented genera ( Acacia sp., Combretum sp. and Terminalia sp.) show more precision than the generic model. The model residual standard error and relative errors showed a good fit between observed and predicted data. Species-based models showed smaller errors compare to generic models outputs. [ABSTRACT FROM AUTHOR]

Sacred forests are patches of remnant natural forests, protected through social laws by the local communities near their villages and are always dedicated to cultural purposes. They are playing a significant role in combating climate change and informal enhancing biodiversity conservation. The aim of this study was to estimate carbon stocks of sacred forests by quantifying the aboveground biomass (AGB), and belowground (BGB) carbon of trees. The estimation of carbon stocks was conducted across the three sacred forests of Bolocho sacred forest (BSF), Ejjerissa sacred forest (ESF), and Amba sacred forest (ASF). A total of 30 plots: 10 BSF, 10 ESF, and 10 ASF were sampled and trees with DBH ≥5 cm and a height of ≥3 m was considered for biomass-carbon determination. We compared tree biomass, carbon stocks, stem densities, basal area, and importance value index of trees. Nondestructive methods of woody species biomass measurement was used by using allometric equations developed for application in tropical forests and/ or agroforestry system. A total of 4216 individuals representing 87 different species and 44 families were recorded. Statistical the highest stem density was recorded. Total biomass considered as AGB+BGB, which is highest for ASF followed by ESF and BSF (one way ANOVA, F = 98.66, df, 2, p <.001). The estimated amount of AGB across the three sacred forests were (505 Mg ha−1), (267 Mg ha−1) and (202 Mg ha−1) in ASF, ESF, and BSF, respectively. Total biomass stored, both aboveground and belowground (AGB+BGB) significantly higher for ASF (637 Mg ha−1) followed by ESF (338 Mg ha−1) and BSF (255 Mg ha−1). Total biomass carbon (C) was 318.5 Mg C ha−1 for ASF, 169 Mg C ha−1 for ESF, and 127.5 Mg C ha−1 for BSF. From the present study, it can be concluded that, sacred forests and indigenous way of forest protection has playing an enormous roles in carbon sequestration. Perhaps it could be accepted as best practices in climate change (CC) mitigation and reducing deforestation. Hence, it needs urge calls for an immediate attention for conservation, protections and documentation of indigenous knowledge. [ABSTRACT FROM AUTHOR]

Karri (Eucalyptus diversicolor F. Muell.) forest is an endemic forest type of southwest Western Australia (SWWA), noted for having the tallest trees in the region, and providing commercial, ecological and conservation value. To inform management aimed at optimising these values, a thinning trial was commenced in 1992. The aim of this study was to evaluate the effects of thinning on individual tree growth, stand level growth and allometry of karri trees in even-aged stands. Mixed effect models were used to compare the effect of different levels of thinning on individual tree growth and stand level growth of karri. We developed allometric equations modelling the relationship between diameter at breast height (DBH) and height, and tested whether thinning affected this allometric relationship. Thinning enhanced DBH, height and crown width (CW) growth of individual trees by up to 149%, 56% and 108% respectively in heavily thinned stands, with stand basal area growth optimised at retained basal areas of 13 m2 ha−1. Thinning had a significant effect on allometry of DBH with height, height-DBH ratio (HDR) and CW. Reduction in stand density through thinning from below increased diameter growth of individual trees. Stand level basal area growth is optimised at an intermediate level of thinning. Thinning can be a good management tool for even-aged karri forest because it may promote the diameter and thereby basal area growth, good health of individual trees, and potential ecological benefits including accelerated development of larger tree crowns typical of mature forest. [ABSTRACT FROM AUTHOR]

