Mixture Of Trees Research Articles

Plantation understorey legume functional groups enhance soil organic carbon sequestration by promoting species richness

AbstractDespite evidence showing that plant diversity or tree mixtures increase carbon storage in experimental grasslands or mixed forests, the effects of understorey plant communities on changes in soil organic carbon (SOC) storage in planted forests remain unclear, especially for monoculture plantations. Therefore, based on field observations in monoculture plantations on the Loess Plateau in China, we investigated the direct effects of understorey species richness (USR) and plantation age on SOC storage, and identified the indirect effects of understorey legume species richness (ULSR) and soil moisture (SM) mediated by USR. Results indicated that plantation age and USR significantly increased SOC sequestration with almost equal effects. The changes in the relationship between USR and SOC storage varied along the water availability gradient, from significantly positive (in plots with SM ≤11.14%) to insignificant (in plots with SM >11.14%). We observed that ULSR could increase SOC sequestration by promoting USR, while SM had negative and positive effects on ULSR and USR, respectively. Our findings can provide insights into plantation management in semiarid regions: Thinning mature plantations and introducing understorey legumes can increase SOC sequestration and maintain water resource sustainability.

Tree diversity and identity modulate the growth response of thermophilous deciduous forests to climate warming

Tree diversity and species identity are known to play an important role in modulating forest productivity and its capacity to buffer the effects of climatic events. The FunDivEurope exploratory platform allowed us to analyse this modulating effect in a medium‐term time span, after an abrupt rise to a new stable level of the average summer temperature of ca 2°C, in Mediterranean forests in central Italy.This paper aims to answer the following questions: 1) did increasing temperature and drought events affect the growth of thermophilous deciduous forests? 2) Was this effect buffered in mixed stands compared to monocultures? 3) Did co‐occurring tree species with different ecological characteristics, from more mesophilous to more xerophilous, have different responses?In 2012 and 2017, wood cores were collected from 659 trees in 36 plots representative of thermophilous deciduous forests. The selected tree species were Castanea sativa, Ostrya carpinifolia, Quercus cerris, Quercus ilex and Quercus petraea. In the sampling plots, they were present in pure stands and mixtures from two to four species. After measuring annual rings on cores, chronologies of basal area increment were built, and inventory data were used to estimate tree growth. Results showed a strong reduction of growth, lasting at least 18 years, after the temperature rise. Tree diversity significantly reduced the growth drop after the sudden and stable rise in summer average temperature. Tree mixture effect on growth stability appeared to be dependent on the tree species present in the mixture.Temperature rise and associated drought events, even without changes in rainfall, are one of the main challenges that European forests will face in the current scenarios of climate change. Tree diversity can buffer the effects of climate change over periods of at least 15 years and should be considered in forest management plans.

Tree mixtures mediate negative effects of introduced tree species on bird taxonomic and functional diversity

Abstract Recent biodiversity loss has emphasized the necessity to critically evaluate the consequences of human alterations of forest ecosystems. Stand diversification via tree species mixtures and the use of non‐native trees are two such alterations currently gaining importance as climate change adaptations. However, the effects of local versus regional tree mixing on associated biodiversity and notably the modifying role of tree species growing outside their natural range remain poorly understood. We assessed how monocultures and mixtures of native and introduced tree species influence the taxonomic and functional diversity of bird communities at stand and landscape scales in north‐west Germany. We focused on the dominant natural tree species (Fagus sylvatica) and economically important conifer species planted outside their natural range (the native Picea abies and non‐native Pseudotsuga menziesii). We found that bird species richness and functional diversity were generally higher in pure and mixed stands of native F. sylvatica than in pure conifer stands, especially in comparison to non‐native P. menziesii. These differences were particularly strong at the landscape scale. Pure conifer stands harboured only a reduced set of functionally similar bird species. Structural diversity based on tree microhabitat availability emerged as a key predictor of bird diversity. Synthesis and applications. Our study suggests that tree species mixtures do not necessarily increase bird diversity compared to pure stands of native trees, but can promote bird diversity relative to pure stands of species planted outside their natural range. Moreover, local mixtures, rather than a mosaic of pure stands, may promote bird diversity also at the landscape scale. By contrast, pure stands of tree species planted outside their natural range can increase biotic homogenization of forest birds. Promoting structural diversity of microhabitats via tree retention and ensuring that non‐native trees are planted in mixtures with native trees may alleviate potential limitations of climate change‐oriented management for biodiversity.

