Canopy Diversity Research Articles

Bridging real and simulated data for cross-spatial- resolution vegetation segmentation with application to rice crops

Accurate image segmentation is essential for image-based estimation of vegetation canopy traits, as it minimizes background interference. However, existing segmentation models often lack the generalization ability to effectively tackle both ground-based and aerial images across a wide range of spatial resolutions. To address this limitation, a cross-spatial-resolution image segmentation model for rice crop was trained using the integration of in-situ and in silico multi-resolution images. We collected more than 3,000 RGB images (real set) covering 17 different resolutions reflecting diverse canopy structures, illumination conditions and background in rice fields, with vegetation pixels annotated manually. Using the previously developed Digital Plant Phenotyping Platform, we created a simulated dataset (sim set) including 10,000 RGB images with resolutions ranging from 0.5 to 3.5 mm/pixel, accompanied by corresponding mask labels. By employing a domain adaptation technique, the simulated images were further transformed into visually realistic images while preserving the original labels, creating a simulated-to-realistic dataset (sim2real set). Building upon a SegFormer deep learning model, we demonstrated that training with multi-resolution samples led to more generalized segmentation results than single-resolution training on the real dataset. Our exploration of various integration strategies revealed that a training set of 9,600 sim2real images combined with only 60 real images achieved the same segmentation accuracy as 2,400 real images (IoU = 0.819, F1 = 0.901). Moreover, combining 2,400 real images and 1,200 sim2real images resulted in the best performing model, effective against six challenging situations, such as specular reflections and shadows. Compared with models trained with single-resolution samples and an established model (i.e., VegANN), our model effectively improved the estimation of both green fraction and green area index across spatial resoultions. The strategy of bridging real and simulated data for cross-resolution deep learning model is expected to be applicable to other crops. The best trained model is available at https://github.com/PheniX-Lab/crossGSD-seg.

Canopy temperatures strongly overestimate leaf thermal safety margins of tropical trees.

Current estimates of temperature effects on plants mostly rely on air temperature, although it can significantly deviate from leaf temperature (Tleaf). To address this, some studies have used canopy temperature (Tcan). However, Tcan fails to capture the fine-scale variation in Tleaf among leaves and species in diverse canopies. We used infrared radiometers to study Tleaf and Tcan and how they deviate from air temperature (ΔTleaf and ΔTcan) in multispecies tropical tree plantations at three sites along an elevation and temperature gradient in Rwanda. Our results showed high Tleaf (up to c. 50°C) and ΔTleaf (on average 8-10°C and up to c.20°C) of sun-exposed leaves during 10:00 h-15:00 h, being close to or exceeding photosynthetic heat tolerance thresholds. These values greatly exceeded simultaneously measured values of Tcan and ΔTcan, respectively, leading to strongly overestimated leaf thermal safety margins if basing those on Tcan data. Stomatal conductance and leaf size affected Tleaf and Tcan in line with their expected influences on leaf energy balance. Our findings highlight the importance of leaf traits for leaf thermoregulation and show that monitoring Tcan is not enough to capture the peak temperatures and heat stress experienced by individual leaves of different species in tropical forest canopies.

Diversity-enhanced canopy space occupation and leaf functional diversity jointly promote overyielding in tropical tree communities

Understanding the mechanisms that drive biodiversity-productivity relationships is critical for guiding forest restoration. Although complementarity among trees in the canopy space has been suggested as a key mechanism for greater productivity in mixed-species tree communities, empirical evidence remains limited. Here, we used data from a tropical tree diversity experiment to disentangle the effects of tree species richness and community functional characteristics (community-weighted mean and functional diversity of leaf traits) on canopy space filling, and how these effects are related to overyielding. We found that canopy space filling was largely explained by species identity effects rather than tree diversity effects. Communities with a high abundance of species with a conservative resource-use strategy were those with most densely packed canopies. Across monocultures and mixtures, a higher canopy space filling translated into an enhanced wood productivity. Importantly, most communities (83 %) produced more wood volume than the average of their constituent species in monoculture (i.e. most communities overyielded). Our results show that overyielding increased with leaf functional diversity and positive net biodiversity effects on canopy space filling, which mainly arose due to a high taxonomic diversity. These findings suggest that both taxonomic diversity-enhanced canopy space filling and canopy leaf diversity are important drivers for overyielding in mixed-species forests. Consequently, restoration initiatives should promote stands with functionally diverse canopies by selecting tree species with large interspecific differences in leaf nutrition, as well as leaf and branch morphology to optimize carbon capture in young forest stands.

