[Meta-analysis of plant restoration impacts on soil microbial community structure in mining areas]. / 植被恢复对矿区土壤微生物群落结构影响的整合分析.

Mining causes severe damage to soil ecosystems. Vegetation restoration in abandoned mine areas is an inevitable requirement for sustainable development. Soil microbes, as the most active component of soil organic matter, play a crucial role in the transformation of carbon, nitrogen, phosphorus, and other elements. They are often used as indicators to assess the extent of vegetation restoration in ecologically fragile areas. However, the impacts of vegetation restoration on soil microbial community structure in mining areas at the global scale remains largely unknown. Based on 310 paired observations from 44 papers, we employed the meta-analysis approach to examine the influence of vegetation restoration on soil microbial abundance and biomass in mining area. The results indicated that vegetation restoration significantly promotes soil microbial biomass in mining areas. In comparison to bare soil, vegetation restoration leads to a significant 95.1% increase in soil microbial biomass carbon and a 87.8% increase in soil microbial biomass nitrogen. The abundance of soil bacteria, fungi, and actinomycetes are significantly increased by 1005.4%, 472.4%, and 177.7%, respectively. Among various vegetation restoration types, the exclusive plan-ting of trees exhibits the most pronounced promotion effect on soil microbial biomass and population, which results in a significant increase of 540.3% in soil fungi and 104.5% in actinomycetes, along with a respective enhancement of 110.3% and 106.4% in microbial biomass carbon and nitrogen. Model selection results revealed that soil satura-ted water content and vegetation restoration history contribute most significantly to the abundance of soil bacteria and fungi. Soil available nitrogen has the most significant impact on the abundance of actinomycetes and microbial biomass carbon, while soil available phosphorus emerges as a crucial factor affecting microbial biomass nitrogen. This research could contribute to understanding the relationship between vegetation restoration and the structure of soil microbial communities in mining areas, and providing scientific support for determining appropriate vegetation restoration types in mining areas.

Microbial competition for phosphorus limits the CO2 response of a mature forest.

The capacity for terrestrial ecosystems to sequester additional carbon (C) with rising CO2 concentrations depends on soil nutrient availability1,2. Previous evidence suggested that mature forests growing on phosphorus (P)-deprived soils had limited capacity to sequester extra biomass under elevated CO2 (refs. 3-6), but uncertainty about ecosystem P cycling and its CO2 response represents a crucial bottleneck for mechanistic prediction of the land C sink under climate change7. Here, by compiling the first comprehensive P budget for a P-limited mature forest exposed to elevated CO2, we show a high likelihood that P captured by soil microorganisms constrains ecosystem P recycling and availability for plant uptake. Trees used P efficiently, but microbial pre-emption of mineralized soil P seemed to limit the capacity of trees for increased P uptake and assimilation under elevated CO2 and, therefore, their capacity to sequester extra C. Plant strategies to stimulate microbial P cycling and plant P uptake, such as increasing rhizosphere C release to soil, will probably be necessary for P-limited forests to increase C capture into new biomass. Our results identify the key mechanisms by which P availability limits CO2 fertilization of tree growth and will guide the development of Earth system models to predict future long-term C storage.

[Differences and drivers of leaf stable carbon and nitrogen isotope in herbs under different vegetation types on the eastern Qinghai-Tibet Plateau]. / é’è—é«˜åŽŸä¸œç¼˜ä¸åŒæ¤è¢«ç±»åž‹ä¸‹è‰æœ¬æ¤ç‰©å¶ç‰‡ç¢³æ°®ç¨³å®šåŒä½ç´ å·®å¼‚åŠå ¶é©±åŠ¨å› ç´ .

