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We quantified the lag time of vegetation response to drought in the Pearl River basin (PRB) based on the standardized precipitation evapotranspiration index (SPEI) and normalized difference vegetation index (NDVI), and constructed a vegetation loss probability model under drought stress based on the Bayesian theory and two-dimensional joint distribution. We further quantitatively evaluated the spatial variations of loss probability of four vegetation types (evergreen broadleaf forest, mixed forest, grassland, and cropland) under different drought intensities. The results showed that the drought risk in eastern West River, the upper reaches of North River and East River, and southern Pearl River Delta was obviously higher than that in other regions during 1982-2020. The response time of vegetation to drought in high-altitude areas in the upper reaches of PRB (mostly<3 month) was generally shorter than that in low altitude areas (>8 month). Drought exacerbated the probability of vegetation loss, with higher vulnerability of mixed forest than the other three vegetation types. The loss probability of vegetation was lower in northwestern PRB than that in central PRB.

The carbon costs of global wood harvests.

After agriculture, wood harvest is the human activity that has most reduced the storage of carbon in vegetation and soils1,2. Although felled wood releases carbon to the atmosphere in various steps, the fact that growing trees absorb carbon has led to different carbon-accounting approaches for wood use, producing widely varying estimates of carbon costs. Many approaches give the impression of low, zero or even negative greenhouse gas emissions from wood harvests because, in different ways, they offset carbon losses from new harvests with carbon sequestration from growth of broad forest areas3,4. Attributing this sequestration to new harvests is inappropriate because this other forest growth would occur regardless of new harvests and typically results from agricultural abandonment, recovery from previous harvests and climate change itself. Nevertheless some papers count gross emissions annually, which assigns no value to the capacity of newly harvested forests to regrow and approach the carbon stocks of unharvested forests. Here we present results of a new model that uses time discounting to estimate the present and future carbon costs of global wood harvests under different scenarios. We find that forest harvests between 2010 and 2050 will probably have annualized carbon costs of 3.5-4.2 Gt CO2e yr-1, which approach common estimates of annual emissions from land-use change due to agricultural expansion. Our study suggests an underappreciated option to address climate change by reducing these costs.

Above-ground carbon stock and REDD+ opportunities of community-managed forests in northern Thailand.

This study aimed to investigate the structure of two deciduous forests and assess their above-ground carbon stock in order to promote community forest management (CFM) for REDD+ opportunities in the Ban Mae Chiang Rai Lum Community Forest in northern Thailand. A systematic sampling method was used to establish twenty-five sample plots of 40 m × 40 m (0.16 ha) each that were used to survey the entire 3,925 ha area of the community forest. Cluster analysis identified two different forest types: dry dipterocarp forest and mixed deciduous forest. It was determined that the above-ground carbon stock did not vary significantly between them. An analysis of carbon sequestration in the community forest indicates that carbon stock increased under CFM from 2007 to 2018 by an estimated 28,928 t C and participation in the carbon market would have yielded approximately US $339,730.43 or US $8.66 /ha/year to the community for that 10-year period. Projections for 2028 reflect that carbon stock will experience continual growth which indicates that maintaining CFM can increase carbon sequestration and reduce CO2 emissions. However, though further growth of carbon stock in the community forest is expected into 2038, that growth would be at a lesser rate than during the preceding decade. This suggests that CFM management should address forest utilization practices with a focus on maintaining long term carbon stock growth. Additional measures to address the impact of drought conditions and to safeguard against forest fires are required to sustain tree species' growth and expansion in order to increase their carbon accumulation potential. Thailand's community forest involvement in REDD+ and participation in its international carbon market could create more economic opportunities for local communities.

Conditional inference trees in the assessment of tree mortality rates in the transitional mixed forests of Atlantic Canada.