Research on Individual Tree Canopy Segmentation of Camellia oleifera Based on a UAV-LiDAR System

In consideration of the limited accuracy of individual tree canopy segmentation algorithms due to the diverse canopy structure and complex environments in mountainous and hilly areas, this study optimized the segmentation parameters of three algorithms for individual tree canopy segmentation of Camellia oleifera in such environments by analyzing their respective parameters. Utilizing an Unmanned Aerial Vehicle-Light Detecting and Ranging (UAV-LiDAR) system, we obtained Canopy Height Models (CHM) of Camellia oleifera canopies based on Digital Elevation Models (DEM) and Digital Surface Models (DSM). Subsequently, we investigated the effects of CHM segmentation, point cloud clustering segmentation, and layer stacking fitting segmentation on Camellia oleifera canopies across different research areas. Additionally, combining ground survey data from forest lands with visual interpretation of UAV orthophoto images, we evaluated the performance of these three segmentation algorithms in terms of the F-score as an evaluation indicator for individual tree canopy segmentation accuracy. Combined with the Cloth Simulation Filter (CSF) filtering algorithm after removing the ground point cloud, our findings indicate that among different camellia densities and terrain environments, the point cloud clustering segmentation algorithm achieved the highest segmentation accuracy at 93%, followed by CHM segmentation at 88% and the layer stacking fitting segmentation method at 84%. By analyzing the data from UAV-LiDAR technology involving various land and Camellia oleifera planting types, we verified the applicability of these three segmentation algorithms for extracting camellia canopies. In conclusion, this study holds significant importance for accurately delineating camellia canopies within mountainous hilly environments while providing valuable insights for further research in related fields.

Using a Machine Learning Approach to Classify the Degree of Forest Management

A prerequisite for sustainable forest management is knowing the total diversity and how management affects forests. Both are poorly studied and relate to canopy diversity and comparison with primary forests. From 2001–2004, we fogged beetles from oaks in primary and disturbed, managed sites in Białowieża (Eastern Poland) and also in distant age-class forests. Using a machine learning (ML) method (elastic net), we identified a beetle signature based on the species abundance distribution to distinguish these forest types. The beetle communities from 2001 served as training data, with 21 signature species correctly assigning the oaks to primary and different managed forests. However, the predictive quality of the signature decreased with each year due to high spatio-temporal heterogeneity and beta diversity. To improve the power of the signature, we combined the data from all years to calculate a more general model. Due to its greater complexity, this model identified 60 species that correctly classified both the studied forests and foreign forests in Central Europe, increasing the possibility of a general classification. Further research is needed to determine whether it is possible to establish a general signature-based index on a large number of samples from different years and forest types.

Tree species size class patterns portend compositional shifts and low resilience in managed northern hardwood forests

AbstractDeclining temperate forest biodiversity is a global challenge to future sustainability and resilience. Canopy tree diversity has declined in northern hardwood forests (NHFs) of the Great Lakes region since European colonization, with current tree regeneration patterns suggesting this trend may continue. However, regional (106 ha) patterns and drivers are underexplored. We used data from 141 managed NHF stands, Michigan, USA, to examine diversity indices across tree size classes (seedling, sapling, and canopy); stand‐level drivers of regeneration (seedling and sapling) diversity and individual species density; and patterns among species in relative abundances across size classes. Diversity was similar across size classes (mean asymptotic species richness of 6–7 species and <3 effective common species); however, some species contributing to sapling diversity are unlikely to contribute to future canopy diversity (Fraxinus americana and Fagus grandifolia, insect/pathogen limited; Ostrya virginiana, small maximum size). For the 11 most common species, conspecific canopy density (+, seedlings, significant for 10 species) and stand basal area (−, saplings, 3 species) most consistently associated with density; deer use, site quality, and substrate were less predictive. Patterns of relative density by size class among 18 species present on >10% of sites were consistent with species life history strategy and/or establishment/recruitment barriers. For seven species (including Tsuga canadensis, Betula alleghaniensis), relative density was lowest in the seedling layer, suggesting seedling establishment substrate and/or early shade mortality limitations. For two species (Acer saccharum, Quercus rubra), reduced sapling relative density compared with seedling or canopy strata suggests a sapling recruitment bottleneck from deer browsing/shade, whereas six species (e.g., F. grandifolia, O. virginiana, Pinus strobus) had highest relative density for saplings, suggesting sapling to canopy recruitment limitations. Lastly, seedlings were relatively most dense for Acer rubrum and Prunus spp., indicating disproportionally high seedling establishment, if not sapling or canopy recruitment, and for F. americana, consistent with recent pest‐related canopy mortality. Collectively our analyses suggest sustained low diversity and shifting composition are driven by limited local seed availability, limited seedling establishment substrate, deep shading, and abundant deer. Management aimed at overcoming these limitations may be necessary to promote future NHF resilience.

