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Individual trees have been shown to exhibit strong relationships between DBH, height and volume. Often such studies are cited as justification for forest volume or standing biomass estimation through remote sensing. With resolution of common satellite remote sensing systems generally too low to resolve individuals, and a need for larger coverage, these systems rely on descriptive heights, which account for tree collections in forests. For remote sensing and allometric applications, this height is not entirely understood in terms of its location. Here, a forest growth model (SERA) analyzes forest canopy height relationships with forest wood volume. Maximum height, mean, H₁₀₀, and Lorey's height are examined for variability under plant number density, resource and species. Our findings, shown to be allometrically consistent with empirical measurements for forested communities world-wide, are analyzed for implications to forest remote sensing techniques such as LiDAR and RADAR. Traditional forestry measures of maximum height, and to a lesser extent H₁₀₀ and Lorey's, exhibit little consistent correlation with forest volume across modeled conditions. The implication is that using forest height to infer volume or biomass from remote sensing requires species and community behavioral information to infer accurate estimates using height alone. SERA predicts mean height to provide the most consistent relationship with volume of the height classifications studied and overall across forest variations. This prediction agrees with empirical data collected from conifer and angiosperm forests with plant densities ranging between 10²-10⁶ plants/hectare and heights 6-49 m. Height classifications investigated are potentially linked to radar scattering centers with implications for allometry. These findings may be used to advance forest biomass estimation accuracy through remote sensing. Furthermore, Lorey's height with its specific relationship to remote sensing physics is recommended as a more universal indicator of volume when using remote sensing than achieved using either maximum height or H₁₀₀.

AbstractChina is under pressure to improve its agricultural productivity to keep up with the demands of a growing population with increasingly resource‐intensive diets. This productivity improvement must occur against a backdrop of carbon intensity reduction targets, and a highly fragmented, nutrient‐inefficient farming system. Moreover, the Chinese government increasingly recognizes the need to rationalize the management of the 800 million tonnes of agricultural crop straw that China produces each year, up to 40% of which is burned in‐field as a waste. Biochar produced from these residues and applied to land could contribute to China's agricultural productivity, resource use efficiency and carbon reduction goals. However competing uses for China's straw residues are rapidly emerging, particularly from bioenergy generation. Therefore it is important to understand the relative economic viability and carbon abatement potential of directing agricultural residues to biochar rather than bioenergy. Using cost‐benefit analysis (CBA) and life‐cycle analysis (LCA), this paper therefore compares the economic viability and carbon abatement potential of biochar production via pyrolysis, with that of bioenergy production via briquetting and gasification. Straw reincorporation and in‐field straw burning are used as baseline scenarios. We find that briquetting straw for heat energy is the most cost‐effective carbon abatement technology, requiring a subsidy of $7 MgCO2e−1 abated. However China's current bioelectricity subsidy scheme makes gasification (NPV $12.6 million) more financially attractive for investors than both briquetting (NPV $7.34 million), and pyrolysis ($−1.84 million). The direct carbon abatement potential of pyrolysis (1.06 MgCO2e per odt straw) is also lower than that of briquetting (1.35 MgCO2e per odt straw) and gasification (1.16 MgCO2e per odt straw). However indirect carbon abatement processes arising from biochar application could significantly improve the carbon abatement potential of the pyrolysis scenario. Likewise, increasing the agronomic value of biochar is essential for the pyrolysis scenario to compete as an economically viable, cost‐effective mitigation technology.

Exploring the sensitivity of rural households’ livelihood strategies to livelihood capital is of great significance for improving rural households’ livelihood levels. This paper selects 23 livelihood capital measurement indicators and conducts an in-depth survey of rural households. In addition, the entropy method and a weighted comprehensive model are used to explore the basic characteristics of rural households’ livelihood capital in the upper reaches of the Min River, China, in 2017. Furthermore, econometric models are used to analyze the sensitivity of rural households’ livelihood strategies to livelihood capital. As indicated from the research, the livelihood capital levels of different types of rural households in the study area are not equivalent. The types of rural households with different livelihood strategies can be ordered in terms of quantity as follows: non-agricultural type > non-agricultural dominant type > agricultural dominant type > pure agricultural type. Livelihood strategies have different sensitivities to different livelihood capital measurement indicators. Among these indicators, cash income, the number of relatives and friends available for financial assistance, and the number of civil servants have positive effects on the livelihood strategy selection of non-agricultural dominant rural households and non-agricultural rural households. However, the average age of laborers, area of cultivated land and gardens, number of livestock and poultry, and present value of production tools have negative effects. These evaluation results can provide a scientific decision-making basis for the formulation of poverty alleviation policies by relevant government departments.

This chapter uses data on Intended Nationally Determined Contributions (INDCs) to examine the nature of climate change mitigation and adaptation actions being pursued in African countries and assesses the extent to which preferred mitigation and adaptation priorities advance the cause of sustainable development on the continent. The prospective synergies between mitigation and adaptation approaches and sustainable development are assessed. Also, the pathways through which resource constraints and institutional and policy environment affect Africa’s ability to mitigate and adapt to climate change are examined, as well as the degree to which these constraints are being addressed. It is argued that Africa’s ability to benefit from sustainable development synergies embedded in the mitigation and adaptation strategies in the INDCs will be greatly limited by institutional and policy environment that hinders funding, capacity building, and technological innovation systems development. The slow pace of efforts to address these impediments further erodes confidence that climate adaptation in Africa will be effective at sufficiently contributing to a reduction in climate change risks to the continent.

