Forest fragmentation impacts the seasonality of Amazonian evergreen canopies

Small forest patches and landscape-scale fragmentation exacerbate forest fire prevalence in Amazonia

Over recent decades, forest fire prevalence has increased throughout the tropics, necessitating improved understanding of the landscape-scale drivers of fire occurrence. Here, we use MapBiomas land-cover and fire scar data to evaluate relationships between forest fragmentation, land-use, and forest fire prevalence in a typically consolidated Amazonian agricultural frontier: Portal da Amazonia, Mato Grosso, Brazil. Using zero-/zero-one-inflated Beta regressions, we investigate effects of forest patch (area, shape, surrounding forest cover) and landscape-scale variables (forest edge length, land-cover composition) on forest fire occurrence and density between 1985 and 2021. We show that fire density was greatest in small, complex forest patches. Small patches (≤100 ha) were also the dominant contributors to annual, regional forest fire cover. At the landscape-scale (100 km2), forest edge length and urban land cover were positively associated with forest fire occurrence and density. Furthermore, forest fires were most likely to occur in landscapes consisting of ∼45% pasture cover, while fire density increased roughly linearly with pasture cover. Cropland cover was negatively associated with forest fire occurrence and density. Our findings indicate clear links between forest fragmentation and increased forest fire prevalence. This is cause for global concern, given that fragmentation rates throughout Amazonia are increasing, and fires are eroding the Amazon's capacity to act as a carbon sink. Efforts to minimise further fragmentation within Amazonia would likely help reduce forest fire prevalence. Within already fragmented regions, the conversion of pasture into crops, alongside targeted efforts to suppress fires within small forest patches and urbanized areas, may also limit fire prevalence.

Light quality regulates growth and flavonoid content in a widespread forest understorey medicinal species Scutellaria Baicalensis Georgi

Introduction

Introduction: Light is not only essential for plant photosynthesis and growth, but also acts as a signal to regulate its secondary metabolism. Despite the influence of light quality on the yield and flavonoid compounds in commercial crops is well-documented, its role in regulating wild understorey species, particularly medicine plants whose flavonoid biosynthesis driven by multiple spectral regions of canopy sunlight, is less understood.

Methods

To address it, we conducted a light-quality manipulation experiment on Scutellaria baicalensis Georgi, a widespread understorey medicinal species, with light-emitting diodes (LED). This study included eight treatments: UV-A (UV-A radiation), CK (control group), Green (monochromatic green light), and different combinations of blue and red light (R0B4: monochromatic blue light; R1B3: 25% Red+75% Blue light; R1B1: 50% Red+50% Blue light; R3B1: 75% Red+25% Blue light; R4B0: monochromatic red light).

Results

Our results showed that light quality significantly drove morphology, biomass accumulation, and flavonoids biosynthesis in S. baicalensis. R0B4 treatment promoted growth and flavonoids accumulation, including baicalin, and wogonoside concentrations. In contrast, UV-A radiation and green light negatively impacted these parameters compared to CK treatment. Interestingly, plant biomass and flavonoid concentrations were lower in R1B3, R1B1 and R3B1 treatments compared to monochromatic blue or red light.

Discussion

Our study found that red light may antagonize blue light-stimulated growth and flavonoids accumulation, indicating a complex crosstalk between photoreceptors. These findings highlight the importance of blue light for optimizing the yield and quality of S. baicalensis in the understorey cultivation. It provides practice suggestion for the efficient management and sustainable cultivation of understorey medicinal plants.