As the loss of forests over time results in a net flux of carbon (C) into the atmosphere, the practice of agroforestry can combat this and serve as a long-term sink for CO2. Based on the inventory of 93 homegarden agroforestry systems (AFS) in three study sites and using a non-destructive method involving allometric equations, the research assessed aboveground (AG) and belowground (BG) biomass and biomass C stocks across sites and along age groups in homegarden AFS in southern and southwestern Ethiopia. Plant diversity parameters were also gathered on perennial plant species. Results indicate that the mean perennial plant species richness per homegarden agroforestry, and other diversity parameters varied strongly among sites (p < 0.05). Biomass C stocks range from 18.11 at Malo Ezo to 32.86 Mg C ha−1 at Saja Laften for AG, 3.97 to 7.10 Mg C ha−1 for BG, and 22.02 to 39.96 Mg C ha−1, for each respective sites, for the overall biomass C stocks were recorded within the homegarden agroforestry systems. In terms of age groups, the mean total biomass C stock did show numerical change from the initial, ≤10 years (22.49 Mg C ha−1) to the middle age group, >10 and ≤20 years (39.96 Mg C ha−1), but it was stagnant 20 years onward (28.49 Mg C ha−1). The homegarden agroforestry systems had the potential to store up to 80.81–112.30 Mg·ha−1 of CO2 equivalents across sites, and 82.53–104.55 Mg·ha−1 of CO2 equivalents along age groups. A positive relationship was noted between AG woody biomass C stocks and attributes such as woody species richness, and woody plant density. Considering the involvement of large numbers of homegardeners, future improvements and expansion of homegarden agroforestry to larger areas can enhance to a great extent the potential to sequester C and thereby mitigate climate change. [ABSTRACT FROM AUTHOR]

Upper-elevation mesic Hawaiian forests have been transformed by cattle ranching and invasive ungulates within the past 200 years. Although the flora and fauna of the Hawaiian Islands have been radically altered by the introduction of invasive species, there is a movement of agriculturalists within the islands interested in reintroducing native species and reforestation in agricultural spaces. One of the keystone species in the Hawaiian Islands is the endemic tree species Acacia koa, known for its ecosystem services and cultural importance. This species is valuable for nitrogen fixation, aquifer recharge, habitat for biodiversity and usefulness in agroforestry systems. This investigation is focused on the relationship between the tree species A. koa and the forage grass species Pennisetum clandestinum (kikuyu) in a silvopastoral context, at an elevation of 5,200 feet above sea level (1585 masl) on the island of Maui. The site of investigation is called Pu'u Makua in Hawaiian and is situated on the southwestern flank of Haleakalā (10,023 feet above sea level–3055 masl) and is part of Ulupalakua Ranch. A total of n = 28 forage samples of P. clandestinum were taken in dry season, 21 of which were taken from underneath the canopies of koa trees (which had been planted in densities of 3, 4, and 6 m apart). The other seven samples were taken in full sun (where no koa trees were growing). This same protocol (sampling n = 28) was repeated in the wet season. Forage samples were then sent to the Agricultural Diagnostics Laboratory at the University of Hawai'i at Manoa for forage analysis to compare attributes of kikuyu under different canopy densities of A. koa. To better understand the leaf area index (LAI) of the canopy of various densities of A. koa, hemispheric (180 degree) photos were taken and then input into Gap Light Analyzer Software for LAI. LAI data of A. koa as well as forage attributes of P. clandestinum were then input into the statistical software InfoStat to investigate relationships between canopy cover and forage quality at each specific location. It was found through Pearson correlation analysis that there are in fact significant relationships between koa and the quality of kikuyu. Measurements of koa trees were also taken to estimate biomass and the amount of carbon sequestered within each tree. These measurements were input into allometric equations specific to koa growing on the Island of Maui that were created by the United States Forest Service. Lastly, to better understand the knowledge of ranchers on Maui, we conducted surveys regarding various ranchers' perceptions of native and non-native trees and their usefulness for silvopastoral ranching systems. Ranchers also identified various tree species that were of use (or harmful) to their operations. Since A. koa was on this list of helpful trees and conferred various ecosystem services and agroecological benefits, the incorporation of koa into ranching systems on the island of Maui is recommended in zones appropriate for its growth. [ABSTRACT FROM AUTHOR]