Software Defect Prediction and Analysis Using Enhanced Random Forest (extRF) Technique: A Business Process Management and Improvement Concept in IOT-Based Application Processing Environment

Software defect prediction is a thriving study area in the realm of software engineering and processing in the IOT-based environment. Defect prediction creates a list of defective source code artifacts so that quality assurance companies may successfully assign limited methods for certifying programming things by investing more effort into the bad source code. Defect prediction can assist estimate maintenance times, which can help with quality assurance, dependability, security, and cost reduction. Many predictions in IOT-based processing environment and business process management and enhancement challenges still exist in defect expectation ponders, and there are various noteworthy concerns. In addition, it is difficult to apply these methodologies practically because most of the investigations verified in open-source programming ventures with the goal that present forecast models might not work for other programming items including business programming. Investigating security issues in cross-project deformity expectation is required since if we have more accessible restrictive datasets, the assessment of forecast models will be more stable. In general, every defect is essential regarding quality, reliability, security, and cost-effectiveness. Therefore, an enhanced and improved maintenance schedule is required to acknowledge forecasting techniques. Therefore, in this article, we have evaluated different Semi-Supervised Learning (SSL) techniques, among which Extended Random Forest (extRF) technique is one for defective system prediction. The Extended Random Forest (extRF) technique is the extended form of the Random Forest (RF), which is a supervised learning technique into semi-supervised learning getting the hang of refining every arbitrary tree given an individual-training worldview. An enhancing technique is recommended, and a weighted mixture of irregular trees creates the final forecast results.

A novel pressed coal from citrus and cooking oil wastes using fungi

Nowadays renewable energy with low prices is a global target that has taken the attention to compare alternatives energy sources with fossil fuels. Therefore, this study was established to find suitable and sustainable alternative low-cost fuels source. Cooking oil waste (COW) was mixed with non-pretreated citrus tree fibers (CTF) (0.5 mL to 1 g ratio) and pressed to formulate coal (CTF/COW). Otherwise, this mixture was subjected to in situ fungal pretreated using Aspergillus flavus isolate to simplify the mixture composition and pressed to offer in a usable form with enhancing their heating value for the first time. CTF/COW was characterized using attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIR), scanning electron microscope (SEM) and thermal analysis (TGA) before and after treatment. The fungal isolate was observed with enzyme productivity and activity of CMCase, avicelase, xylanase, mannanase, α-glucosidase, β-glucosidase, lignin peroxidase and lipase according to enzyme assays and the chemical compositions of CTF before and after fungal treatment, where the best PH for enzymes extraction was between 5 and 7. The fungal enzymes increased the heating value by about two and half folds in comparison with non-pretreated coal. Moreover, the calorific value of tCTF/COW was 43,422 kJ/kg, which was higher than CTF recorded 18,214 kJ/kg and COW recorded 39,823 kJ/kg. Our result suggests that fungal treatment of the mixture of citrus trees and cooking oil waste presents as a promising low-cost and eco-friendly coal.Graphical

Comparaison d'ensembles d'arbres à l'aide de descripteurs vectoriels basés sur les modèles de Markov cachés

Trees are among the most studied data structures and several techniques have consequently been developed for comparing two trees belonging to the same category. Until the end of year 2020, there was a serious lack of suitable metrics for comparing two weighted trees or two trees from different categories. The problem of comparing two tree sets was not also specifically addressed. These limitations have been overcome in a paper published in 2021 where a customizable metric based on hidden Markov models has been proposed for comparing two tree sets, each containing a mixture of trees belonging to various categories. Unfortunately, that metric does not allow the use of non metric-dependent classifiers which take descriptor vectors as inputs. This paper addresses this drawback by deriving a descriptor vector for each tree set using meta-information related to its corresponding models. The comparison between two tree sets is then realized by comparing their associated descriptor vectors. Classification experiments carried out on the databases FirstLast-L (FL), FirstLast-LW (FLW) and Stanford Sentiment Treebank (SSTB) respectively showed best accuracies of 99.75%, 99.75% and 87.22%. These performances are respectively 40.75% and 20.52% better than the tree Edit distance respectively for FLW and SSTB. Additional clustering experiments exhibited 54.25%, 98.75% and 75.53% of correctly clustered instances for FL, FLW and SSTB. No clustering was performed in existing work.