The natural abundance of stable carbon and nitrogen isotopes (δ13C and δ15N) in leaves can provide comprehensive information on the physiological and ecological processes of plants and has been widely used in ecological research. However, recent studies on leaf δ13C and δ15N have focused mainly on woody species, few studies have been conducted on herbs in different vegetation types, and their differences and driving factors are still unclear. In this study, we focused on the herbs in subalpine coniferous forests, alpine shrublands, and alpine mea-dows on the eastern Qinghai-Tibet Plateau, and investigated the differences in leaf δ13C and δ15N of herbs and the driving factors. The results showed that there were significant differences in leaf δ13C and δ15N values of herbs among different vegetation types, with the highest δ13C and δ15N values in alpine meadows, followed by alpine shrublands, and the lowest in subalpine coniferous forests. Using variation partitioning analysis, we revealed that differences in leaf δ13C and δ15N of herbs among various vegetation types were driven by both leaf functional traits and climate factors, with the contribution of leaf functional traits being relatively higher than that of climate factors. Hierarchical partitioning results indicated that mean annual temperature (MAT), chlorophyll content index, leaf nitrogen content per unit area (Narea), and leaf mass per area were the main drivers of leaf δ13C variations of herbs across different vegetation types, while the relative importance of Narea and MAT for variation in leaf δ15N of herbs was much higher than those other variables. There was a strong coupling relationship between leaf δ13C and δ15N as indicated by the result of the ordinary least squares regression. Our findings could provide new insights into understanding the key drivers of leaf δ13C and δ15N variations in herbs across different vegetation types.

[Characteristics of soil moisture limitation and non-limitation in the response of sap flow to transpiration driving factors]. / æ ‘å¹²æ¶²æµå¯¹è’¸è ¾é©±åŠ¨å› å­å“åº”çš„åœŸå£¤æ°´åˆ†é™åˆ¶ä¸Žéžé™åˆ¶ç‰¹å¾.

Transpiration is a significant part of water cycle in forest ecosystems, influenced by meteorological factors and potentially constrained by soil moisture. We used Granier-type thermal dissipation probes to monitor xylem sap flow dynamics of three tree species (Quercus liaotungensis, Platycladus orientalis, and Robinia pseudoacacia) in a semi-arid loess hilly region, and to continuously monitor the key meteorological factors and soil water content (SWC). We established the SWC thresholds delineating soil moisture-limited and -unlimited sap flow responses to transpiration drivers. The results showed that mean sap flux density (Js) of Q. liaotungensis and R. pseudoacacia was significantly higher during period with higher soil moisture compared to lower soil moisture, while the difference in Js for P. orientalis between the two periods was not significant. We used an exponential saturation function to fit the relationship between the Js of each tree species and the integrated transpiration variable (VT) which reflected solar radiation and vapor pressure deficit. The difference in the fitting curve parameters indicated that there were distinct response patterns between Js and VT under different soil moisture conditions. There was a threshold in soil moisture limitation on sap flow for each species, which was identified as 0.129 m3·m-3 for Q. liaotungensis, 0.116 m3·m-3 for P. orientalis, and 0.108 m3·m-3 for R. pseudoacacia. Below the thresholds, Js was limited by soil moisture. Above these points, the normalized sensitivity index (NSI) for Q. liaotungensis and P. orientalis reached saturation, while that of R. pseudoacacia did not reach saturation but exhibited a significant reduction in moisture limitation. Among the three species, P. orientalis was the most capable of overcoming soil moisture constraints.

[Application of LA-UNet network model in remote sensing classification of urban green space]. / LA-UNet网络模型在城市绿地遥感分类中的应用.