Managing a mixed sward to maintain species and functional diversity

The intensification of animal production systems to meet the increasing demand for animal products may undermine environmental sustainability. One solution is to establish pastoral environments with diverse plant functional groups, promoting sustainable intensification by enhancing ecosystem services such as nutrient cycling and soil health. However, maintaining the species diversity in such systems, particularly those with grasses and legumes, remains a challenge. Although using the critical leaf area index (LAI) and its corresponding height has proven useful in managing single-species stands, there is a need for further investigation of the criteria for managing more complex swards. This study aimed to identify the management strategies for coupling species diversity and forage production in mixed pastures containing grasses and legumes. The pastures included five species: Tifton 85 (Cynodon spp.), kikuyu grass (Cenchrus clandestinus), pintoi peanut (Arachis pintoi), white clover (Trifolium repens) and birdsfoot trefoil (Lotus corniculatus). Two management heights (17 and 23 cm) and three nitrogen fertilizer rates (50, 150, and 250 kg ha−1) were combined in a randomized complete block design, with a factorial arrangement and three replicates per treatment. The pastures were subjected to intermittent grazing with a 40% defoliation severity, and the experimental period lasted for three warm seasons (November – April) from 2020 to 2022. Forage accumulation was similar for both management heights; however, shorter heights (17 cm) reduced species diversity and higher nitrogen rates increased forage production. Tifton-85 and kikuyu grasses dominated the canopy and coexisted in similar proportions across all treatments. However, higher nitrogen application rates decreased species diversity and dissimilarity in community traits. Our findings suggest that grazing pastures at shorter heights (17 cm) can be detrimental to canopy diversity, whereas managing mixed swards at a pre-grazing height close to the critical LAI (approximately 23 cm for a predominantly Tifton 85 and kikuyu grass mixture) can promote greater species diversity without compromising forage production. Additionally, our data suggest that functional diversity is enhanced when grasses experience suboptimal nitrogen nutrition indices (NNI no greater than 0.8). However, further research is required to fully understand this relationship.

Enhancing Green Fraction Estimation in Rice and Wheat Crops: A Self-Supervised Deep Learning Semantic Segmentation Approach.

The green fraction (GF), which is the fraction of green vegetation in a given viewing direction, is closely related to the light interception ability of the crop canopy. Monitoring the dynamics of GF is therefore of great interest for breeders to identify genotypes with high radiation use efficiency. The accuracy of GF estimation depends heavily on the quality of the segmentation dataset and the accuracy of the image segmentation method. To enhance segmentation accuracy while reducing annotation costs, we developed a self-supervised strategy for deep learning semantic segmentation of rice and wheat field images with very contrasting field backgrounds. First, the Digital Plant Phenotyping Platform was used to generate large, perfectly labeled simulated field images for wheat and rice crops, considering diverse canopy structures and a wide range of environmental conditions (sim dataset). We then used the domain adaptation model cycle-consistent generative adversarial network (CycleGAN) to bridge the reality gap between the simulated and real images (real dataset), producing simulation-to-reality images (sim2real dataset). Finally, 3 different semantic segmentation models (U-Net, DeepLabV3+, and SegFormer) were trained using 3 datasets (real, sim, and sim2real datasets). The performance of the 9 training strategies was assessed using real images captured from various sites. The results showed that SegFormer trained using the sim2real dataset achieved the best segmentation performance for both rice and wheat crops (rice: Accuracy=0.940, F1-score=0.937; wheat: Accuracy=0.952, F1-score=0.935). Likewise, favorable GF estimation results were obtained using the above strategy (rice: R2=0.967, RMSE=0.048; wheat: R2=0.984, RMSE=0.028). Compared with SegFormer trained using a real dataset, the optimal strategy demonstrated greater superiority for wheat images than for rice images. This discrepancy can be partially attributed to the differences in the backgrounds of the rice and wheat fields. The uncertainty analysis indicated that our strategy could be disrupted by the inhomogeneity of pixel brightness and the presence of senescent elements in the images. In summary, our self-supervised strategy addresses the issues of high cost and uncertain annotation accuracy during dataset creation, ultimately enhancing GF estimation accuracy for rice and wheat field images. The best weights we trained in wheat and rice are available: https://github.com/PheniX-Lab/sim2real-seg.