Intimate mixtures of Scots pine and Sitka spruce do not increase resilience to spring drought

Understanding how we can increase the resilience of forest systems to future extreme drought events is increasingly important as these events become more frequent and intense. Diversifying production forests using intimate mixtures of trees with complementary functional traits is considered as one promising silvicultural approach that may increase drought resilience. However, the direction and magnitude of the drought response of mixed-species stands relative to monospecific stands of the same species can vary with species identity, relative abundance and levels of competition in a focal tree's immediate neighbourhood. Using a long-term experiment where tree-level mortality and the neighbourhood composition of each tree was known, we assessed the radial growth response of 24-year-old Scots pine (Pinus sylvestris) and Sitka spruce (Picea sitchensis) trees in intimately mixed and monospecific stands to a short-duration, high-intensity spring drought in Scotland. Mixing proportions included 25:75, 50:50 and 75:25 of P. sylvestris and P. sitchensis. At the species level, Scots pine was more drought resistant and resilient than Sitka spruce, while Sitka spruce showed higher recovery. Surprisingly, neither pre-drought tree size nor neighbourhood competition were significantly associated with resistance or resilience to drought, and trees of both species within monospecific stands showed higher recovery and resilience than trees growing in mixed stands. Our study suggests intimate mixtures of these two species may not be an effective way to mitigate the negative impacts of future extreme spring drought events. Given that these two species comprise almost 70% of coniferous forests in the UK, our results highlight the pressing need to better understand their vulnerability to drought and the conditions under which intimate mixtures of these species could be beneficial or detrimental. Such knowledge is essential if we are to enable forest managers to effectively plan how to adapt these forests to the challenges of a changing climate.

INCREMENTO, ALOMETRÍA Y SOBREVIVENCIA DE PLÁNTULAS DE Avicennia germinans L. EN CÁRDENAS, TABASCO , MEXICO

<p><strong>Background. </strong>The mangrove forest is a mixture of tree and shrub species which inhabit the coastal areas of the tropics and subtropics, around estuaries and coastal lagoons, near the mouths of rivers, with another different capacities than the tolerance of salinity. Despite its ecological and social importance, it is one of the ecosystems most threatened by changes in land use and climatic variations. <strong>Objective.</strong> Evaluate the increase in total height and basal diameter in the dry and rainy period in <em>Avicennia germinans</em> L. seedlings, from the nursery and from natural regeneration. <strong>Methodology.</strong> In ten sampling units (SU) the total height (At), basal diameter (Db) and the survival rate (%) of the reforested individuals were recorded. In each SU, three Sub-SU (SSU) were installed where only the first two attributes were recorded for natural repopulation. The measurements were carried out in three stages during one year (M1, M2 and M3). <strong>Results</strong>. The mean annual increase in reforestation was 1.14 cm in Db and 58.8 cm in At. SU 4 was the one that reported the greatest increase in Db (1.87 cm) and At (132.6 cm), while the lowest values were presented in SU 9. The growth relationship between Db and At was statistically significant (p ≤ 0.05). Reforestation survival decreased from 73.2% to 52.7% during the evaluation period. The highest growth in Db, At and survival were in the SU´s where the water flow is greater and with a canopy gap is larger. Natural regeneration had a lower mean annual increase in both Db (0.51 cm) and At (37.2 cm). <strong>Implications.</strong> This novel information provides the basis for the planning, management and conservation of <em>A. germinans</em> in the southeast of Mexico. <strong>Conclusion</strong>. The time of measurement and the ecological differences between sampling units significantly influence the dasometric increase of <em>A. germinans</em>. The reforested individuals show a greater annual increase in Db and At compared to those of natural regeneration.</p>