Recent synergies have increased the use of forest biomass for energy purposes. In addition to high investment costs, low feed-in tariffs, and low operational efficiency, the real potential of forest biomass does not always correspond to the potential that is often claimed in studies. Instead of total forest biomass assessments, it is recommended that sustainable afforestation criteria should be introduced to obtain more reliable and environmentally sustainable scenarios. In this article, the most representative forest species in the Alto Minho region (northern Portugal) are identified, as well as the total forest area available. Based on cartography, forest inventory data, and allometric equations, the annually available usable residual forest biomass (RFB) and corresponding potential energy are estimated. Finally, to promote local forest biomass markets and most efficient thermal use of forest biomass is suggested the creation biomass logistic centres (BLCs) and second-generation biomass logistic centres (2GBLCs) are introduced as well. [ABSTRACT FROM AUTHOR]

Aquilaria malaccensis: Lam. is an important commercial tree species of Bangladesh. This species is widely planted for the increased demand for an essential oil locally knows as "Agar". A nondestructive method was adopted to derive the allometric biomass model for A. malaccensis. Stem volume of 254 trees and the model of biomass expansion factor (BEF) were used to estimate the total above-ground biomass (TAGB). A total of five allometric equations with natural logarithm were tested to derive best-fit biomass models for crown, stem, and total above-ground biomass (TAGB). The best-fit allometric model was selected based on the lowest value of akaike information criteria (AIC), residual standard error (RSE), and the highest value of the coefficient of determination (R2) and akaike information criteria weighted (AICw). The best-fit model of BEF was BEF = exp(2.112318 – (DBH*TH)^0.1066121). The best-fit allometric biomass models for crown, stem and TAGB were crown biomass = exp(−0.6031 + 0.4279*Ln(DBH^2*TH), steam biomass = exp(−3.2483 + 1.7910*Ln(DBH) + 0.7881*Ln(TH) and TAGB = exp(−1.9121 + 1.5937*Ln(DBH) + 0.6152*Ln(TH). The best-fit TAGB model showed the highest efficiency in biomass estimation compared to commonly used pan-tropical biomass models in terms of model prediction error (MPE), model efficiency (ME). [ABSTRACT FROM AUTHOR]

The carbon storage capacity and allometry for bamboo in forest ecosystems has been neglected in the Congo Basin. This study evaluated the above ground carbon stocks and develop allometry for Bambusa vulgaris Schrad. ex J.C.Wendl. in the tropical evergreen forest of Cameroon. Data was collected destructively. Culm density and aboveground carbon were extrapolated; and log transformed models were regressed for best fit allometries. Age of bamboo appeared to be the best predictor of biomass, followed by height and diameter respectively. Height of culm was the best predictor of leaf biomass. The best fit allometric model was obtained when all three predictive variables (diameter, height and age) were inputted in the model. The culm density was 2296 bamboo per hectare (ha); the average aboveground biomass of bamboo was 29 kg; the total aboveground carbon of bamboo per hectare (AGCbamboo per ha) was 29.70 t C per ha and the total aboveground carbon dioxide emission of bamboo per hectare (AGCbamboo emissions per ha) was 108.7 t CO2 equivalence. The more predictive variables were added in a model, the more the model's quality improved and thereby reducing the uncertainty. Thus, the destruction of one ha of bamboo releases enormous CO2 into the atmosphere. These findings are especially timely given the urgent need to quantify carbon stocks in the tropics and formulate good policies to fight against climate change in Cameroon. [ABSTRACT FROM AUTHOR]