Facing the non-point source pollution caused by fertilizer loss, study on the agricultural factors that have an influence on fertilizer reduction could provide a basis for the implementation of policies on fertilizer reduction control. Based on the panel data during 2002-2016 with cumulative contribution model and Log-Mean Divisia Index (LMDI), this paper innovatively comes up with reduction driving functions (including agricultural scale, intensification, fertilizer utilization, and labor productivity), studies the cumulative contribution rate and driving factors of fertilizer reduction in county units of Zhejiang Province. Main conclusions are: (1) 37 of 63 county units (58.73%) showed decreased in fertilizer application; top five county units contributed 50+%; top county units that contribute to fertilizer reduction are in plain area in Northern Zhejiang, coastal area in Eastern and Southern Zhejiang, valley and basin area in Western and Southern Zhejiang where arable land is relatively even. (2) Fertilizer application intensity (fertilizer application per unit area of land cultivation) in Zhejiang Province increased by 18.67%, but there are only 15 county units where fertilizer application intensity is reduced. In general, fertilizer reduction in Zhejiang Province kept developing steadily. (3) Factors (fertilizer efficiency, intensification and agricultural scale) drive fertilizer reduction while labor productivity triggers the growth in application intensity. In Hangzhou, Ningbo and Shaoxing in Northern and Eastern Zhejiang, the above factors all have a prominent driving effect, but labor productivity also promotes fertilizer increment. In the end, this paper proposes policies on fertilizer reduction control in terms of efficiency, inputs and compensations.

Abstract Reasonable assessment of the environmental benefits of integrating forest products into global value chains (GVCs) is important to promote sustainable development. Based on the forest product sector data for 41 countries from 2002 to 2014, this paper explores the impact of GVC participation on carbon embodied in exports using the 2008 financial crisis, a quasi-natural experiment of negative global value chain shocks. We found that deepening backward participation in forest product value chains led to more substantial increases in carbon emissions than did forward participation. Countries with large decreases in GVC participation reduced more carbon embodied in forest product exports after the financial crisis (relative to countries with small decreases) through a larger reduction in the scale of forest product exports, and a decrease in the growth rate of capital-intensive products as a result of the relative decline in capital investment. They increased the embodied carbon of exports through a decrease in the growth rate of skilled personnel. Strengthening the technology effect of GVCs with the guidance of skilled forestry personnel is a key way to decrease exported embodied carbon.

Urban vacant lots are often a contentious feature in cities, seen as overgrown, messy eyesores that plague neighborhoods. We propose a shift in this perception to locations of urban potential, because vacant lots may serve as informal greenspaces that maximize urban biodiversity while satisfying residents’ preferences for their design and use. Our goal was to assess what kind of vacant lots are ecologically valuable by assessing their biotic contents and residents’ preferences within a variety of settings. We surveyed 150 vacant lots throughout Baltimore, Maryland for their plant and bird communities, classified the lot’s setting within the urban matrix, and surveyed residents. Remnant vacant lots had greater vegetative structure and bird species richness as compared to other lot origins, while vacant lot settings had limited effects on their contents. Residents preferred well-maintained lots with more trees and less artificial cover, support of which may increase local biodiversity in vacant lots. Collectively, we propose that vacant lots with a mixture of remnant and planted vegetation can act as sustainable urban greenspaces with the potential for some locations to enhance urban tree cover and bird habitat, while balancing the needs and preferences of city residents.

AbstractAutotrophs play an essential role in the cycling of carbon and nutrients, yet disease‐ecosystem relationships are often overlooked in these dynamics. Importantly, the availability of elemental nutrients like nitrogen and phosphorus impacts infectious disease in autotrophs, and disease can induce reciprocal effects on ecosystem nutrient dynamics. Relationships linking infectious disease with ecosystem nutrient dynamics are bidirectional, though the interdependence of these processes has received little attention. We introduce disease‐mediated nutrient dynamics (DND) as a framework to describe the multiple, concurrent pathways linking elemental cycles with infectious disease. We illustrate the impact of disease–ecosystem feedback loops on both disease and ecosystem nutrient dynamics using a simple mathematical model, combining approaches from classical ecological (logistic and Droop growth) and epidemiological (susceptible and infected compartments) theory. Our model incorporates the effects of nutrient availability on the growth rates of susceptible and infected autotroph hosts and tracks the return of nutrients to the environment following host death. While focused on autotroph hosts here, the DND framework is generalizable to higher trophic levels. Our results illustrate the surprisingly complex dynamics of host populations, infection patterns, and ecosystem nutrient cycling that can arise from even a relatively simple feedback between disease and nutrients. Feedback loops in disease‐mediated nutrient dynamics arise via effects of infection and nutrient supply on host stoichiometry and population size. Our model illustrates how host growth rate, defense, and tissue chemistry can impact the dynamics of disease–ecosystem relationships. We use the model to motivate a review of empirical examples from autotroph–pathogen systems in aquatic and terrestrial environments, demonstrating the key role of nutrient–disease and disease–nutrient relationships in real systems. By assessing existing evidence and uncovering data gaps and apparent mismatches between model predictions and the dynamics of empirical systems, we highlight priorities for future research intended to narrow the persistent disciplinary gap between disease and ecosystem ecology. Future empirical and theoretical work explicitly examining the dynamic linkages between disease and ecosystem ecology will inform fundamental understanding for each discipline and will better position the field of ecology to predict the dynamics of disease and elemental cycles in the context of global change.