SSRs MARKERS REVEAL HIGH GENETIC DIVERSITY AND LIMITED DIFFERENTIATION AMONG POPULATIONS OF NATIVE GUATEMALAN AVOCADO

Even though Guatemala is considered one of the three domestication centres of the avocado (Persea americana Mill), little is known about the genetic diversity of its native populations. This is the first study to explore avocado genetic diversity and population structure in native dispersal areas using microsatellite markers. We sampled 189 avocado trees grown from seeds in eight geographical populations, and 12 microsatellite loci were tested for diversity. There were a total of 289 alleles found throughout the 12 loci, with an average of 23.83 alleles per locus. The average observed and expected heterozygosity were 0.53 and 0.83, respectively. The analysis of molecular variance revealed that the eight populations comprised around 2% of the variation. Five of the 28 G'ST(Nei) pairwise comparisons indicated no genetic difference. We discovered a mixture of avocado trees from various populations using unweighted pair group method with arithmetic mean (UPGMA) hierarchical cluster analysis. The sampled individuals were classified into three main genetic clusters by the model-based STRUCTURE and discriminant analysis of principal components (DAPC). The weak genetic structure exhibited by mixing avocado trees from different populations could be mainly attributed to high human-mediated gene flow (Nm = 12.25) due to avocado's importance in food, culture, and Guatemala's religion. The high genetic diversity found in the avocado germplasm suggests that it might be a valuable source of variable alleles that could be used in breeding programs for this crop in Guatemala.

Carbon allocation and tree diversity: shifts in autotrophic respiration in tree mixtures compared to monocultures

Mixed species forests are known to have a higher gross primary productivity (GPP) and net primary productivity (NPP) than forests containing only one single tree species. Trees growing in mixtures are characterized by higher autotrophic respiration (Ra), this results in a lower carbon use efficiency of mixed species forests compared to monocultures. The pathway responsible for the high quantities of carbon lost through respiratory pathways is still unclear. Here, we present the only existing measurements evaluating tree mixture effects based on stem CO2 efflux (Estem), scaled to woody respiration (Rw) on stand level. We conducted predawn Estem measurements on five tree species in an experimental tree plantation in Central Panama. Estem was scaled to the entire plot level woody respiration (Rw). Annual Rw was on average 0.25 ± 0.08 Mg C ha− 1 in the monocultures and 0.28 ± 0.10 Mg C ha− 1 in mixed species stands. In mixtures, annual Ra was more than three times higher than in monocultures. As mean Rw was almost constant across the mixture types and Ra varied largely, leads to the conclusion that mixed species plots allocate a higher amount of carbon toward respiratory processes in leaves and roots. This was supported by no significant differences in the mixture effects on the growth respiration relationship.

Patterns of belowground overyielding and fine‐root biomass in native and exotic angiosperms and gymnosperms

Mixing tree species can lead to more productive forests, but how belowground productivity is affected by mixtures of trees of diverse phylogenetic and eco‐evolutionary histories is unclear. Here, we examine how species origin and phylogeny affect belowground productivity in tree communities of varied richness and functional diversity. We measured standing fine‐root biomass and annual fine‐root production across 41 assemblages of 12 tree species, representing both angiosperms and gymnosperms originating from North America and Europe. Increasing functional diversity of mixtures stimulated overyielding of annual production but did not affect standing biomass. In general, annual productivity of mixtures of species that were less productive in monoculture had neutral (angiosperms) to positive (North American species: +16%) responses to mixing, whereas annual productivity of mixtures of species that were more productive in monoculture had neutral (European species) to negative (gymnosperms: −6%) responses to mixing. These differences translated into angiosperm mixtures overyielding in standing biomass by 16% but no effects of mixing on gymnosperm mixtures. The trends we observed between North American and European species annual production were reversed when considering standing biomass. European mixtures had 14% more standing biomass and North American mixtures had 10% less standing biomass than expected from monocultures.Our study offers a rare examination of the combined roles of origin and phylogeny in forest fine‐root productivity, and suggests varied consequences of biodiversity change for forest belowground productivity based on composition. In North America, belowground productivity of young forests composed of angiosperms and native tree species may be more tightly linked to diversity than that of forests dominated by gymnosperms or European species. This suggests that increased diversity may lead to the greatest enhancement of belowground productivity in native, North American forests dominated by angiosperms, but also that declines in diversity may be felt most strongly in these forests as well.