Evaluating sound attenuation of single trees using 3D information

Urban tree belts reduce noise pollution, but limited research has focused on the mitigation potential of single trees. Identifying individual tree characteristics that influence noise propagation can assist in selecting trees to improve urban soundscapes at multiple scales. This study introduces a methodology to evaluate and predict the sound attenuation of single trees using 3D tree morphology data and sound observations. We extracted structural characteristics for 26 trees on Nanjing University's Xianlin campus from handheld terrestrial LiDAR. Second, the sound attenuation of each sample tree was quantified systematically using a sound source and a receiver. The sound level meter was placed in front of and behind each sample tree to record the received sound levels. The sound source was positioned 1.5m above ground to emit white noise, ensuring the front receiver recording sound levels of 55, 60, and 68 dBA. We established a support vector regression (SVR) with a linear (LN) kernel to predict the sound attenuation of single trees based on their 3D characteristics. Single trees yielded an insertion loss of 2-3 dBA, effectively eliminating sound above 500 Hz and increasing with the frequency. It is also interesting to note that the insertion loss increases with increasing source sound levels. Regression analysis revealed that an increase in crown leaf area index (β = 0.332, p < 0.01) and average leaf inclination (β = 0.168, p < 0.01) reduced sound significantly, indicating the tree canopy's predominant role in impeding sound propagation. The SVR-LN model, established using standardized parameters with statistical significance, exhibited strong predictive sound attenuation performance using tree characteristics (R2 = 0.74, RMSE = 0.38, and MSE = 0.15). This study addresses a research gap in the acoustic effects of single trees and provides a framework for accurately evaluating and predicting sound attenuation based on 3D characteristics. The findings can assist urban planners and policymakers in strategically planting trees to foster healthier and quieter living spaces for residents.

Amazon forest biogeography predicts resilience and vulnerability to drought

Amazonia contains the most extensive tropical forests on Earth, but Amazon carbon sinks of atmospheric CO2 are declining, as deforestation and climate-change-associated droughts1-4 threaten to push these forests past a tipping point towards collapse5-8. Forests exhibit complex drought responses, indicating both resilience (photosynthetic greening) and vulnerability (browning and tree mortality), that are difficult to explain by climate variation alone9-17. Here we combine remotely sensed photosynthetic indices with ground-measured tree demography to identify mechanisms underlying drought resilience/vulnerability in different intact forest ecotopes18,19 (defined by water-table depth, soil fertility and texture, and vegetation characteristics). In higher-fertility southern Amazonia, drought response was structured by water-table depth, with resilient greening in shallow-water-table forests (where greater water availability heightened response to excess sunlight), contrasting with vulnerability (browning and excess tree mortality) over deeper water tables. Notably, the resilience of shallow-water-table forest weakened as drought lengthened. By contrast, lower-fertility northern Amazonia, with slower-growing but hardier trees (or, alternatively, tall forests, with deep-rooted water access), supported more-drought-resilient forests independent of water-table depth. This functional biogeography of drought response provides a framework for conservation decisions and improved predictions of heterogeneous forest responses to future climate changes, warning that Amazonia's most productive forests are also at greatest risk, and that longer/more frequent droughts are undermining multiple ecohydrological strategies and capacities for Amazon forest resilience.

The role of vegetation structural diversity in regulating the microclimate of human-modified tropical ecosystems

Vegetation regulates microclimate stability through biophysical mechanisms such as evaporation, transpiration and shading. Therefore, thermal conditions in tree-dominated habitats will frequently differ significantly from standardized free-air temperature measurements. The ability of forests to buffer temperatures nominates them as potential sanctuaries for tree species intolerant to the increasingly challenging thermal conditions established by climate change. Although many factors influencing thermal conditions beneath the vegetation cover have been ascertained, the role of three-dimensional vegetation structure in regulating the understory microclimate remains understudied. Recent advances in remote sensing technologies, such as terrestrial laser scanning, have allowed scientists to capture the three-dimensional structural heterogeneity of vegetation with a high level of accuracy. Here, we examined the relationships between vegetation structure parametrized from voxelized laser scanning point clouds, air and soil temperature ranges, as well as offsets between field-measured temperatures and gridded free-air temperature estimates in 17 sites in a tropical mountain ecosystem in Southeast Kenya. Structural diversity generally exerted a cooling effect on understory temperatures, but vertical diversity and stratification explained more variation in the understory air and soil temperature ranges (30%-40%) than canopy cover (27%), plant area index (24%) and average stand height (23%). We also observed that the combined effects of stratification, canopy cover and elevation explained more than half of the variation (53%) in understory air temperature ranges. Stratification's attenuating effect was consistent across different levels of elevation. Temperature offsets between field measurements and free-air estimates were predominantly controlled by elevation, but stratification and structural diversity were influential predictors of maximum and median temperature offsets. Moreover, stable understory temperatures were strongly associated with a large offset in daytime maximum temperatures, suggesting that structural diversity primarily contributes to thermal stability by cooling daytime maximum temperatures. Our findings shed light on the thermal influence of vertical vegetation structure and, in the context of tropical land-use change, suggest that decision-makers aiming to mitigate the thermal impacts of land conversion should prioritize management practices that preserve structural diversity by retaining uneven-aged trees and mixing plant species of varying sizes, e.g., silvopastoral, or agroforestry systems.

