density measures a review and analysis pdf

Density measures a review and analysis pdf

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Density Worksheet Answers

Subjects and Methods

1: Measurements in the Laboratory (Experiment)

Why does changing the shape of an object have no effect on the density of that object? Answer Key Density Calculations Worksheet. Always use atmosphere for pressure, liters for volume, and Kelvin for temperature.

The mass of carbon contained in trees is governed by the volume and density of their wood. This represents a challenge to most remote sensing technologies, which typically detect surface structure and parameters related to wood volume but not to its density. Since wood density is largely determined by taxonomic identity this challenge is greatest in tropical forests where there are tens of thousands of tree species. Here, using pan-tropical literature and new analyses in Amazonia with plots with reliable identifications we assess the impact that species-related variation in wood density has on biomass estimates of mature tropical forests.

Density Worksheet Answers

The mass of carbon contained in trees is governed by the volume and density of their wood. This represents a challenge to most remote sensing technologies, which typically detect surface structure and parameters related to wood volume but not to its density. Since wood density is largely determined by taxonomic identity this challenge is greatest in tropical forests where there are tens of thousands of tree species.

Here, using pan-tropical literature and new analyses in Amazonia with plots with reliable identifications we assess the impact that species-related variation in wood density has on biomass estimates of mature tropical forests.

We find impacts of species on forest biomass due to wood density at all scales from the individual tree up to the whole biome: variation in tree species composition regulates how much carbon forests can store. Further, because species composition varies at all scales and even vertically within a stand, our analysis shows that bias and uncertainty always result if individual identity is ignored.

Our analysis shows that mapping tropical ecosystem carbon always benefits from locally validated measurement of tree-by-tree botanical identity combined with tree-by-tree measurement of dimensions. Tropical forests contain more species and biomass than any other biome on Earth.

While they are being rapidly degraded and deforested, large areas of relatively intact tropical forest still exist, particularly in the Amazon and Congo basins. Wherever they persist, tropical forests contribute hugely to societies, economies, and human well-being, providing vital services that sustain people and nations Watson et al.

For example, dozens of the tree species in South American forests are also cultivated or domesticated, and hundreds more are close relatives Levis et al. These services are all under threat, however, with climate change itself a leading concern. Tropical lands have been warming fast, and continued warming is projected to combine with stronger droughts and potentially lead to crossing ecological thresholds e.

This unique nexus of values and threats in tropical forests means that measuring and mapping their biophysical properties—and then tracking changes—are central goals of global environmental science. Yet because of their extent and complexity, tropical forests are challenging to measure and monitor with precision. For the key property of biomass—from which we may derive carbon storage per unit area—space-borne and airborne sensor technologies are increasingly used to infer biomass [Zolkos et al.

Laser scanning enables precise measurement of canopy height, and if done at sufficient intensity can reveal the three-dimensional structure of trees, while space-borne radar offers potentially global-scale assessment of forest structure. Optical sensing of canopies is widely used to infer vegetation state, such as distinguishing forest from non-forest.

This represents a fundamental challenge, especially given that the single most remarkable and celebrated feature of tropical forests is their extraordinary diversity of species and variation in tree composition e. Indeed, tropical tree species composition varies at all scales from a few metres to across the whole biome due to factors that include climate, geomorphology, nutrient supply, evolutionary history, and anthropogenic impacts e. Since biological composition determines the physical composition of forests in terms of leaf e.

Yet how much the variation in tropical forest species actually matters for biomass mapping remains controversial. The aims of this paper are to explore and quantify this issue for tropical forests and then suggest how the difficulties faced by current remote Earth Observation techniques in mapping tropical forest species compositional variation and biomass density might be mitigated.

By combining literature and new analysis, we examine the issue from the scale of individual tropical tree up to whole continents and assess its impact on Amazon biomass estimates. Forests are made mostly of trees, and in tropical forests these come in extraordinary variety. There can be tree species in a bym patch of Amazon forest. In Amazonia, there are as many as 16, tree species ter Steege et al. With huge floristic diversity, it is reasonable to expect a high degree of functional diversity too, including in the key attributes that affect tree biomass Baker et al.