Advantage of mixed trees in the trade-off between soil water storage and tree biomass: A meta-analysis from artificially planted forests in Chinese Loess Plateau

Afforestation is an effective measure to combat land degradation and mitigate climate change. However, afforestation tends to consume a tremendous amount of soil moisture while increasing vegetation biomass and coverage. Although convincing evidence indicates that mixed trees have higher resistance and resilience to climate change and natural disturbance than pure trees, it is unclear how tree mixtures affect the relationship between soil water storage and tree biomass. By conducting a meta-analysis of 86 observations from 27 studies, we showed that there was a trade-off between soil water storage and tree biomass in artificially planted trees on the Loess Plateau, with an average root mean square deviation (RMSD) value of 0.22. The RMSD value between soil water storage and tree biomass for mixed trees was significantly lower than that for pure trees, and the relative benefits of the trade-off were biased toward soil water storage. In dry areas (aridity index (AI) < 0.3), the RMSD value between soil water storage and tree biomass of artificially planted trees was the highest, and this value of mixed trees was significantly lower than that of pure trees. In terms of different plantation ages, the RMSD value between soil water storage and tree biomass for mixed trees was significantly lower than that for pure trees in plantations aged >20 years. Additionally, RMSD values between soil water storage and tree biomass under different afforestation patterns were negatively correlated with the initial water storage and soil organic carbon content. Our results show that tree mixtures optimize the trade-off between soil water storage and tree biomass in arid and semiarid areas.

MoËT: Mixture of Expert Trees and its application to verifiable reinforcement learning

Rapid advancements in deep learning have led to many recent breakthroughs. While deep learning models achieve superior performance, often statistically better than humans, their adoption into safety-critical settings, such as healthcare or self-driving cars is hindered by their inability to provide safety guarantees or to expose the inner workings of the model in a human understandable form. We present MoËT, a novel model based on Mixture of Experts, consisting of decision tree experts and a generalized linear model gating function. Thanks to such gating function the model is more expressive than the standard decision tree. To support non-differentiable decision trees as experts, we formulate a novel training procedure. In addition, we introduce a hard thresholding version, MoËTh, in which predictions are made solely by a single expert chosen via the gating function. Thanks to that property, MoËTh allows each prediction to be easily decomposed into a set of logical rules in a form which can be easily verified. While MoËT is a general use model, we illustrate its power in the reinforcement learning setting. By training MoËT models using an imitation learning procedure on deep RL agents we outperform the previous state-of-the-art technique based on decision trees while preserving the verifiability of the models. Moreover, we show that MoËT can also be used in real-world supervised problems on which it outperforms other verifiable machine learning models.

Effect of Environmental Planning on Elderly Individual Quality of Life in Severe Cold Regions: A Case Study in Northeastern China

With the development of urbanization and the ageing population, the improvement of the urban environment and the quality of life (QOL) of the elderly in cities with a cold climate have become critical issues to be addressed. However, only a few studies have focused on this aspect. According to a review of the literature, the contents of the built environment (BE) in severe cold regions are defined as thirteen key factors of four categories (density, environmental aesthetics, outdoor environment, and accessibility) and the QOL of old people consists of three aspects (residential, health, and social satisfaction). This study explores how BE variables are associated with the QOL of older adults by using ordered logit and gologit2 models. The data consist of the results of 1945 questionnaires from field surveys in 11 different residential areas, across two cities in northeastern China. The results show: (1) Walkability in winter, distance to a public park of 400–1000 m, outdoor shelters and seating, less than five buses available, and a mixture of evergreen and deciduous trees are five of the most important variables of BE that have a significant positive impact on QOL compared with other climatic regions; (2) “Pocket parks” and pedestrian walkway safety are appropriate approaches to improve wellbeing under local economic conditions. For public transportation, metro and rail transit systems are encouraged, and some rules are needed to reduce the number of buses in harsh weather conditions; (3) Compared with spatial distribution in other climates, the scope of a 15 min city should be less than 1km in severe cold areas. From the findings, we conclude that there are six possible pattern languages to improve the urban environment, and they can provide information for further study on environmental planning in severe cold regions.

Soil bacterial community responses to cadmium and lead stabilization during ecological restoration of an abandoned mine

AbstractEcological restoration refers to the gradual recovery of damaged ecosystems by utilizing their self‐recovery capacity and artificial measures. It is considered as an effective technique to alleviate heavy metal pollution in open‐pit mining soils. However, little is known about the stability of heavy metals and soil bacterial responses in artificially restored soil‐plant systems. In this study, different vegetation restoration strategies were established in the Dabaoshan mining area, China, and the accumulation and transfer of Cd/Pb in the soil‐plant system and the responses of the soil bacterial community were investigated. Results showed that ecological restoration with a combination of trees, shrubs and grasses/herbs could increase soil cation‐exchange capacity and organic matter content, but not soil pH. The mixture of trees, shrubs and grasses/herbs was most effective for reducing the available Pb content to 33.7% of the content in the control, and the mixture of trees and grasses/herbs was beneficial in reducing Cd to 60.4% of the content in the control. Data showed that ecological restoration could change the quantity, composition and community structure of soil microorganisms. The soils in which a mixture of trees, shrubs and grasses/herbs were grown had the greatest abundance and diversity of bacteria; the abundances of Proteobacteria increased by 12% and Actinobacteria by 5% from those of the control. Plant coverage, soil available Cd content, and organic matter emerged as major determinants of bacterial community composition. This study demonstrates a promising remediation strategy for limiting Cd/Pb mobility in mining areas.