The accurate identification and monitoring of urban green space is of great significance in urban planning and ecological management. In view of the complex background of urban green space, the traditional remote sensing classification technology is prone to the problem of misalignment and adhesion. Taking Yuhua District of Changsha City as the research area and Gaofen-2 (GF-2) remote sensing image as the data source, we proposed a remote sensing classification method for urban green space based on the LA-UNet model, which was based on the UNet model. We introduced the DWTCA channel attention mechanism module to improve the attention of the network to green space information, and used the CARAFE module to up sample the extracted features to achieve accurate classification of trees, shrubs and other land types in the complex background of the city. The results showed that the LA-UNet model had the best classification effect of urban green space when using standard false color remote sensing images. The overall accuracy and mean intersection over union were 96.3% and 90.9%, which were 2.8% and 6.1% higher than the UNet model, respectively. In the Potsdam public dataset, the overall accuracy and mean intersection over union of the LA-UNet model were also better than those of the UNet model, which increased by 0.9% and 1.8%, respectively, indicating that the LA-UNet model had good robustness and versatility. In summary, the proposed LA-UNet model could effectively alleviate the problems of misalignment and adhesion of urban green space, with advantages in the remote sensing classification of urban green space. The improved LA-UNet model had a smaller parameter volume than the UNet model, which could effectively improve the classification accuracy of urban green space. This study would provide a methodological reference for the accurate classification and understanding the spatial distribution of urban green space.

[Spatiotemporal variation and driving factors of vegetation coverage in Shanxi Province, China]. / å±±è¥¿çœæ¤è¢«è¦†ç›–åº¦çš„æ—¶ç©ºå˜åŒ–åŠé©±åŠ¨å› å­.

Understanding the spatiotemporal variations and driving factors of regional vegetation coverage is crucial for developing scientific plans for ecological environment protection and maintaining regional ecological balance. Based on the Google Earth Engine (GEE) platform and using Landsat Collection 2 data, we investigated the spatiotemporal variation and driving factors of vegetation coverage in Shanxi Province, China, from 1990 to 2020, by employing methods such as pixel-based binary model, trend analysis, zonal statistics, and geodetector. The results showed that vegetation coverage in Shanxi Province showed a fluctuating upward trend from 1990 to 2020. Vegetation coverage in 44.4% of this region had been significantly improved, and the area with significant degradation accounted for 7.4%. Vegetation coverage in Shanxi Province was positively correlated with elevation, slope, and mountain terrain relief. The area proportion of vegetation coverage growth was the highest in the plateau and hilly regions. Factor detection results showed that land use type, landform type, annual average precipitation, and soil type were the main influencing factors of the spatial differentiation of vegetation coverage in Shanxi Province. Results of the interaction detection showed that the interaction between driving factors all showed enhancement. The interaction between natural factors showed a downward trend, while the interaction results of social factors showed an upward trend, reflecting that the impacts of human activities on vegetation coverage in Shanxi Province were gradually increasing.

[Assessment of the lagging effect of vegetation response and loss probability in the Pearl River basin under drought stress]. / å¹²æ—±èƒè¿«ä¸‹ç æ±ŸæµåŸŸæ¤è¢«å“åº”çš„æ»žåŽæ•ˆåº”åŠæŸå¤±æ¦‚çŽ‡è¯„ä¼°.

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.

A warmer climate impairs the growth performance of Central Europe's major timber species in lowland regions.

Recent hot droughts have caused tree vitality decline and increased mortality in many forest regions on earth. Most of Central Europe's important timber species have suffered from the extreme 2018/2019 hot drought, confronting foresters with difficult questions about the choice of more drought- and heat-resistant tree species. We compared the growth dynamics of European beech, sessile oak, Scots pine and Douglas fir in a warmer and a cooler lowland region of Germany to explore the adaptive potential of the four species to climate warming (24 forest stands). The basal area increment (BAI) of the two conifers has declined since about 1990-2010 in both regions, and that of beech in the warmer region, while oak showed positive BAI trends. A 2 °C difference in mean temperatures and a higher frequency of hot days (temperature maximum >30 °C) resulted in greater sensitivity to a negative climatic water balance in beech and oak, and elevated sensitivity to summer heat in Douglas fir and pine. This suggests to include hot days in climate-growth analyses. Negative pointer years were closely related to dry years. Nevertheless, all species showed growth recovery within one to three years. We conclude that all four species are sensitive to a deteriorating climatic water balance and hot temperatures, and have so far not been able to successfully acclimate to the warmer climate, with especially Douglas and beech, but also Scots pine, being vulnerable to a warming and drying climate.