Analysis of Vegetation Analysis in The existing Areas Around in The Landslides in The City of Palopo

The composition and structure of vegetation is one of the parameters that must be considered in forest planning activities. It can also be defined that the structure of vegetation as a result of spatial planning by the components of the stand and the life form of the vegetation which is described through the conditions of diameter, height, distribution in space, canopy diversity, and species continuity. In order to be able to withstand the occurrence of landslides, especially those in sloping areas, it is very important to analyze the vegetation to determine the composition and structure of vegetation types so that the forest is maintained (Fahrul, 2007). The purpose of this study was to determine vegetation in the existing area around the landslides in Palopo city. Research methods. The method of determining plots is purposive sampling, to find out vegetation and tree classification based on the growth rate of the method, namely by making observation plots and placing them by census at the top of 12 landslide points with a size of 20 m x 20 m for trees, 10 m x 10 m for poles, 5 m x 5 m for saplings and 2 m x 2 m for seedlings. The results obtained for the growth rate of trees found 35 species with the highest IVI Litsea sp 95.94%, the growth rate of poles found 28 species with the highest IVI Litsea sp 71.15%, the growth rate of saplings found 62 species with the highest IVI Cinnamomum camphora 45.62 %, and the level of seedlings found 51 species with the highest IVI Nephrolepis cordifolia 40.78%. The biodiversity index found a sapling growth rate with the highest H' value of 3.41 in the high species diversity category. Likewise the highest evenness index on saplings with an E' value of 0.59 is in medium level of evenness.

Host-tree selection by the ant garden-initiating arboreal ponerine Neoponera goeldii.

Host-tree selection by the ant garden-initiating arboreal ponerine Neoponera goeldii.

Editorial: Understanding patterns and mechanisms of forest canopy diversity and ecosystem functions in a changing world

Editorial: Understanding patterns and mechanisms of forest canopy diversity and ecosystem functions in a changing world

Differences in canopy and understorey diversities after the eruptions of Mount Usu, northern Japan — Impacts of early forest management

Evaluating the effects of management on successional trajectories, plant composition, and diversity has been difficult due to the scarcity of long-term studies. This study examined the composition and diversity of species in natural and artificially regenerated forests at two eruption sites of Mount Usu, northern Japan, during 2015–2019, to compare the effects of active and passive management. The two sites are Yosomi, damaged by the 1910 eruptions, and the summit, damaged by the 1977–78 eruptions. Various natural and artificial forests developed at both sites, whose species composition was analyzed by non-metric multidimensional scaling to measure similarity between the forest types, and whose diversity was compared by the true diversity index, showing the effective number of species, from order 0 (presence-absence) to order 2 (weighted species) for two layers: the canopy (woody species with DBH > 3 cm) and understorey (< 2 m high plants). Canopy diversity was measured by stem density in five 10 m × 10 m plots in each forest type, and understory diversity was measured by shoot density in four 1 m × 1 m quadrats in each plot. The canopy and understorey species compositions were distinct between the forest types, but the canopy was more affected by management than the understorey, indicating that early forest management had long-term effects on species composition. Species composition of the plantations resembled those of the natural forests when the plantations had patchy spatial structure. The naturally regenerated forests showed the highest diversities at both eruption sites, while the plantations displayed low diversities, except in one case, when the plantation showed heterogeneous forest structure. The plantations changed their species composition slowly and did not transform into natural forests. In conclusion, we suggest using a patchy plantation design with some space between patches instead of dense planting, to create resilient, diverse, and native forests after disturbances.