Visualization, benchmarking and characterization of nested single-cell heterogeneity as dynamic forest mixtures.

A major topic of debate in developmental biology centers on whether development is continuous, discontinuous, or a mixture of both. Pseudo-time trajectory models, optimal for visualizing cellular progression, model cell transitions as continuous state manifolds and do not explicitly model real-time, complex, heterogeneous systems and are challenging for benchmarking with temporal models. We present a data-driven framework that addresses these limitations with temporal single-cell data collected at discrete time points as inputs and a mixture of dependent minimum spanning trees (MSTs) as outputs, denoted as dynamic spanning forest mixtures (DSFMix). DSFMix uses decision-tree models to select genes that account for variations in multimodality, skewness and time. The genes are subsequently used to build the forest using tree agglomerative hierarchical clustering and dynamic branch cutting. We first motivate the use of forest-based algorithms compared to single-tree approaches for visualizing and characterizing developmental processes. We next benchmark DSFMix to pseudo-time and temporal approaches in terms of feature selection, time correlation, and network similarity. Finally, we demonstrate how DSFMix can be used to visualize, compare and characterize complex relationships during biological processes such as epithelial-mesenchymal transition, spermatogenesis, stem cell pluripotency, early transcriptional response from hormones and immune response to coronavirus disease. Our results indicate that the expression of genes during normal development exhibits a high proportion of non-uniformly distributed profiles that are mostly right-skewed and multimodal; the latter being a characteristic of major steady states during development. Our study also identifies and validates gene signatures driving complex dynamic processes during somatic or germline differentiation.

Functionally diverse tree stands reduce herbaceous diversity and productivity via canopy packing

Abstract There is extensive experimental evidence for the importance of biodiversity in sustaining ecosystem functioning. However, such experiments typically prevent immigration by continuously removing non‐target species, thereby questioning the generality of these findings to real‐world ecosystems. This is particularly true in forest ecosystems where understorey herbaceous species are key biodiversity components but are usually weeded in tree diversity experiments. Consequently, little is known about how tree diversity influences the natural dynamics of understorey herbaceous layers. We conducted a 3‐year non‐weeded tree diversity experiment composed of eight woody species differing widely in plant economic strategies. We examined how the functional diversity and identity of tree species mixtures drive the temporal dynamics of understorey productivity, functional diversity and composition through canopy packing (CP). Tree mixtures with high functional diversity experienced increased CP over time, thereby decreasing understorey productivity and diversity. Furthermore, herbaceous communities were dominated by species with functional traits typical of low‐light conditions [lower community‐weighted mean (CWM) of maximum plant height, but larger CWM of specific leaf area] in response to increased CP. Our results provide mechanistic insights into the role of tree functional diversity in shaping the dynamics of biomass, functional diversity and composition of the understorey herbaceous layer during the early successional period. It is expected that the effects of tree functional diversity would also be relevant over time due to the increasing usage of canopy space. This study highlights the significance of natural community processes in determining the effects of tree diversity on the temporal dynamics of previously neglected ecosystem structures and functioning. Read the free Plain Language Summary for this article on the Journal blog.

Effects of Mixture Mode on the Canopy Bidirectional Reflectance of Coniferous–Broadleaved Mixed Plantations