There is ongoing debate as to whether diversity helps support higher biomass, and if so how e. Thus, here it is the different taxonomic and evolutionary identities of the tree species present which are hypothesised to matter, not the number of species per se.

While the biomass contained by any individual tree is determined by many factors, these are reducible to just two: 1 its size—the volume of wood—and 2 the amount of matter per unit volume or its density. The genetic identity of a tree affects both how big it can become and how dense it is Baker et al. Various studies have shown that these effects are largely independent e.

Since size is a poor predictor of wood density it follows we cannot use the dimensions of trees to infer their density. The fundamental disconnect between size and wood density means that measuring size alone can never capture all information needed to derive biomass. Consequently, in species-diverse tropical forests tree biomass varies greatly even for a fixed tree size.

In southern Peru, Goodman et al. We plot these data here to illustrate how volume and wood density combine to determine biomass Fig.

Canopy trees with similar dimensions have very different biomass. For example, a Cavanillesia umbellata canopy tree with wood density measured at 0. Further, in multivariate allometric models of tree biomass based on harvested tropical trees, wood density is the most important factor after stem diameter in explaining tree biomass—entering models before height e. With the huge range in wood density of species present locally, it is essential to know identity in order to estimate tropical tree biomass with confidence.

Direct measurement of tropical trees shows that wood density and size each independently control biomass. Red points represent 51 forest trees destructively sampled and weighed by Goodman et al. Point areas are proportional to the actual, directly measured aboveground biomass AGB of each tree, plotted against their trunk volume and directly measured wood density. Trunk volume was estimated as basal area multiplied by tree height.

The greyscale background depicts a quasi-continuous allometric estimate of AGB for combinations of tree volume and wood density. To do this, the Chave et al. Yet it does not necessarily follow that the impact of identity on biomass will persist at the larger scales of interest to most Earth Observation questions. Here, we seek to address the question of the extent to which species composition impacts on forest biomass at stand, landscape, and larger scales by reviewing current evidence and developing new analyses.

Ultimately, we wish to shed light on the pervasiveness of species effects, focussing on South American tropical forests due to the relatively larger literature here. At the very largest scales, some spatial variation in forest biomass driven by wood density is already recognised.

For example in the neotropics, dry forest trees generally have greater wood density Chave et al. However, across the tropical moist forest biome we could not find any analysis at the pan-tropical level as to whether wood density varies systematically continent to continent. At the sub-continental scale, concerted, species-driven differences in wood density prevail even within the same biome and same successional stage.

Basal-area-weighted wood density is also significantly higher for Central African forests than their West or East African counterparts Lewis et al.

This is in spite of similar climate and instead is linked to differences in stem turnover rates, with the western forests much more dynamic Phillips et al. This large-scale species-driven difference in biomass is invisible in space-borne LiDAR-derived biomass estimates c. Mitchard et al. While the broad difference between north-east and south-west Amazon forests is clear, uncertainties remain, including the exact nature of the relationships between AGB and wood density, and between mortality rates and wood density, and crucially whether these relationships also persist at smaller geographical units.

Some evidence suggests that at finer scales a more nuanced situation prevails. Within western Amazonia, Landsat-based analyses have revealed great variation in spectral types of forest, starting with the seminal study of Salo et al. In combination with fieldwork, spectral variation has been linked to variation in species and subtle geomorphological, edaphic, and geological controlling factors have been revealed e.

Recently, using airborne hyperspectral sensing variation in canopy function has been explored here at high resolution Asner et al. Recent investigations also show how soil and species differences affect tropical forest wood density in regional and landscape scales.

Similarly, in north-west Amazonia and in French Guiana, Baraloto et al. In Borneo, Jucker et al. As in Amazonia and French Guiana, in Borneo it is white sand forests that have highest wood density. Therefore, in every case—across African, South American, and Asian landscapes—failing to account for habitat-related variation in wood density significantly biases AGB estimates. In sum, complex variation in biodiversity across tropical forest landscapes is the rule, not the exception, and this matters for biomass mapping.

In the white sand case, Borneo and South America are biogeographically isolated from one another so the consistent response implies independent convergence in function driven by selective pressures, possibly as a result of low nutrient availability favouring more conservative, slow-growing species.

Topographic differences in wind disturbance Fortunel et al. In Amazonia, the large regional differences in wood density are related to greater dominance by light-wooded families in the south-west e.