Spring phenological variability promoted by topography and vegetation assembly processes in a temperate forest landscape

Plant phenological processes significantly impact ecosystem function and services across multiple ecological scales and are widely viewed to be among the most sensitive indicators of global environmental change. Remote sensing has crucially expanded our understanding of phenological variability. Yet, we continue to lack a complete mechanistic understanding of phenology and its variability and drivers, which is important to the development of predictive models, especially under continued environmental change. We combined field inventories and Land Surface Phenology (LSP) approaches, using 36 years of Landsat phenological observations, to characterize the degree to which long-term spring greenup patterns are shaped by topography, vegetation, and topographically structured vegetation assembly processes within a dissected forest landscape in southeastern Ohio. We found temporal and spatial variability among the field samples where greenup patterns displayed rapid change (18 total days) over relatively short distances (<1 km). Slope position explained the most variation (35%), where the bases of hills displayed the latest timing in spring greenup. However, we found that differences in terrain aspect and slope influenced canopy diversity, height, and composition of forest stands, influencing plant community processes that support heterogeneity in spring leaf-out timing. Understanding how forest phenology is shaped by direct and often complex interacting processes that influence the distribution of species assemblages supports new insight into phenological variability and, importantly, the management of forest ecosystems facing continued environmental change.

Distribution and photosynthetic assimilation of rosulate aroid epiphytes in a Costa Rican lowland rainforest

Relatively few studies are available to characterize the distribution, abundance and ecophysiology of aroid epiphytes, distinct from aroid hemiepiphytes which are more common and abundant. The rosulate growth form is restricted to a relatively small number of aroid species. Field and experimental growth studies and ecophysiological measurements on rosulate aroids were carried out at La Selva Biological Station in the premontane rainforest of the Atlantic lowlands of Costa Rica. Rosulate aroids occur in habitats from forest understory to high canopy, and from old growth wet forest to secondary forest in Costa Rica. The distribution of rosulate and acaulescent aroid epiphytes were determined in multiple stands of old growth and secondary tropical forests at La Selva. Anthurium upalense and Philodendron wendlandii exhibited a preference for upper canopies on trees over 50 cm dbh where irradiance levels are high for much of the day. Anthurium consobrinum and A. bakeri occurred lower in the canopy in more shaded positions. To evaluate how these habitat preferences are related to plant traits, controlled shadehouse growth experiments were conducted to characterize species response to different ambient light environments. We applied conditions of high light (50% full sun), medium light (10% full sun), and low light (2% full sun) to simulate a gradient of canopy and understory light environments. Anthurium consobrinum and A. bakeri exhibited photosynthetic traits characteristic of shade-adapted understory epiphytes. In contrast, A. upalense and Ph. wendlandii, typically high canopy species, had maximum photosynthetic rates of 10.5 and 8.7 µmol m−2 s−1, respectively, higher than those previously reported for other vascular epiphytes. The variability in distribution of epiphytic aroids in Costa Rican premontane rainforest is consistent with their diversity of ecological and ecophysiological traits demonstrating adaptation to diverse canopy habitats in this aroid growth form.

Latitude, paleo-history and forest size matter for Afromontane canopy beetle diversity in a world context

Tree canopies in forests host exceptional levels of biodiversity. However ecologists are still faced with vast regional gaps in need of fundamental information on the nature of tree canopy diversity. The southern Afrotemperate forests at the tip of Africa are ancient, existing today as a biogeographical string of natural remnants from long-past climate events. Their canopy arthropod fauna is scarcely known, but could provide insights into global canopy diversity patterns. As part of the broader Afromontane archipelago and southern hemispheric forests in general, they form part of the last and largest global gaps in canopy science. Here we ask how the canopy beetle diversity of these forests qualitatively and quantitatively compare with other forests around the world. We show that beetle species richness and richness per m2 are closer to temperate than tropical canopies. Estimates for beetle richness most closely matched the latitudinal equivalent Chilean temperate rainforests. However, feeding guild structure of beetles are closer in resemblance to tropical than temperate forest canopies, in line with expectations regarding the region’s paleo-history. The most diverse beetle families, Curculionidae, Staphylinidae and Chrysomelidae, were proportionately similar to both temperate and tropical forest canopies. We discuss the importance of latitude, paleo-history and forest size when considering canopy fauna in a global context.