This study aims to derive individual tree allometric equations for the above- and belowground biomass components of grey and common alder based on data sets obtained in Latvia. The species aboveground biomass data consisted of 81 trees collected in 27 forest stands. The belowground biomass data were obtained from 27 common alder and 28 grey alder trees sampled throughout Latvia. For grey and common alder, the root-to-shoot ratio decreased with increasing tree dimensions. Our analysis revealed that biomass functions currently used in the national forest inventory overestimate grey alder and underestimate common alder biomass stocks in Latvia. Our findings indicate that the existing local aboveground biomass equation has an overall satisfactory predictive ability compared to the derived equations in this study. The equations from southern Sweden underestimate biomass for mature trees and overestimate small tree biomass, suggesting that even in the hemiboreal region, the grey and common alder populations could have a different distribution of biomass allocated to various components. Model examinations indicated that the derived allometric functions for grey and common alder were unbiased and performed well within the data range and are the best available to substantially improve national estimates of carbon sequestration and biomass resources in Latvia. [ABSTRACT FROM AUTHOR]

Speed agility is considered as the whole assessment of speed of movement, agility and coordination. The 10x4m test has been broadly used to evaluate physical fitness and overall health in children of developmental ages. A myriad of studies have investigated the ecology of speed agility (SA). However, body dimensions are rarely appraised, and this is a weakness because body shapes are affected by growth. This study aimed to model SA-specific allometric equations, and develop an approach objectively predictive for performance while controlling for maturity through age at peak height velocity (agePHV). A total of 7317 (3627 girls) children aged 8–11 years were SA-tested. Multiplicative models with allometric body-size components, agePHV, and categorical differences, were implemented to evaluate SA performance. Model 1 accounted for body-size and shape only, whereas Model 2 included agePHV and Model 3 considered standing broad jump (SBJ) as a surrogate marker for explosive strength. An ectomorphic dominance was revealed across all the models. The explosive strength resulted in influencing SA per height-to-weight ratio. Further, positive exponent of agePHV suggested that the late maturers were likely to show better SA performances. Predictive equations modelled on developmental factors are fundamental to scrutinise performances as valuable health and fitness outcomes in childhood. [ABSTRACT FROM AUTHOR]

Carbon storage is one of the most important ecosystem services provided by kelp beds. Laminarialean kelps are widely harvested along the Warm Temperate South-eastern Pacific coast, a marine province shared by Chile and Peru. Carbon storage assessments of kelps in Peru are lacking. From a blue economy and sustainable management perspectives, information on the carbon storage of kelps is important. We conduct the first carbon storage assessment of Lessonia trabeculata in Peru and contribute to the development of biomass estimation models in order to monitor kelps using the least destructive methodologies. We chose three commonly harvested sites in San Juan de Marcona to haphazardly extract Lessonia trabeculata sporophytes using transects. Sporophyte height (m), wet biomass (kg), maximum (D) and minimum (d) holdfast disk widths (cm) were measured in the field. In the laboratory, C content was measured to calculate the best-fitting coefficients for future estimations by using allometric equations. Individual biomass was best estimated from sporophyte height through a rational model, while holdfast area (ellipse in cm2) was a good proxy of biomass with a sinusoidal model. The southernmost, least accessible, and most exposed site (Elefante) had significantly higher values of stored carbon. We estimated a carbon standing stock (from sporophytes only) of 2044 t C in these kelp beds. Nevertheless, additional and more detailed measurements will likely produce more accurate estimates both in time and space. We provide allometric equations for future carbon assessments. Our results highlight the importance carbon assessment for kelp management and blue carbon estimates and the need to develop science-based marine planning strategies. [ABSTRACT FROM AUTHOR]

The aim of this study has been to compare the aboveground biomass (AGB) in six tropical forests in southeastern Mexico using generic and species-specific models at tree, species, and community levels. The dbh of 2,352 trees ≥10 cm was measured at 115 plots. AGB was estimated using Chave et al.'s generic model, with the most reliable specific equations extracted from the literature and online databases. Overall, we found 45 specific models applicable to 55.4% of the species present. In 30% of the species examined, there was a difference in AGB between the different methods used. Using specific equations at the community level, the estimate for AGB increased by 9.1% (x = 166.6 Mg ha−1 ± 27.5 SD) compared to the generic model alone (p < 0.04). Based on the consistency of overestimation at all sites, we concluded that for these particular tropical rainforests, applying specific models to the small proportion (≤10%) of dominant tree species (≥ 5% relative biomass) was sufficient to improve the accuracy of community level AGB estimates. This justifies increasing the number of databases of specific models particularly for highly productive rainforests. We therefore recommend that this approach be applied to provide further evidence to facilitate model choice. [ABSTRACT FROM AUTHOR]