Future carbon sequestration potential in a widespread transcontinental boreal tree species: Standing genetic variation matters!

Climate change (CC) necessitates reforestation/afforestation programs to mitigate its impacts and maximize carbon sequestration. But comprehending how tree growth, a proxy for fitness and resilience, responds to CC is critical to maximize these programs' effectiveness. Variability in tree response to CC across populations can notably be influenced by the standing genetic variation encompassing both neutral and adaptive genetic diversity. Here, a framework is proposed to assess tree growth potential at the population scale while accounting for standing genetic variation. We applied this framework to black spruce (BS, Picea mariana [Mill] B.S.P.), with the objectives to (1) determine the key climate variables having impacted BS growth response from 1974 to 2019, (2) examine the relative roles of local adaptation and the phylogeographic structure in this response, and (3) project BS growth under two Shared Socioeconomic Pathways while taking standing genetic variation into account. We modeled growth using a machine learning algorithm trained with dendroecological and genetic data obtained from over 2600 trees (62 populations divided in three genetic clusters) in four 48-year-old common gardens, and simulated growth until year 2100 at the common garden locations. Our study revealed that high summer and autumn temperatures negatively impacted BS growth. As a consequence of warming, this species is projected to experience a decline in growth by the end of the century, suggesting maladaptation to anticipated CC and a potential threat to its carbon sequestration capacity. This being said, we observed a clear difference in response to CC within and among genetic clusters, with the western cluster being more impacted than the central and eastern clusters. Our results show that intraspecific genetic variation, notably associated with the phylogeographic structure, must be considered when estimating the response of widespread species to CC.

Why can Mikania micrantha cover trees quickly during invasion?

The invasion of Mikania micrantha by climbing and covering trees has rapidly caused the death of many shrubs and trees, seriously endangering forest biodiversity. In this study, M. micrantha seedlings were planted together with local tree species (Cryptocarya concinna) to simulate the process of M. micrantha climbing under the forest. We found that the upper part of the M. micrantha stem lost its support after climbing to the top of the tree, grew in a turning and creeping manner, and then grew branches rapidly to cover the tree canopy. Then, we simulated the branching process through turning treatment. We found that a large number of branches had been formed near the turning part of the M. micrantha stem (TP). Compared with the upper part of the main stem (UP), the contents of plant hormones (auxin, cytokinin, gibberellin), soluble sugars (sucrose, glucose, fructose) and trehalose-6-phosphate (T6P) were significantly accumulated at TP. Further combining the transcriptome data of different parts of the main stem under erect or turning treatment, a hypothetical regulation model to illustrate how M. micrantha can quickly cover trees was proposed based on the regulation of sugars and hormones on plant branching; that is, the lack of support after ascending the top of the tree led to turning growth of the main stem, and the enhancement of sugars and T6P levels in the TP may first drive the release of nearby dormant buds. Plant hormone accumulation may regulate the entrance of buds into sustained growth and maintain the elongation of branches together with sugars to successfully covering trees.

[Response of radial growth of different timberline species to climate change in Yading Nature Reserve, Sichuan, China]. / å››å·äºšä¸è‡ªç„¶ä¿æŠ¤åŒºä¸åŒæž—çº¿æ ‘ç§å¾„å‘ç”Ÿé•¿å¯¹æ°”å€™å˜åŒ–çš„å“åº”.