One of the main initiatives for China to achieve the goal of being carbon neutral before 2060 is transforming monocultures into mixed plantations in subtropical China, because mixed forests possess a higher quality than monocultures in various ways. Very high spatial resolution (VHR) satellite imagery is very promising to precisely monitor the transformation process under the premise of clarifying the canopy reflectance anisotropy of mixed plantations. However, it is almost impossible to understand the canopy reflectance anisotropy of mixed plantations with real satellite data due to the extreme lack of multiangular VHR satellite images. In this study, the effects of the mixture mode on the canopy bidirectional reflectance factor (BRF) were comprehensively analyzed with simulated VHR images. The three-dimensional (3D) Discrete Anisotropic Radiative Transfer model (DART) was used to construct a pure coniferous scene, a pure broadleaved scene, and 27 coniferous–broadleaved mixed plantation scenes containing 3 mixture patterns (i.e., mixed by single trees, mixed by stripes, and mixed by patches) and 9 mixing proportions (i.e., from 10% to 90% with the interval of 10%), and to simulate red (R) and near-infrared (NIR) VHR images for these 3D scenes at both the solar principal plane (SPP) and perpendicular plane (PP) under different solar-viewing geometries. Negative correlations were generally found between the canopy BRF and the ratio of conifers in a mixed stand. The anisotropy of conifer dominated plantations is more prominent than broadleaf dominated plantations, especially for the single tree mixture. Although the level of anisotropy is much lower for PP than SPP, it should not be ignored, especially for the R band. Observations under large viewing zenith angles at PP are more preferred to study the effect of mixing proportions, followed by forward observations at SPP. The R band image has higher potential to distinguish mixture patterns for broadleaf-dominated situations, while the NIR band image has a higher potential for conifer-dominated situations. Furthermore, the canopy BRF generally increases with the solar zenith angle, and one meter can be considered as the optimal spatial resolution for the optical monitoring of the mixture mode. The findings of the current study add some valuable theoretical knowledge for the accurate monitoring of coniferous–broadleaved mixed plantations with VHR imagery.

A revision of theRostania occultata(Collemataceae) complex in Fennoscandia

AbstractTheRostania occultataspecies complex (‘Collema occultatums. lat.’) is revised in Fennoscandia and found to consist of four species, all epiphytes on deciduous trees:Rostania effusaA. Košuth., M. Westb. &amp; Wedin sp. nov.,R. occultata(Bagl.) Otáloraet al.,R. pallidaA. Košuth., M. Westb. &amp; Wedin sp. nov. andR. populina(Th. Fr.) A. Košuth., M. Westb. &amp; Wedin comb. nov.Rostania effusaandR. pallidaare newly described from humid habitats in old-growth boreal coniferous forests, usually with a mixture of deciduous trees, and from similar areas in the subalpine birch-dominated forests of Fennoscandia.Rostania effusais characterized by apothecia with red-brown apothecium discs and an excipulum thallinum with a simple pseudocortex and cubic to oblong, muriform spores.Rostania pallidahas apothecia with whitish to pale yellowish discs and an excipulum thallinum with a distinct cellular pseudocortex, and ellipsoid, muriform mature spores that are often constricted at the centre. A lectotype is designated forCollema quadratumJ. Lahm ex Körb. The new combinationRostania populinais introduced for the species recognized until now as the varietyRostania occultatavar.populina(Th. Fr.) Perlmutter &amp; Rivas Plata. A key to the six species inRostanias. str. is included.

Root litter decomposition in a sub-Sahelian agroforestry parkland dominated by Faidherbia albida

In agroforestry systems, fine roots grow at several depths due to the mixture of trees and annual crops. The decomposition of fine roots contributes to soil organic carbon stocks and may impact soil fertility, particularly in poor soils, such as those encountered in sub-Sahelian regions. The aim of our study was to measure the decomposition rate of root litter from annual and perennial species according to soil depth and location under and far from trees in a sub-Sahelian agroforestry parkland.Soil characteristics under and far from the trees were analysed from topsoil to 200 cm depth. Faidherbia tree, pearl millet and cowpea root litter samples were buried in litterbags for 15 months at 20, 40, 90 and 180 cm depths.Root litter decomposition was mainly impacted by soil moisture and soil depth. Faidherbia decomposed more slowly (36 ± 12% remaining mass after 15 months) than cowpea and pearl millet roots (23 ± 7% and 29 ± 11% respectively). Pearl millet aboveground biomass, at harvesting time, was twice as high under (992 g m−2) than far (433 g m−2) from the tree, and belowground biomass (0–200 cm of depth) was 30.9 g m−2 and 19.6 g m−2 under and far from the tree, respectively. Faidherbia fine roots contributed slightly (p-value < 0.1) to higher stocks of C under the tree (7761 ± 346 g m−2) than far from it (5425 ± 558 g m−2) and from 0 cm down to 200 cm depth.