This study aims at developing a remote sensing based model to estimate carbon stock (CS) in date palm plantations in the United Arab Emirates (UAE). Data from Landsat 8 OLI were used to assess the correlation between spectral reflectance and different vegetation indices on one side, and aboveground biomass (AGB) derived from ground measurements on the other. AGB and CS (ton ha−1) were estimated using traditional destructive methods of standard sampling techniques and allometric equations developed in a previous study for date palms in the area. The relationships between the estimated AGB and parameters derived from remote sensing (RS) data were tested using single and multiple linear regression analysis. The results indicated a significant correlation with certain RS parameters. For mature palms class alone (>10 years), the correlation with single bands was only significant with SWIR1 and SWIR2 while the correlation was significant with all tested VI's except for TCB vegetation index. A combination of bands R, SWIR1, and SWIR2 improved the determination of this class to a coefficient of determination (R2) value of 0.961. However, for the medium and young age classes (10–5 and less than 5 years), the correlation was not significant (with the exception of SWIR1 and TCB index for medium class), where the use of higher spatial resolution can be a good alternative. On the other hand, for mixed ages (young, medium and mature palms), the strongest correlations were found using SWIR2 single band and the SR vegetation index; having R2 values of 0.753 and 0.871, respectively. The R2 was improved to 0.952 by using stepwise multiple regression combining DVI, NDI, and RVI vegetation indices. Finally, results obtained showed that CS represented 53.87% of the total AGB in date palms. Subsequently, the average amount of carbon stock (CS) for both mature and mixed classes was calculated at 15.81 and 10.3 ton ha−1 respectively. [ABSTRACT FROM AUTHOR]

Indigenous forests represent South Africa's smallest biome, yet they are critical spaces for aligning sustainable development goals with carbon mitigation activities and conservation. The objectives of this study were to quantify the productivity and biodiversity of coastal lowland forests in the Dwesa Cwebe nature reserve in the Eastern Cape Province and characterize how estimates differed among alternative allometric equations. Using a complete tree census across six plots in the reserve, a total of 1489 trees were inventoried in 2011 and again in 2016. Aboveground tree carbon averaged 99.8 Mg C ha−1 (range 77.2–126.9 Mg C ha−1) using locally derived equations and 214.6 Mg C ha−1 using generalized equations. Tree aboveground net primary productivity averaged 1041.8 g C m−2 y−1. Forty-eight tree species were identified, including many species important to the livelihoods of local communities for medicinal, ceremonial, and other provisioning services. Overall, this study shows that current conservation activities are concomitant with high tree productivity and high levels of C stocks and biodiversity, including species of local and regional significance. Sustaining forest productivity and biodiversity in the future will be critical for maintaining ecosystem services and enhancing stewardship of forest resources in the region. [ABSTRACT FROM AUTHOR]

Shea tree (Vitellaria paradoxa) is one of the main native oil plants with high economic value in Africa. Its fruits are used for food, medicinal, cultural and exportation purposes. However, the lack of efficient tools to assess annual fruit production of the species limits the sustainable management of its resources. Therefore, production statistics are useful to organize the activities of the shea sector. This study aimed to (i) assess the interannual variation in fruit production along a climatic gradient in Burkina Faso, (ii) examine fruit production patterns according to climatic zones and tree size, (iii) assess the contribution of high-yielding trees in the annual potential production and (iv) develop allometric equations for estimating fruit yields of the species. The yield of 212 trees distributed across three climatic zones was monitored over four successive years. Within each climatic zone, fruit production was significantly different among years. Fruit production was positively and significantly correlated with tree size. The interannual variation in fruit production at tree individual level was higher in drier climatic conditions. The mean interindividual synchrony was less than 50% in each zone, suggesting a large range in fruit production patterns of the species. Annually, more than 55% of the total fruit production was supported by high-yielding trees. The best regression models for estimating fruit yields had R2 values of 69–73% with prediction errors ranging from −7% to 4%. Our findings are useful tools for the planning of rational exploitation of shea tree's resources and its sustainable management. [ABSTRACT FROM AUTHOR]