Long-term predictions of forest dynamics, including forecasts of tree growth and mortality, are central to sustainable forest-management planning. Although often difficult to evaluate, tree mortality rates under different abiotic and biotic conditions are vital in defining the long-term dynamics of forest ecosystems. In this study, we have modeled tree mortality rates using conditional inference trees (CTREE) and multi-year permanent sample plot data sourced from an inventory with coverage of New Brunswick (NB), Canada. The final CTREE mortality model was based on four tree- and three stand-level terms together with two climatic terms. The correlation coefficient (R2) between observed and predicted mortality rates was 0.67. High cumulative annual growing degree-days (GDD) was found to lead to increased mortality in 18 tree species, including Betula papyrifera, Picea mariana, Acer saccharum, and Larix laricina. In another ten species, including Abies balsamea, Tsuga canadensis, Fraxinus americana, and Fagus grandifolia, mortality rates tended to be higher in areas with high incident solar radiation. High amounts of precipitation in NB's humid maritime climate were also found to contribute to heightened tree mortality. The relationship between high GDD, solar radiation, and high mortality rates was particularly strong when precipitation was also low. This would suggest that although excessive soil water can contribute to heightened tree mortality by reducing the supply of air to the roots, occasional drought in NB can also contribute to increased mortality events. These results would have significant implications when considered alongside regional climate projections which generally entail both components of warming and increased precipitation.

Unveiling African rainforest composition and vulnerability to global change.

Africa is forecasted to experience large and rapid climate change1 and population growth2 during the twenty-first century, which threatens the world's second largest rainforest. Protecting and sustainably managing these African forests requires an increased understanding of their compositional heterogeneity, the environmental drivers of forest composition and their vulnerability to ongoing changes. Here, using a very large dataset of 6 million trees in more than 180,000 field plots, we jointly model the distribution in abundance of the most dominant tree taxa in central Africa, and produce continuous maps of the floristic and functional composition of central African forests. Our results show that the uncertainty in taxon-specific distributions averages out at the community level, and reveal highly deterministic assemblages. We uncover contrasting floristic and functional compositions across climates, soil types and anthropogenic gradients, with functional convergence among types of forest that are floristically dissimilar. Combining these spatial predictions with scenarios of climatic and anthropogenic global change suggests a high vulnerability of the northern and southern forest margins, the Atlantic forests and most forests in the Democratic Republic of the Congo, where both climate and anthropogenic threats are expected to increase sharply by 2085. These results constitute key quantitative benchmarks for scientists and policymakers to shape transnational conservation and management strategies that aim to provide a sustainable future for central African forests.

The tree cover and temperature disparity in US urbanized areas: Quantifying the association with income across 5,723 communities.

Urban tree cover provides benefits to human health and well-being, but previous studies suggest that tree cover is often inequitably distributed. Here, we use National Agriculture Imagery Program digital ortho photographs to survey the tree cover inequality for Census blocks in US large urbanized areas, home to 167 million people across 5,723 municipalities and other Census-designated places. We compared tree cover to summer land surface temperature, as measured using Landsat imagery. In 92% of the urbanized areas surveyed, low-income blocks have less tree cover than high-income blocks. On average, low-income blocks have 15.2% less tree cover and are 1.5°C hotter than high-income blocks. The greatest difference between low- and high-income blocks was found in urbanized areas in the Northeast of the United States, where low-income blocks in some urbanized areas have 30% less tree cover and are 4.0°C hotter. Even after controlling for population density and built-up intensity, the positive association between income and tree cover is significant, as is the positive association between proportion non-Hispanic white and tree cover. We estimate, after controlling for population density, that low-income blocks have 62 million fewer trees than high-income blocks, equal to a compensatory value of $56 billion ($1,349/person). An investment in tree planting and natural regeneration of $17.6 billion would be needed to close the tree cover disparity, benefitting 42 million people in low-income blocks.

Modeling trade-offs across carbon sequestration, biodiversity conservation, and equity in the distribution of global REDD+ funds.

The program on Reducing Emissions from Deforestation and Forest Degradation (REDD+) is one of the major attempts to tackle climate change mitigation in developing countries. REDD+ seeks to provide result-based incentives to promote emission reductions and increase carbon sinks in forest land while promoting other cobenefits, such as the conservation of biodiversity. We model different scenarios of international REDD+ funds distribution toward potential recipient countries using 2 carbon emission reduction targets (20% and 50% compared to the baseline scenario, i.e., deforestation and forest degradation without REDD+) by 2030. The model combines the prioritization of environmental outcomes in terms of carbon sequestration and biodiversity conservation and social equity, accounting for the equitable distribution of international REDD+ funds. Results highlight the synergy between carbon sequestration and biodiversity conservation under alternative fund allocation criteria, especially for scenarios of low carbon emission reduction. Trade-offs increase when distributional equity is considered as an additional criterion, especially under higher equity requirements. The analysis helps to better understand the inherent trade-offs between enhancing distributional equity and meeting environmental targets under alternative REDD+ fund allocation options.