The radial growth of trees in alpine timberline is particularly sensitive to climate change. We sampled and disposed tree-ring cores of three coniferous tree species including Juniperus saltuaria, Abies forrestii, and Larix potaninii at alpine timberline in Yading Nature Reserve. The standard tree-ring chronology was used to explore the response of radial growth of different timberline species to climate change. The results showed that radial growth of L. potaninii increased after 2000, while that of A. forrestii declined after 2002, and J. saltuaria showed a significant decreasing growth trend in the past 10 years. Such results indicated divergent growth responses to climate factors among the three tree species at alpine timberline. The radial growth of J. saltuaria was sensitive to temperature, and was positively correlated with the minimum temperature from previous October to current August, the mean tempera-ture from previous November to current April and from current July to October, but was negatively associated with the relative humidity from current July to October. The radial growth of A. forrestii showed negative correlation with mean temperature and the maximum temperature from May to June in the current year, while it exhibited positive association with the relative humidity and the Palmer drought severity index from May to June in the current year. L. potaninii radial growth was positively associated with mean temperature and the maximum temperature of November-December in the previous year, the maximum temperature of current March and mean temperature of current August. The temporal stability of climate-growth relationship varied among different timberline species. The positive correlation between radial growth of A. forrestii and J. saltuaria and temperature gradually decreased, while the posi-tive relationship of L. potaninii radial growth and temperature gradually increased. Under the background of climate warming, rapid rise in surface air temperatures may promote the radial growth of L. potaninii, while inhibit that of J. saltuaria and A. forrestii, which may change the position of regional timberline.

[Effects of mycorrhizal types on herbaceous species richness in forest ecosystem]. / èŒæ ¹ç±»åž‹å¯¹æ£®æž—è‰æœ¬æ¤ç‰©ç¾¤è½ç‰©ç§ä¸°å¯Œåº¦çš„å½±å“.

Species richness plays an important role in ecosystem stability and health. Mycorrhizal type is an important factor affecting ecological processes. How mycorrhizal types affect understory herb species richness and their responses to environmental changes remain largely unknown. We investigated the effects of mycorrhizal types on species richness and their responses to environmental change in understory herbaceous communities based on data of three mycorrhizal types of dominated trees (including 1604 arbuscular mycorrhiza (AM) trees, 4654 ectomycorrhiza (ECM) trees, and 5568 AM+ECM trees) and environmental factors in America. The results showed significant differences in species richness of herbaceous plant communities among different mycorrhizal types. Forests with higher dominance of AM plants tended to have higher herbaceous plant richness, supporting the mycorrhizal mediation hypothesis. The impacts of environmental factors (latitude, temperature, precipitation, nitrogen deposition, and soil characteristics) on species richness of herbaceous plant communities depended on mycorrhizal type of forests. The species richness of understory herbs in AM, ECM, and AM+ECM forests was mostly affected by nitrogen deposition, temperature, and soil pH, with the relative importance of 42.3%, 41.1% and 48.7%, respectively. Mycorrhizal types of dominant trees played a vital role in regulating the species richness of understory herbs and influenced their responses to environmental changes.

[Characteristics and drivers of vegetation temporal dynamics in Hunan Province of China during 2002-2020]. / 湖南省2002­2020å¹´æ¤è¢«åŠ¨æ€æ¼”å˜ç‰¹å¾åŠå½±å“å› å­.

Understanding the influences of climate change and human activities on vegetation change is the foundation for effective ecosystem management. Based on the 250 m MODIS-NDVI data from 2002 to 2020, we employed Theil-Sen Median trend analysis and the Mann-Kendall test to quantify vegetation change in Hunan Province. By combining with meteorological, nighttime light index, land cover and other data, residual analysis and correlation analysis, we examined the impacts of human activities and climate change on vegetation dynamics at both the pixel level and the county level. The results showed that the normalized difference vegetation index (NDVI) in Hunan Province exhibited a spatial pattern of "overall improvement with localized degradation" during 2002-2020. Approximately 64.9% of the study area experienced significant vegetation improvement, mainly occurring in the western and central-southern parts of Hunan Province. 1.4% of the study area experienced significant vegetation degradation, mostly in the newly developed urban areas and the farmland in the Dongting Lake Plain. Human activities and climate change jointly promoted vegetation improvement in 67.9% of the study area. Human activities and climate contributed to 96% and 4% of the NDVI change, respectively. At the county level, human activities contributed to over 80% of the NDVI change in each district or county. The impacts of human activities on vegetation change exhibited significant spatial heterogeneity. Urban expansion led to vegetation degradation in the newly developed areas, while vegetation growth appeared in the old developed urban areas. The ecological restoration projects promoted vegetation restoration in the western part of Hunan Province. This study could help us better understand the spatiotemporal variations of vegetation and their responses to climate change and human activities, which would offer scientific basis for effective ecological restoration policy.