Copyright of Annals of the American Association of Geographers is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Allometric equations are required for a rapid estimation of commercial timber volume and forest biomass stocks. In order to preserve the forest ecosystem, this study applied a non-destructive sampling approach to measure biophysical properties of living trees. From these measurements, volume and biomass models were developed for 11 dominant tree species in a semi-deciduous natural forest and for Acacia auriculiformis in a plantation located in southern Benin. The observations were combined to develop also generic models applicable to non-dominant tree species. Wood samples of the tree species were collected with an increment borer and analysed in the laboratory to determine species-specific wood densities. The sample size was composed of 243 trees in natural forest and 21 trees in plantation. The measurements were conducted in 30 plots of 50 m × 50 m. The graphical assessment of correlation between model outputs (biomass and volume) and variables (diameter and height) and the statistical analysis confirmed that the logarithmic model with two variables had the best predictions. The assessment also confirmed that the model using diameter only as a variable had good predictions when observations on height were unavailable. The comparative analysis of model predictions showed that the generic model in this study over-estimated biomass by up to 74.80% for certain species and under-estimated biomass by 21.18% for other species. The study shows that there are no statistically significant differences between the wood densities in this research and that published in previous studies. [ABSTRACT FROM AUTHOR]

Vascular epiphyte biomass is poorly studied in Congo Basin forest. The aim of this study was to develop a protocol to estimate epiphyte biomass. Epiphytes were collected on 77 phorophytes of diameter 57-169.5 cm, oven-dried for biomass. Allometric equations for epiphyte biomass were developed with diameter and phorophyte height as predictor variables using regression analysis. The mean epiphyte biomass was 24.48 kg/phorophyte with a standard deviation of ±49.99. Cylicodiscus gabunensis and Triplochiton scleroxylon hosted the greatest epiphyte biomass with a mean vascular epiphyte biomass of 71.65 and 62.3 kg/phorophyte, respectively. Kruskal-Wallis test (p = 0.005) showed that there was a significant difference between epiphyte biomass with respect to phorophyte species. The relationship found between epiphyte biomass and dendrometric variables of the phorophytes were intermediate (Adj.R2 < 0.630) meaning epiphyte biomass increased with increasing tree diameter. However, models with diameter input variables had greater prediction than input variables of total height. Based on the Akaike Information Criterion (AIC), the allometry lnY = −21.37 + 5.21 x ln(D) −0.35 x ln(H) with AIC (183) was the best equation for the prediction of epiphyte biomass. These findings shall contribute to REDD+ (Reducing Emissions from Deforestation and Forest Degradation) strategy for climate change mitigation in Congo Basin. [ABSTRACT FROM AUTHOR]

Procyonidae were the first northern placental carnivorans that reached the Neotropics. They are represented by two extinct genera: †Cyonasua and †Chapalmalania (late Miocene - early Pleistocene). Postcranial elements are only known for †Cyonasua and related taxa (†Parahyaenodon argentinus and †Tetraprothomo argentinus). To obtain highly reliable allometric equations for body mass estimations of fossil procyonids, we performed least squares regressions (multiple and bivariate lineal models) using 51 postcranial linear measurements. The extant sample included 124 taxa corresponding to nine families of Carnivora, with body mass data from the literature. We obtained about 63 equations from diverse combinations of postcranial measurements; 14 of them were selected using several reliability indexes as criteria. Our results show that body masses calculated for †Cyonasua range between 12.63 and 28.45 kg, †P. argentinus was estimated at 14.41 kg, while †T. argentinus at 25.31 kg. Thus, the body mass of †Cyonasua would have been at least twice as high as the mean of the extant procyonid Procyon cancrivorus. †Cyonasua was probably able to fend off predators and quite capable of climbing slowly on thick-enough branches. Other palaeoecological and palaeobiological inferences are discussed. [ABSTRACT FROM AUTHOR]