Increasing functional diversity of the urban canopy for climate resilience: Potential tradeoffs with ecosystem services?

Cities are home to an increasing number of people who depend on urban forests to provide ecosystem services such as temperature regulation, air quality improvement and storm water abatement. Climate change may challenge the capacity of urban forests to provide these services. Intensification of heat waves, droughts and strengthening storms could lead to tree die-offs. In Quebec City, work has suggested that the urban canopy is vulnerable to future projected climates, i.e. hotter and drier summers. Compounding this threat, the exotic emerald ash borer is expected to kill 11 % of municipal trees over the next decade. Together these pressures could lead to a significant loss of canopy cover and ecosystem service provisioning in the near-term.We test whether replanting strategies for lost ash, which shift the forest community towards a more climate-tolerant canopy using a functional trait-based approach, can help to mitigate or improve ecosystem service provisioning in the near-term. Using a municipal database of urban trees, we simulate canopy growth and replacement over 20-years for three different replanting scenarios: i) ‘business-as-usual’, ii) ‘stratified’ or iii) ‘conifer-focused’ replanting strategy, and compare their delivery of ecosystem services.Results from the simulations find clear trade-offs in ecosystem service provisioning within and between replanting approaches. The ‘conifer-focused’ scenario provides the highest level of air quality improvement, storm water abatement and reduced energy demands in winter, however there are limitations on where coniferous trees can be planted in cities. In contrast, the ‘business-as-usual’ scenario achieved greater canopy cover, carbon sequestration, and high summertime cooling, but remains vulnerable to climate change. Stratifying replanting across tree functional groups results in the greatest increase to canopy diversity, intermediate levels of ecosystem service provisioning and important reduction in vulnerability to future pests . We suggest that a replanting approach focused on increasing the functional trait diversity of the urban canopy will likely confer the greatest ecosystem service benefits to the urban population and improve the resilience of the urban canopy to pests and climate pressures in the future.

How does leaf functional diversity affect the light environment in forest canopies? An in-silico biodiversity experiment

The interaction of shortwave radiation with vegetation drives basic processes of the biosphere, such as primary productivity, species interactions through light competition, and energy fluxes between the atmosphere, vegetation, and soil. Here, we aim to understand the effects of leaf functional trait diversity on canopy light absorption. We focus on the diversity of three key functional traits that influence the light-canopy interaction: leaf area index (LAI), leaf angle distribution (LAD) and leaf optical properties (LOP). We used a 3D radiative transfer model to perform an in-silico biodiversity experiment to study the effects of leaf functional diversity on a light proxy for productivity (the fraction of absorbed photosynthetically active radiation (FAPAR)) and net radiation (shortwave albedo). We found that diverse canopies had lower albedo and higher FAPAR than the average of the corresponding monoculture values. In mixtures, FAPAR was unequally re-distributed between trees with distinct traits: some plant functional types absorbed more light and some plant functional types absorbed less than in monocultures. The net biodiversity effect on absorptance was greater when combining plant functional types with more distinct leaf traits. Our results support the mechanistic understanding of overyielding effects in functionally diverse canopies and may partially explain some of the growth-promoting mechanisms in biodiversity-ecosystem functioning experiments. They can further help to account for biodiversity effects in climate models.

Harvested opening size affects cohort development and failures in a second-growth northern hardwood forest