[Foraging habitat selection and foraging activities of Picoides tridactylus during winter and spring in Liangshui National Nature Reserve, Heilongjiang, China]. / 凉水国家级自然保护区三趾啄木鸟冬春季节取食生境选择和取食活动特征.

We conducted field surveys on foraging habitat and foraging activities of Picoides tridactylus in Liangshui National Nature Reserve of Heilongjiang Province, China, from April to May and November to December 2022. By using the resource selection function, we analyzed the factors affecting foraging habitat selection of P. tridactylus, compared the differences between foraging habitat selection and foraging activities in winter and spring by chi-square and Mann-Whitney U tests, and investigated their foraging preference with Bailey's method. The results showed that dominant tree species and dead arbor number were the important factors affecting foraging habitat selection of P. tridactylus. They preferred habitats with a large number of dead arbor and dominant trees, such as Picea asperata and Abies fabri. They preferred trees with a height of 10-20 m and a diameter at breast height of 15-45 cm. In spring, they favored semi-withered arbors and showed random utilization of P. koraiensis. During winter, they preferred dead arbors and avoided choosing P. koraiensis. They preferred to forage on tree trunk, in spring pecking in the middle of the tree for a short duration, and during winter, digging in the upper part of the tree for a long duration. Foraging habitat selection and foraging activities of P. koraiensis showed certain differences between winter and spring.

Applying taper function models for black locust plantations in Greek post-mining areas.

A key process in forest management planning is the estimation of tree volume and, more specifically, merchantable volume. The ability to predict the cumulative stem volume relative to any upper stem diameter on standing trees or stands is essential for forest inventories and the management of forest resources. In the 1980s, the Hellenic Public Power Corporation (HPPC) started the rehabilitation of lignite post-mining areas in Greece by planting mainly black locust (Robinia pseudoacacia, L.). Today, these plantations occupy an area of approximately 2570 ha, but the stem volume has not yet been estimated. Therefore, we aimed to estimate the over- and under-bark stem volume using taper function models for 30 destructively sampled trees. Of the nineteen calibrated fixed-effects models, Kozak's (2004) equation performed best for both the over-bark and under-bark datasets, followed by Lee's (2003) and Muhairwe's (1999) equations. Two fixed effect models were compared with fitted coefficients from Poland and the United States confirming that the local model fits were better suited, as the foreign model coefficients caused an increase in root mean square error (RMSE) for stem diameter predictions of 13% and 218%, respectively. The addition of random effects on a single-stem basis for two coefficients of Kozak's (2004) equation improved the model fit significantly at 86% of the over-bark fixed effect RMSE and 69% for the under-bark model. Integrated taper functions were found to slightly outperform three volume equations for predictions of single stem volume over and under bark. Ultimately it was shown that these models can be used to precisely predict stem diameters and total stem volume for the population average as well as for specific trees of the black locust plantations in the study area.

Drought shortens subtropical understory growing season by advancing leaf senescence.