This study aims to derive allometric functions to estimate the above- and belowground biomass components of the most important tree species in Latvia. The study material included a total of 81 Norway spruce (Picea abies [L.] Karst), 102 Scots pine (Pinus sylvestris L.), 105 birch spp. (mainly silver birch (Betula pendula Roth)) and 84 European aspen (Populus tremula L.) trees sampled in 124 forest stands. The suitability of three mathematical models for the prediction of total aboveground biomass, stem biomass, total live and dead branch biomass, belowground biomass and small root biomass was evaluated. Our analysis revealed that the use of the Intergovernmental Panel on Climate Change mean default values for the root-to-shoot ratio recommended for temperate and boreal ecological zones leads to the overestimation of root biomass of young trees, especially Scots pine and Norway spruce. Our findings indicate that biomass functions recommended for other Baltic Sea countries are not appropriate for the assessment of the biomass stock in Latvia’s forests because these lead to biased estimates. The biomass functions derived in our study are recommended for reporting the biomass stock in Latvia. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Remote Sensing is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Adequate allometric equations are needed for estimating carbon pools of fast growing tree species in relation to international reporting of CO2emissions and for assessing their possible contribution to increasing forest biomass resources. We developed models for predicting biomass, stem basic density and expansion factors of stem to above-ground biomass for five fast growing conifers. Data included destructive measurements of 236 trees from 14 sites, covering a wide range of growth conditions. To ensure model efficiency, models for predicting stem, crown and total above-ground biomass for the five species were estimated simultaneously using a linear, mixed effects model that allowed contemporaneous correlations between the different tree components. Models differed among species and included dbh and tree height. The models explained more than 98% of the variation in above-ground biomass and reflected differences in the allometry between tree species. Stem density differed among species but generally declined with increasing site index and dbh. The overall model for predicting stem basic density included dbh,H100and site index and explained 66% of the total variation. Expansion factors decreased from 1.8–2.0 in small trees (dbh < 10 cm) to 1.1–1.2 for large trees (dbh > 25 cm), but differed among species. The overall model explained 86% of the variation and included quadratic mean diameter and dbh. [ABSTRACT FROM PUBLISHER]

Recent climate change, environmental design, and ecological conservation policies require new and existing urban developments to mitigate and offset carbon dioxide emissions and for cities to become carbon neutral. Some North American models and tools are available and can be used to quantify the carbon offset function of urban trees. But, little information on urban tree carbon storage and sequestration exists from the European Southern Alps. Also, the use of these North American models in Europe has never been assessed. This study developed a protocol to quantify aboveground carbon (C) storage and sequestration using a subsample of urban trees in Bolzano, Italy, and assessed two existing and available C estimation models. Carbon storage and sequestration were estimated using city-specific dendrometrics and allometric biomass equations primarily from Europe and two other United States models; the UFORE (Urban Forest Effects Model) and the CUFR Tree Carbon Calculator (CTCC). The UFORE model carbon storage estimates were the lowest while the CUFR Tree Carbon Calculator (CTCC) C sequestration estimates were the highest. Results from this study can be used to plan, design, and manage urban forests in northern Italy to maximize C offset potential, provide ecosystem services, and for developing carbon neutral policies. Findings can also be used to predict greenhouse gas emissions from tree maintenance operations as well as estimating green waste yield from landscape maintenance activities and its use as biofuel and compost. Managers need to be aware that available models and methods can produce statistically different C storage and sequestration estimates. [ABSTRACT FROM AUTHOR]