Group selection is one potential tool in contemporary, uneven-aged silviculture for mitigating increased dominance by shade-tolerant species while continuing to meet stocking goals and harvest quotas. However, recent experimental group-selection openings in northern hardwood forests on some sites in the Upper Great Lakes region have failed to meet management goals of increased tree diversity and timely natural regeneration. Few observational studies have documented the long-term stand development of nascent cohorts following group-selection prescriptions. This study revisits a long-term group-selection experiment which previously found that opening size had little effect on regeneration diversity and found that large areas devoid of saplings and dominated by understory vegetation were common more than a decade following harvest. Our goals were to reassess the state of stand development and diversity within harvested openings, as well as look for early post-harvest indicators of regeneration success or failure after 23 years. At 23 years post-harvest, we found that opening size had little effect on regeneration diversity but rather influenced patterns of cohort development. Smaller openings (6–20 m diameter) showed signs of self-thinning, while larger openings (30–46 m diameter) showed divergent developmental patterns including both self-thinning and ongoing sapling recruitment. Most areas of regeneration failures persisted through 23 years, and the largest openings (46 m diameter) were most likely to display regeneration failure, with 42% of subplots devoid of saplings but containing dense understory vegetation. The density of understory vegetation at 2 years post-harvest had no effect on year-23 sapling density. Instead, only seedling/sapling density in year 2 correlated with regeneration success after 23 years. These results suggest that in northern hardwood forests in the upper Great Lakes region, opening creation alone may not produce the desired effects of increased canopy diversity and sustained timber yields. Canopy openings >30 m diameter appear more likely to result in partial, multi-decade regeneration failures compared to smaller openings; however, our results highlight the importance of advance regeneration for preventing these failures. Thus, simultaneously achieving management goals of increased tree diversity and adequate regenerative stocking with group selection likely requires additional inputs (e.g. herbivore protection, planting, scarification, herbicides, repeated thinning, etc.) beyond the current status quo.

Remote sensing enabled essential biodiversity variables for biodiversity assessment and monitoring: technological advancement and potentials

The strong contribution of remote sensing has led to the development of the concept of the Remote Sensing enabled Essential Biodiversity Variables which represents a set of variables that can be monitored from space. This work synthesizes current state of research and technological development in use of remote sensing enabled essential biodiversity variables. The issue of scale, satellite observation requirements and status of remote sensing have been discussed in the context of monitoring of community composition, plant functional types, vegetation structure, canopy diversity, targeted animal groups, fragmentation, disturbances and as an input for biodiversity modelling, and Earth Observations based variables. This work highlighted existing approaches for addressing community level biodiversity and discusses in the context of Earth Observations as which are key components for biodiversity monitoring strategy. Biodiversity monitoring could be improved by using new satellite sensors and the synergy of remotely sensed data from multiple sensors which are providing hyperspatial, hyperspectral and hypertemporal observations. The use of remote sensing for operational monitoring of biodiversity is still under development as existing approaches and techniques have not holistically addressed the metrics of essential biodiversity variables.

Lack of vulnerability segmentation among woody species in a diverse dry sclerophyll woodland community

Abstract Recent findings suggest that tree mortality and post‐drought recovery of gas exchange can be predicted from loss of function within the water transport system. Understanding the susceptibility of plants to hydraulic damage requires knowledge about the vulnerability of different plant organs to stress‐induced hydraulic dysfunction. This is particularly important in the context of vulnerability segmentation between plant tissues which is believed to protect more energetically ‘costly’ tissues, such as woody stems, by sacrificing ‘cheaper’ leaves early under drought conditions. Differences in vulnerability segmentation between co‐occurring plant species could explain divergent behaviours during drought, yet there are few studies considering how this characteristic may vary within a plant community. Here we investigated community‐wide vulnerability segmentation by comparing leaf/shoot and stem vulnerability in all coexistent dominant canopy and understory woody species in a diverse dry sclerophyll woodland community, including multiple angiosperms and one gymnosperm. Previously published terminal leaf/shoot vulnerability to loss of water transport capacity was compared with stem xylem vulnerability to embolism measured on the same species at the same site. We calculated hydraulic safety margins for stems to determine variation in the risk of hydraulic failure during drought among species. The xylem of all species was found to be highly resistant to hydraulic dysfunction, with only two of the eight species exhibiting significantly different vulnerability to the overall mean. No evidence of vulnerability segmentation between shoots/leaves and stems was found in seven of the eight species. Phylogenetically diverse canopy and understory species in this evergreen sclerophyll woodland appear to have evolved similar strategies of drought resistance, including low xylem vulnerability to embolism and general lack of vulnerability segmentation. This convergence in hydraulic safety indicates a lack of hydraulic niche partitioning in this woodland community. A free plain language summary can be found within the Supporting Information of this article.