Subtropical forests, recognized for their intricate vertical canopy stratification, exhibit high resistance to extreme drought. However, the response of leaf phenology to drought in the species-rich understory remains poorly understood. In this study, we constructed a digital camera system, amassing over 360,000 images through a 70% throughfall exclusion experiment, to explore the drought response of understory leaf phenology. The results revealed a significant advancement in understory leaf senescence phenology under drought, with 11.75 and 15.76 days for the start and end of the leaf-falling event, respectively. Pre-season temperature primarily regulated leaf development phenology, whereas soil water dominated the variability in leaf senescence phenology. Under drought conditions, temperature sensitivities for the end of leaf emergence decreased from -13.72 to -11.06 days °C-1, with insignificance observed for the start of leaf emergence. Consequently, drought treatment shortened both the length of the growing season (15.69 days) and the peak growth season (9.80 days) for understory plants. Moreover, this study identified diverse responses among intraspecies and interspecies to drought, particularly during the leaf development phase. These findings underscore the pivotal role of water availability in shaping understory phenology patterns, especially in subtropical forests.

Parametrization of biological assumptions to simulate growth of tree branching architectures.

Modeling and simulating the growth of the branching of tree species remains a challenge. With existing approaches, we can reconstruct or rebuild the branching architectures of real tree species, but the simulation of the growth process remains unresolved. First, we present a tree growth model to generate branching architectures that resemble real tree species. Secondly, we use a quantitative morphometric approach to infer the shape similarity of the generated simulations and real tree species. Within a functional-structural plant model, we implement a set of biological parameters that affect the branching architecture of trees. By modifying the parameter values, we aim to generate basic shapes of spruce, pine, oak and poplar. Tree shapes are compared using geometric morphometrics of landmarks that capture crown and stem outline shapes. Five biological parameters, namely xylem flow, shedding rate, proprioception, gravitysense and lightsense, most influenced the generated tree branching patterns. Adjusting these five parameters resulted in the different tree shapes of spruce, pine, oak, and poplar. The largest effect was attributed to gravity, as phenotypic responses to this effect resulted in different growth directions of gymnosperm and angiosperm branching architectures. Since we were able to obtain branching architectures that resemble real tree species by adjusting only a few biological parameters, our model is extendable to other tree species. Furthermore, the model will also allow the simulation of structural tree-environment interactions. Our simplifying approach to shape comparison between tree species, landmark geometric morphometrics, showed that even the crown-trunk outlines capture species differences based on their contrasting branching architectures.

Damage to tropical forests caused by cyclones is driven by wind speed but mediated by topographical exposure and tree characteristics.

Each year, an average of 45 tropical cyclones affect coastal areas and potentially impact forests. The proportion of the most intense cyclones has increased over the past four decades and is predicted to continue to do so. Yet, it remains uncertain how topographical exposure and tree characteristics can mediate the damage caused by increasing wind speed. Here, we compiled empirical data on the damage caused by 11 cyclones occurring over the past 40 years, from 74 forest plots representing tropical regions worldwide, encompassing field data for 22,176 trees and 815 species. We reconstructed the wind structure of those tropical cyclones to estimate the maximum sustained wind speed (MSW) and wind direction at the studied plots. Then, we used a causal inference framework combined with Bayesian generalised linear mixed models to understand and quantify the causal effects of MSW, topographical exposure to wind (EXP), tree size (DBH) and species wood density (ρ) on the proportion of damaged trees at the community level, and on the probability of snapping or uprooting at the tree level. The probability of snapping or uprooting at the tree level and, hence, the proportion of damaged trees at the community level, increased with increasing MSW, and with increasing EXP accentuating the damaging effects of cyclones, in particular at higher wind speeds. Higher ρ decreased the probability of snapping and to a lesser extent of uprooting. Larger trees tended to have lower probabilities of snapping but increased probabilities of uprooting. Importantly, the effect of ρ decreasing the probabilities of snapping was more marked for smaller than larger trees and was further accentuated at higher MSW. Our work emphasises how local topography, tree size and species wood density together mediate cyclone damage to tropical forests, facilitating better predictions of the impacts of such disturbances in an increasingly windier world.

Comprehensive evaluation and application of woody plants in the green spaces of parks in saline-Alkaline areas from a low-carbon perspective: A case study of Tianjin Qiaoyuan Park.