Telecoupling between urban expansion and forest ecosystem service loss through cultivated land displacement: A case study of Zhejiang Province, China

Urbanization can either directly occupy forests or indirectly lead to forest loss elsewhere through cultivated land displacement, resulting in further forest fragmentation and ecosystem service (ES) loss. However, the effects of urban expansion on forest area and ESs are unknown, and this is especially true for indirect effects. Taking Zhejiang Province, China, a typical deforested province, as an example, this study quantified the direct and indirect effects of urban expansion on forest area and five ESs (timber yield, water yield, carbon sequestration, soil conservation, and biodiversity) from 2000 to 2020, explored the relationship between forest structure (forest proportion, mean patch area, edge density, and mean euclidean nearest neighbor distance) change and ESs, and revealed the telecoupling of urban expansion and forest loss and cascade effects among urbanization, deforestation, forest structure, and ESs. The results indicated that the indirect forest loss (4.30%-6.15%) caused by cultivated land displacement due to urban expansion was larger than the direct forest loss (2.42%). Urban expansion has a greater negative impact on carbon sequestration (6.40%-8.20%), water yield (6.08%-7.78%), and biodiversity (5.79%-7.44%) than on timber yield (4.77%-6.17%) and soil conservation (4.43%-5.77%). The indirect forest ES loss was approximately 2.83-4.34 times greater than the direct forest ES loss. Most forest ESs showed a nonlinear significant positive correlation with changes in forest proportion and mean patch area and a significant nonlinear negative correlation with changes in edge density and mean Euclidean nearest neighbor distance (p < 0.05). There is telecoupling between urban expansion in one region and forest ES loss in other distant regions. This study contributes to guiding sustainable forest conservation and management globally.

Edge effects on tree architecture exacerbate biomass loss of fragmented Amazonian forests

Habitat fragmentation could potentially affect tree architecture and allometry. Here, we use ground surveys of terrestrial LiDAR in Central Amazonia to explore the influence of forest edge effects on tree architecture and allometry, as well as forest biomass, 40 years after fragmentation. We find that young trees colonising the forest fragments have thicker branches and architectural traits that optimise for light capture, which result in 50% more woody volume than their counterparts of similar stem size and height in the forest interior. However, we observe a disproportionately lower height in some large trees, leading to a 30% decline in their woody volume. Despite the substantial wood production of colonising trees, the lower height of some large trees has resulted in a net loss of 6.0 Mg ha-1 of aboveground biomass - representing 2.3% of the aboveground biomass of edge forests. Our findings indicate a strong influence of edge effects on tree architecture and allometry, and uncover an overlooked factor that likely exacerbates carbon losses in fragmented forests.

StrucNet: a global network for automated vegetation structure monitoring

Climate change and increasing human activities are impacting ecosystems and their biodiversity. Quantitative measurements of essential biodiversity variables (EBV) and essential climate variables are used to monitor biodiversity and carbon dynamics and evaluate policy and management interventions. Ecosystem structure is at the core of EBVs and carbon stock estimation and can help to inform assessments of species and species diversity. Ecosystem structure is also used as an indirect indicator of habitat quality and expected species richness or species community composition. Spaceborne measurements can provide large-scale insight into monitoring the structural dynamics of ecosystems, but they generally lack consistent, robust, timely and detailed information regarding their full three-dimensional vegetation structure at local scales. Here we demonstrate the potential of high-frequency ground-based laser scanning to systematically monitor structural changes in vegetation. We present a proof-of-concept high-temporal ecosystem structure time series of 5 years in a temperate forest using terrestrial laser scanning (TLS). We also present data from automated high-temporal laser scanning that can allow upscaling of vegetation structure scanning, overcoming the limitations of a typically opportunistic TLS measurement approach. Automated monitoring will be a critical component to build a network of field monitoring sites that can provide the required calibration data for satellite missions to effectively monitor the structural dynamics of vegetation over large areas. Within this perspective, we reflect on how this network could be designed and discuss implementation pathways.