Forest biomass studies not only range from estimation of timber standing mass to assessing biogeochemical cycles, but may also reveal genetic variation in growth and biomass allocation. In this study, we investigated differences in biomass accumulation and allometric relationships between tree diameter and biomass of above and belowground components in two populations of Scots pine (Pinus sylvestrisL.) (progeny of clonal seed orchards) differing in stem growth. At a common tree diameter, populations differed in accumulated belowground biomass, but not in total tree or aboveground components' biomass. Populations also differed in the root:shoot ratio and proportional allocation of biomass into stems. However, proportional allocation to stem mass decreased from smaller to larger trees, contrary to branch and foliage, which likely reflected a response to competition in the stand. The allometric equations predicted well the total tree, aboveground, and stem biomass independently of population, but separate equations were required for estimation of belowground biomass for the two populations. These results suggest that total stand and aboveground biomass in young Scots pine stands could be estimated without accounting for genetic component. Comparison of literature data with estimates obtained using our allometric equations indicate that equations were site-specific and should not be generalized to other sites, unless for rough approximation of aboveground biomass. More research is required for a more reliable assessment of genetic effect on allometric relationships for belowground biomass. [ABSTRACT FROM AUTHOR]

We developed a population physiology model, physB, which provides a statistical description of the physiological characteristics in the human population, in terms of the physiological parameters that are needed in physiologically based pharmacokinetic modelling. The model predicts individual organ weights, blood flows and some respiratory parameters from anthropometric properties (body height and weight, age and gender). It draws on two existing models, PK-Pop and P 3 M, but various changes and improvements were made. The conceptual differences among the three models are discussed and they are quantitatively compared by running all three models for various specific combinations of anthropometric properties. [ABSTRACT FROM AUTHOR]

Tree biomass plays an important role in sustainable management and in estimating forest carbon stocks. The objective of this study was to select the best model for measuring stem biomass of Acacia auriculiformis in the study area. Data from five hillocks and 120 individual trees from each hillock were used in this study. Twelve different forms of linear, power and exponential equations were compared in this study to select the best model. Two models (VI and XI) were selected based on R 2, adjusted R 2, the Akaike information criterion, F-statistics and the five assumptions of linear regression. Model VI was discarded based on the Durbin-Watson value of autocorrelation of the residuals, then the ARIMA (2, 0, 1) model was used to remove the autocorrelation from the model and the final bias-corrected model XI was derived. The model was validated with a test data set having the same range of DBH and stem height of the training data set on the basis of linear regression, Morisita's similarity index, and t-test for mean difference between predicted and expected biomass. A comparison between the best logarithmic and non-linear allometric model shows that the non-linear model produces systematic biases and overestimates stem biomass for larger trees. The overall results showed that the bias-corrected logarithmic model XI can be used efficiently for estimating stem biomass of A. auriculiformis in the northeastern region of Bangladesh. [ABSTRACT FROM AUTHOR]

Studies of relationships between number of trees (or other plants) per unit area and their average size have been haunted by doubts about their statistical validity. These doubts are based on the fact that both sides of the size-number equations share the same variable-number of trees. As a result, the error term may be correlated with the predicting variable which would bias the regression. Because of this bias, called artificial correlation, it has been recommended to avoid size-number relationships and use biomass-number relationships instead. This recommendation may work if the shared variable was the only source of bias. Actually, there are several other sources (error of independent variable and constrained variability), which affect both types of relationships. To estimate their overall influence, the variables (stand biomass, average diameter, and number of trees) were smoothed using age of the investigated stands. Using these smoothed variables, it was found that the overall bias of biomass-number relationships was about six times larger and of the opposite sign than that of size-number relationships. This application of the two-stage least squares (2SLS) suggests that we can relate size and number of trees without transgressing any statistical assumptions. [ABSTRACT FROM AUTHOR]