The field of landscape architecture has placed significant emphasis on low-carbon landscapes due to the increasing challenges posed by global warming and environmental deterioration in recent years. The soil ecological conditions in saline-alkaline areas are characterized by poor quality, resulting in suboptimal growth conditions for trees. This, in turn, hampers their ability to effectively sequester carbon, thereby diminishing the potential benefits of carbon sinks. Additionally, the maintenance of tree landscapes in such areas generates more carbon emissions than does conventional green land, making it difficult to reap the benefits of tree-based carbon. A comprehensive evaluation of trees in green park spaces in saline-alkaline areas is conducted from a low-carbon perspective; by identifying the dominant tree species that are well suited to greening, we can offer a precise scientific foundation for implementing low-carbon greening initiatives in cities situated in saline-alkaline environments. Therefore, as a case study, this study investigates Tianjin Qiaoyuan Park, a typical saline park in the Bohai Bay region. The hierarchical analysis method (AHP) was used to evaluate 50 species of trees and shrubs in the park from a low-carbon perspective. The results show that the evaluation system consists of four criterion layers and 15 indicator factors. The relative weight of the criterion layer followed the order of habitat adaptability (B2) > carbon sequestration capacity (B1) > low-carbon management and conservation (B3) > landscape aesthetics (B4). The indicator layer assigned greater weight values to net assimilation (C1), saline and alkaline adaptability (C3), drought tolerance (C4), irr igation and fertilization needs (C8), growth rate (C2), and adaptability to barrenness (C5). The trees were classified into five distinct categories, with each exhibiting significant variation in terms of the strengths and weaknesses of the indicators. According to the comprehensive score, the trees were categorized into three levels. The Grade I plants exhibited the best carbon efficiency performance, comprising a total of 12 species (e.g. Sabina chinensis, Fraxinus chinensis 'Aurea' and Hibiscus syriacu), and demonstrated superior performance in all aspects. Grade II trees, consisting of 26 species (e.g Pinus tabuliformis, Paulownia fortunei, Ligustrum × vicaryi), had the second-highest comprehensive score. Moreover, Grade III trees, encompassing 12 species (e.g Acer mono, Cedrus deodara, Magnolia denudata), exhibited lower comprehensive scores. The extensive use of Grade I and II tree species is recommended in the implementation of low-carbon greening projects in the Bohai Bay region, while Grade III tree species should be judiciously utilized. The findings of this research can serve as a valuable resource for the scientific identification of tree species that are suitable for urban park green spaces in the Bohai Bay region, which is characterized by predominantly saline and alkaline soil. Additionally, the development of an evaluation system can guide the selection of low-carbon tree species when evaluating other types of saline and alkaline lands.

Tree growth potential and its relationship with soil moisture conditions across a heterogeneous boreal forest landscape.

Forest growth varies across landscapes due to the intricate relationships between various environmental drivers and forest management. In this study, we analysed the variation of tree growth potential across a landscape scale and its relation to soil moisture. We hypothesised that soil moisture conditions drive landscape-level variation in site quality and that intermediate soil moisture conditions demonstrate the highest potential forest production. We used an age-independent difference model to estimate site quality in terms of maximum achievable tree height by measuring the relative change in Lorey's mean height for a five year period across 337 plots within a 68 km2 boreal landscape. We achieved wall-to-wall estimates of site quality by extrapolating the modelled relationship using repeated airborne laser scanning data collected in connection to the field surveys. We found a clear decrease in site quality under the highest soil moisture conditions. However, intermediate soil moisture conditions did not demonstrate clear site quality differences; this is most likely a result of the nature of the modelled soil moisture conditions and limitations connected to the site quality estimation. There was considerable unexplained variation in the modelled site quality both on the plot and landscape levels. We successfully demonstrated that there is a significant relationship between soil moisture conditions and site quality despite limitations associated with a short study period in a low productive region and the precision of airborne laser scanning measurements of mean height.