Wealth accumulation in rotation forestry - Failure of the net present value optimization?

The rate of wealth accumulation is discussed, and an expression for a momentary rate of capital return is presented. An expected value of the wealth accumulation rate is produced. The return rates depend on any yield function. Three different yield functions are applied, two of them published in the literature, and a third one parametrized using a comprehensive growth model. A common economic objective function, as well as a third known objective function, are applied and compared with the clarified wealth accumulation rate. While direct optimization of wealth appreciation rate always yields best results, procedures gained by maximizing the internal rate of return are only slightly inferior. With external discounting interest rate, the maximization of net present value yields arbitrary results, the financial consequences being at worst devastating.

Vegetation communities on commercial developments are heterogenous and determined by development and landscaping decisions, not socioeconomics.

In urban ecosystems, woody vegetation communities and the ecosystem functions and habitat they provide are largely controlled by humans. These communities are assembled during development, landscaping, and maintenance processes according to decisions made by human actors. While vegetation communities on residential land uses are increasingly well studied, these efforts generally have not extended to other land uses, including commercial property. To fill this gap, I surveyed tree and shrub communities on office developments located in Redmond and Bellevue, Washington, USA, and explored whether aggregated neighborhood and parcel scale socio-economic variables or variables describing the outcome of development and landscaping actions better explained variation in vegetation communities. I found that both tree and shrub communities on office developments are heterogenous, with sites characterized by native or ornamental vegetation. The heterogeneity I observed in vegetation communities within one land use suggests that different ecosystem functions, habitat quality, and habitat quantities are provided on office developments. Greater provision of e.g. native conifer habitat is possible using currently existing developments as models. Additionally, the outcome of development and landscaping decisions explained more variation in community composition than the socio-economic factors found significant on residential property. Together with previous research showing that residential property owner attitudes and actions are more important than socio-economic descriptors, my results suggest that individual motivators, including intended audience, may be the primary determinant of urban vegetation communities. Future urban ecology research should consider sampling the vegetation gradient within land uses, better understanding individual motivation for vegetation management, and creating models of the urban ecosystems that account for alternate decision pathways on different land uses.

Asymmetric competition, ontogenetic growth and size inequality drive the difference in productivity between two-strata and one-stratum forest stands.

Size inequality has been considered a key feature of plant population structure with impacts on ecosystem functions. In forest ecosystems, studies examining the relationship between tree size inequality and stand productivity have produced mixed outcomes. These studies found positive, neutral or negative relationships and discussed how this could be influenced by competition for light between trees (e.g. light interception efficiency), but far less attention has been paid to the role played by tree ontogenetic growth. In this article, we present a simple mathematical model that predicts the basal area growth of a two-strata stand as a function of tree basal areas and asymmetric competition. Comparing the growth of this stand to the growth of a spatially homogeneous one-stratum stand and a spatially heterogeneous one-stratum stand, we show that higher growth of the two-strata stand is achieved for concave shape, increasing functions of ontogenetic growth and for low intensities of absolute size-asymmetric competition. We also demonstrate that the difference in growth between the two-strata stand and the one-stratum stands depends on tree size inequality, mean tree basal area and total basal area in the two-strata stand. We finally found that the relationships between tree size inequality and productivity can vary from positive to negative and even non-monotonous. However, we highlight that negative relationships may be more frequent. As a conclusion, our results indicate that ontogenetic growth can have a major impact on the form and the magnitude of the size inequality-productivity relationship.

African Orphan Crops Consortium (AOCC): status of developing genomic resources for African orphan crops.