Thermal sensitivity across forest vertical profiles: patterns, mechanisms, and ecological implications

Rising temperatures are influencing forests on many scales, with potentially strong variation vertically across forest strata. Using published research and new analyses, we evaluate how microclimate and leaf temperatures, traits, and gas exchange vary vertically in forests, shaping tree, and ecosystem ecology. In closed-canopy forests, upper canopy leaves are exposed to the highest solar radiation and evaporative demand, which can elevate leaf temperature (T_leaf ), particularly when transpirational cooling is curtailed by limited stomatal conductance. However, foliar traits also vary across height or light gradients, partially mitigating and protecting against the elevation of upper canopy T_leaf . Leaf metabolism generally increases with height across the vertical gradient, yet differences in thermal sensitivity across the gradient appear modest. Scaling from leaves to trees, canopy trees have higher absolute metabolic capacity and growth, yet are more vulnerable to drought and damaging T_leaf than their smaller counterparts, particularly under climate change. By contrast, understory trees experience fewer extreme high T_leaf 's but have fewer cooling mechanisms and thus may be strongly impacted by warming under some conditions, particularly when exposed to a harsher microenvironment through canopy disturbance. As the climate changes, integrating the patterns and mechanisms reviewed here into models will be critical to forecasting forest-climate feedback.

Examining the Angular Effects of UAV-LS on Vegetation Metrics Using a Framework for Mediating Effects

Discrete point cloud data from unmanned aerial vehicle laser scanning (UAV-LS) can provide information on the three-dimensional structure of a forest, the leaf area index (LAI) at the landscape or sample plot scales, the distribution of the vertical forest structure at a fine resolution, and other information. The retrieved parameters, however, may be affected in a non-negligible way by the inclusion of scan angle information. In this study, we introduced a relational model that encompasses the angular effect, predicted the mechanism of this effect, and extracted the vegetation structure indices that the angular effect might influence. Second, we quantified the direct and indirect effects, particularly the magnitude of the angular effect in broadleaf forests, and used mediated effects to investigate the components and processes that influence the angular effect. The findings demonstrate that some of the differences between the LAIe extracted by UAV-LS and the Decagon LAIe considering the angular effect of UAV-LS can be explained by adjusting physical LiDAR parameters (aerial height, laser divergence fraction, and scanning angle) and vertical forest structure variables. Along continuous and closed forest vertical gradients, the indirect angle impact is negative for the upper canopy and positive for the understory. Three-dimensional vegetation measurements were created using multiangle LiDAR data. In conclusion, this article (1) addresses the angular effect in UAV-LS; and (2) discusses how the angular effect affects 3D vegetation parameters such as LAIe, demonstrates the nonlinear trend of the angular effect, and demonstrates how multiangle LiDAR data can be used to obtain 3D vegetation parameters. This study serves as a reference for reducing the uncertainty in simulations of the angular effect and vegetation light transmission, in addition to the uncertainty in analyses of the vegetation characteristics determined by UAV-LS (e.g., the uncertainty of LAIe).

DETER-R: An Operational Near-Real Time Tropical Forest Disturbance Warning System Based on Sentinel-1 Time Series Analysis

Continuous monitoring of forest disturbance on tropical forests is a fundamental tool to support proactive preservation actions and to stop further destruction of native vegetation. Currently most of the monitoring systems in operation are based on optical imagery, and thus are flaw-prone on areas with frequent cloud cover. As this, several Synthetic Aperture Radar (SAR)-based systems have been developed recently, aiming all-weather disturbance detection. This article presents the main aspects and the results of the first year of operation of the SAR based Near Real-Time Deforestation Detection System (DETER-R), an automated deforestation detection system focused on the Brazilian Amazon. DETER-R uses the Google Earth Engine platform to preprocess and analyze Sentinel-1 SAR time series. New images are treated and analyzed daily. After the automated analysis, the system vectorizes clusters of deforested pixels and sends the corresponding polygons to the environmental enforcement agency. After 12 months of operational life, the system has produced 88,572 forest disturbance warnings. Human validation of the warning polygons showed a extremely low rate of misdetections, with less than 0.2% of the detected area corresponding to false positives. During the first year of operation, DETER-R provided 33,234 warnings of interest to national monitoring agencies which were not detected by its optical counterpart DETER in the same period, corresponding to an area of 105,238.5 ha, or approximately 5% of the total detections. During the rainy season, the rate of additional detections increased as expected, reaching 8.1%.