This may be ultimately driven by the unique biogeographic history of the Guiana Shield and the edaphic differences between deep, weathered soils in east-central Amazonia and less developed soils in the Andean forelands affecting forest dynamics Fyllas et al.

Forest structure and dynamics are not only causally linked, but impact other carbon pools too. For example, wood density also affects carbon storage after death: light-wooded forests store less necromass than dense-wooded systems Chao et al.

The mechanistic links between environment, structure, composition and dynamics are relevant for the practical task of remote sensing of biomass as they point to forest properties measureable remotely which may be used to infer composition and hence wood density. In sum, species variation impacts AGB at landscape, regional and continental scales. Yet given the scale of the biome we have only begun to evaluate how biodiversity affects mature forest biomass and wood density.

Here we aim to address these gaps. We first analyse plot-based inventories from one of the best-sampled Amazon landscapes, backed up by some of the most comprehensive botanical work anywhere in the tropics. Secondly, using the latest published data from the RAINFOR plot network we revisit the question of how much wood density matters for large-scale Amazon-wide forest biomass and forest dynamics, and to what extent these relationships hold in geoecological units within Amazonia.

Finally, we combine the new and recent ecological work reporting wood density to document for the first time basal - area-weighted forest wood density estimates at multiple scales across the tropics. For our landscape-scale evaluation of species impacts on biomass, we focus on the lower Tambopata region, in south-eastern Peru. Thirty-five years of botanical collecting have generated a relatively complete knowledge of the flora of the region, and forest inventory and monitoring provide sample plots in intact and human-modified forests, including 1-ha permanent plots and 0.

Variation in fluvial disturbance, soil chemistry, and land use all affect tree species and human livelihoods here e. Classifications derived from larger-scale maps of the Peruvian Amazon e. We centre our analysis on the mature-forest landscape in a roughly km 2 region of the lower Tambopata Fig.

We only use mature-forest plots that are botanically identified as our interest is to identify floristic variation that is geomorphologically associated, rather than due to land-use change. Sampling was conducted between and median date and stratified collaboratively with local residents by geomorphology using Landsat imagery, with exact locations randomised within target habitats.

While the landscape has a fluvial signature, to our knowledge the samples included here have not been subject to recent river flooding. Multiple perspectives on Amazon forest diversity. The figure depicts the study region and forest-type variation sensed with imagery acquired contemporaneously with the floristic and ecological inventories. South American forest cover in the year and location of Peru. Our sample landscape outlined as bykm zone oriented along the lower Tambopata river.

The best-sampled forests centred on Tambopata reserved zone. Note the fine-scale variation in canopy composition and structure driven by small elevational differences. Colours correspond to ten distinct local forest types Gentry , Conservation International and Foster : among-habitat diversity in species composition and associated functional traits is greater than the basic Altura—Bajio dichotomy.

Images from Palmero

Subjects and Methods

Mark J. Bolland, Andrew Grey, Anne M. Horne, Simon E. Briggs, Mark G. Thomas, Rod B. Ellis-Pegler, Greg D.

Javascript is currently disabled in your browser. Several features of this site will not function whilst javascript is disabled. Received 17 December Published 25 July Volume Pages 9— Review by Single anonymous peer review. Editor who approved publication: Professor Henrik Druid.

1: Measurements in the Laboratory (Experiment)

Where is the wisdom we have lost in knowledge? Where is the knowledge we have lost in information? Techniques are not ends in themselves, they are only as good as the answers they provide. The answers are only as good as the questions, and the questions are only as good as the insights generated from observations made using the technique.

Vladimir K. Bakalov, Phillip L. Van, Jeffrey Baron, James C. Reynolds, Carolyn A. In a previous report, preliminary data showed a significant reduction in cortical bone mineral density BMD in women with Turner syndrome that had been treated with GH compared with women with Turner syndrome that had not been treated.

2 comments

  • Mohammad O. 02.06.2021 at 20:43

    This Book is brought to you for free and open access by UWM Digital Commons. It has been accepted for inclusion in Center for Architecture and.

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  • FaraГіn R. 08.06.2021 at 09:39

    Water is the reference with its highest density at 3.

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