MAIN CONCLUSION: The African Orphan Crops Consortium (AOCC) successfully initiated the ambitious genome sequencing project of 101 African orphan crops/trees with 6 genomes sequenced, 6 near completion, and 20 currently in progress. Addressing stunting, malnutrition, and hidden hunger through nutritious, economic, and resilient agri-food system is one of the major agricultural challenges of this century. As sub-Saharan Africa harbors a large portion of the severely malnourished population, the African Orphan Crops Consortium (AOCC) was established in 2011 with an aim to reduce stunting and malnutrition by providing nutritional security through improving locally adapted nutritious, but neglected, under-researched or orphan African food crops. Foods from these indigenous or naturalized crops and trees are rich in minerals, vitamins, and antioxidant, and are an integral part of the dietary portfolio and cultural, social, and economic milieu of African farmers. Through stakeholder consultations supported by the African Union, 101 African orphan and under-researched crop species were prioritized to mainstream into African agri-food systems. The AOCC, through a network of international-regional-public-private partnerships and collaborations, is generating genomic resources of three types, i.e., reference genome sequence, transcriptome sequence, and re-sequencing 100 accessions/species, using next-generation sequencing (NGS) technology. Furthermore, the University of California Davis African Plant Breeding Academy under the AOCC banner is training 150 lead African scientists to breed high yielding, nutritious, and climate-resilient (biotic and abiotic stress tolerant) crop varieties that meet African farmer and consumer needs. To date, one or more forms of sequence data have been produced for 60 crops. Reference genome sequences for six species have already been published, 6 are almost near completion, and 19 are in progress.

Evidence of a seasonal trade-off between growth and starch storage in declining beeches: assessment through stem radial increment, non-structural carbohydrates and intra-ring δ13C.

Forest decline is reported in recent decades all over the world. However, developing a clear vision of the associated tree dysfunctioning is still a challenge for plant physiologists. In this study, our aim was to examine the seasonal carbon adjustments of beech trees in the case of a long-term drought-induced decline. We compared healthy and declining trees in terms of stem radial growth, phloem sugar content and δ13C, together with xylem carbohydrates and intra-ring δ13C patterns. The radial growth of declining trees was clearly reduced by lower growth rates and shorter growing season length (44 days compared with healthy trees). The soluble sugar content was higher in the xylem of declining trees compared with the healthy ones, but similar in the phloem except at the end of their growth. Declining trees increased their levels of xylem starch content from budburst until the date of maximal growth rate. These reserve dynamics revealed an early trade-off between radial growth and starch storage that might be the result of an active or passive process. For declining trees, the slight decrease of intra-ring cellulose δ13C pattern during the early growing season was attributed to the synthesis of 13C enriched starch. For healthy trees, δ13C patterns were characterized by a progressive 13C increase along the ring, attributed to increased water-use efficiency (WUE) in response to decreased water availability. Individual variations of the crown area were negatively correlated to the intra-ring δ13C amplitude, which was ascribed to variations in canopy WUE and resource competition for healthy trees and partly to variations in the amount of reserves accumulated during spring for declining ones. Our study highlights the carbon physiological adjustment of declining trees towards reducing spring growth while storing starch, which can be reflected in the individual intra-ring cellulose δ13C patterns.

Pollution tolerance assessment of temperate woody vegetation growing along the National Highway-5 in Himachal Pradesh, India.

Industrialization and globalization have resulted in pollution of all the three ecosystems, including soil, water, and air. Among these, air pollution has generated much interest, since it has a major influence on the transboundary dispersion of pollutants globally. Air pollution tolerance index (APTI) value represents tolerance level of plants which help in selecting the most suitable plant species for plantation in/around affected areas. This parameter in conjunction with Anticipated Performance Index (API) can provide a logical solution for green belt development by considering biological and socio-economic aspect of the species and help in reducing the levels of pollutants. The present study was conducted in Himachal Pradesh, constituting a very vital part of the Indian Himalayan Region. In the present study, APTI and API values of six commonly growing temperate and sub-temperate plant species viz., Quercus leucotrichophora, Rubus ellipticus, Debregeasia saeneb, Hypericum oblongifolium, Punica granatum, and Grevillea robusta, were evaluated along the National Highway-5 in Himachal Pradesh. The highest value of APTI was observed for Grevillea robusta (12.89), followed by Punica granatum (10.87), Debregeasia saeneb (10.50), Hypericum oblongifolium (10.43), Rubus ellipticus (10.18), and Quercus leucotrichophora (9.68). Upon assessment of API, it was observed that Grevillea robusta (62.50%) was the highest scoring plant species in trees, while Rubus ellipticus and Debregeasia saeneb were the highest scoring shrub species (56.25% each) and thus can be recommended for green belt development and attenuation of air pollution in the region. Punica granatum can be suggested for plantation among the native species.

Automated low-cost terrestrial laser scanner for measuring diameters at breast height and heights of plantation trees.

A terrestrial laser scanner is a fast, high-precision data acquisition device, which has been applied more and more to the research area of forest inventory. In this study, a type of automated low-cost terrestrial laser scanner was designed and implemented based on a SICK LMS-511 two-dimensional laser scanning sensor and a stepper motor. The new scanner was named BEE(developed by the department of Electronic Engineering, Beijing Forestry University), which can scan the forest trees in three dimensions. The BEE scanner and its supporting software are specifically designed for forest inventory. The specific software was developed to smoothly control the BEE scanner and to acquire the data, including the angular data, range data, and intensity data, and the data acquired by the BEE scanner could be processed into point cloud data, a range map, and an intensity map. Based on the point cloud data, the trees were detected by a single slice of the single scan in a plot, and the local ground plane was fitted for each detected tree. Then the diameter at breast height (DBH), tree height, and tree position could be estimated automatically by using the specific software. The experiments have been performed by using the BEE scanner in an artificial ginkgo forest which was located in the Haidian District of Beijing. Four 10 m × 10 m square plots were selected for the experiments. The BEE scanner scanned in the four plots and acquired the single-scan data, respectively. The DBH, tree height, and tree position of the trees in the four plots were estimated and analyzed. For comparison, manually-measured data was also collected in the four plots. The trunk detection rate for all four plots was 92.75%; the root mean square error of the DBH estimation was 1.27 cm; the root mean square error of the tree height estimation was 0.24 m; and the tree position estimation was in line with the actual position. The scanner also was tested in more natural forest in the JiuFeng Forest Park. Two plots with a radius of 5 meters were scanned. Eleven trees in the plot with a flat ground were detected and DBH were estimated. But tree detection was failed in the other plot because of the undulating ground. Experimental results show that the BEE scanner can efficiently estimate the structure parameters of plantation trees and has good potential in practical applications of forest inventory.

Fire, CO2, and climate effects on modeled vegetation and carbon dynamics in western Oregon and Washington.

To develop effective long-term strategies, natural resource managers need to account for the projected effects of climate change as well as the uncertainty inherent in those projections. Vegetation models are one important source of projected climate effects. We explore results and associated uncertainties from the MC2 Dynamic Global Vegetation Model for the Pacific Northwest west of the Cascade crest. We compare model results for vegetation cover and carbon dynamics over the period 1895-2100 assuming: 1) unlimited wildfire ignitions versus stochastic ignitions, 2) no fire, and 3) a moderate CO2 fertilization effect versus no CO2 fertilization effect. Carbon stocks decline in all scenarios, except without fire and with a moderate CO2 fertilization effect. The greatest carbon stock loss, approximately 23% of historical levels, occurs with unlimited ignitions and no CO2 fertilization effect. With stochastic ignitions and a CO2 fertilization effect, carbon stocks are more stable than with unlimited ignitions. For all scenarios, the dominant vegetation type shifts from pure conifer to mixed forest, indicating that vegetation cover change is driven solely by climate and that significant mortality and vegetation shifts are likely through the 21st century regardless of fire regime changes.

Carbon sinks and output of China's forestry sector: An ecological economic development perspective.

Forestry has a dual role in mitigating climate change and increasing regional output value. Therefore, forestry is meaningful for the anthroposphere and the atmosphere. In this study, slacks-based measure (SBM) approach and Malmquist-Luenberger Index are adopted to measure the static efficiency and dynamic changes in forestry productivity in thirty regions in China. Ecological development is measured by setting forest carbon sinks as desirable output and economic development is evaluated by forestry output value. Moreover, using the three-stage DEA model, the economic and environmental factors are introduced to adjust regional forest carbon sinks and forestry output slacks. Finally, from timely evolution and spatial non-equilibrium perspectives, the ecological-economic efficiency and total factor productivity of forests are analyzed according to the results. The results revealed that the estimators of ecological efficiency and productivity are greater than the economic development of the forest. The highest ecological economic efficiency and productivity is in the southwest region of China. Eight economic or environmental factors adjusting the output have influence on the total factor productivity of forestry, and the results show that harvest has no clear effect on environmental improvement. Policy implications are further proposed to develop environmental management to mitigate climate change.