Canopy Cover Research Articles

Predator Personality Variation, Not the Multiple Stressors of Temperature and Light, Determines Feeding Motivation in an Ambush Piscivore Saxatilia proteus

ABSTRACTEnvironmental conditions in freshwater ecosystems are increasingly determined by human activity. Increased temperature and light intensity are among the anthropogenic stressors dramatically altering these ecosystems, for example, through deforestation that reduces canopy cover of riparian vegetation. Simultaneous exposure to multiple stressors complicates predictions of responses to environmental stressors due to potential interactions, yet the interaction between temperature and light intensity on feeding motivation remains poorly understood. Here, a fully factorial design was employed to investigate the combined effect of increased temperature and light intensity on the feeding motivation of a freshwater predator, the pike cichlid Saxatilia proteus. Strikes toward food items were used to quantify the subjects' motivation to feed. We found no effect of temperature or light intensity on feeding motivation, either individually or as an interaction. Our repeated measures design allowed us to test whether the predatory fish showed personality variation, i.e., consistent inter‐individual differences, in their motivation to feed. While the time taken to make the first strike was not consistently different between individuals, the number of strikes in 1 min, 3 min and the time taken for the 10th strike (which were strongly correlated to one another) was consistently different between individuals. This variation could not be explained by variation in body length, which had no effect as a main effect. Thus, we suggest that anthropogenic effects that alter the composition of individuals in a population of predators, for example selective harvesting, will have a greater ecological effect than direct short‐term effects of variability in environmental factors.

Adult Sex-Ratio Bias Does Not Lead to Detectable Adaptive Offspring Sex Allocation Via Nest-Site Choice in a Turtle With Temperature-Dependent Sex Determination.

Sex-ratio theory predicts that parents can optimise their fitness by producing offspring of the rare sex, yet there is a dearth of empirical evidence for adaptive sex allocation in response to the adult sex ratio (ASR). This is concerning, as anthropogenic disruption of the sex ratios of reproductive individuals threatens to cause demographic collapse in animal populations. Species with environmental sex determination (ESD) are especially at risk but may possess the capacity to adaptively influence offspring sex via control over the developmental environment. For example, reptiles with temperature-dependent sex determination (TSD) could conceivably choose nest sites with thermal characteristics that produce offspring of the rare sex. To test this hypothesis, we seeded three secure outdoor ponds with different sex ratios (~M:F 3:1, 1:1, and 1:3) of adult painted turtles (Chrysemys picta), a reptile species with TSD. We then quantified nesting traits that could influence nest temperature and thus offspring sex ratio, including nesting date, nest depth, and nest canopy cover. We found no directional relationship between the ASR treatments and any measured nest traits and thus rejected our hypothesis. Interestingly, increased maternal body size was associated with reduced nest canopy cover, and this trend was more pronounced in the biased ASR treatments. If adaptive sex allocation occurs in this system, it instead may manifest via maternal epigenetic predisposition of offspring sex or in response to a phenomenon other than the ASR.

Tree crowns broken off by windstorms are an unstable life raft for Collembola

There are a number of ways to clear the aftermath of a windthrow disturbance of forest stands, the most common practice being to remove all broken trees and broken-off crowns lying on the ground. This practice leads to complete exposure of the soil, which deprives soil invertebrates (including Collembola) of the protection of trees that affords them a chance of surviving. Accordingly, following a windthrow disturbance of pine stands in 2017, a three-year study of collembolan assemblages was undertaken in stands spared from salvage logging. We aimed to test the effect of three different levels of disturbance (severely, moderately and least disturbed stands with a canopy cover of 0–20%, 20–60% and 60–90%, respectively) on the survival of Collembola assemblages and to determine its association with changes in the soil environment and in the LAI index. Additionally, in the severely and moderately disturbed stands, Collembola were sampled between crowns of fallen trees and under the crowns. There were no significant differences in density, species richness and proportions of individuals of belowground “soil” and aboveground “epedaphic” species between the Collembolan assemblages that were associated with the degree of windthrow disturbance and time since disturbance. The study confirmed the presence of a significantly higher number of species and proportion of “epedaphic” species, and a lower proportion of “soil” species in the assemblages sampled under fallen tree crowns than between crowns. Analysis of principal response curves (PRC) yielded unexpected results as it indicated that these differences were significant only in the first year post-disturbance, thus suggesting a very short-lasting protective effect of tree crowns on Collembola, RDA analysis with preselected factors from environmental variables of interest (LAI of standing and fallen tree crowns, soil respiration, soil temperature and humidity, soil pH and soil nitrogen and carbon content) indicated the LAI index as significant for the Collembolan assemblages in the first yearpost-disturbance, soil moisture in the second year, and soil temperature in the third year. This sequence of significant indices over a three year period is compatible with the fallen crowns becoming more and more thinned as a result of needles falling off (from shade to full exposure to sunlight). We nevertheless postulate that at least some trees or their crowns lying on the ground should be left in place during clearance of windthrow-affected tree stands to facilitate restoration of the soil biota.

Spatio-temporal Analysis of Agroforestry Systems in Hotan Using Multi-source Remote Sensing and Deep Learning

In the Hotan region of Xinjiang, where arable land is scarce, an agroforestry system integrating walnut trees with crops has been implemented to maximize land-use efficiency. While this dense planting enhances land use, it also limits the availability of light to the understory crops, potentially impacting their yield and quality. To address this issue and enhance the system's sustainability and productivity, precise delineation of the planting structure is critical. This study proposes a novel framework that leverages multi-source remote sensing data combined with advanced deep learning techniques to analyze the agroforestry planting structure. The methodological approach consists of three key phases. First, an instance segmentation model was employed to extract farmland parcels from high-resolution imagery, providing a basis for vegetation classification. Next, a time series model using irregular satellite image time series (irSITS) tracked the growth dynamics of the vegetation. Finally, the spatial planting structure of the walnut trees was quantified using the D-LinkNet model, integrated with a template filling algorithm.The results demonstrated a classification accuracy of 97.85% in extracting parcel-level planting structures, identifying 42,955 farmland parcels, including 21,153 intercropped parcels. The temporal and spatial characteristics of the agroforestry system were then analyzed, leading to a grading of canopy cover and walnut tree density within the intercropped areas. This comprehensive spatiotemporal planting structure offers a valuable foundation for informed local agricultural policy adjustments. In conclusion, this approach advances the understanding of complex agroforestry systems and provides a robust scientific basis for optimizing intercropping practices, contributing to sustainable agricultural development in arid regions.

Evaluation of Automated Object-Detection Algorithms for Koala Detection in Infrared Aerial Imagery.

Effective detection techniques are important for wildlife monitoring and conservation applications and are especially helpful for species that live in complex environments, such as arboreal animals like koalas (Phascolarctos cinereus). The implementation of infrared cameras and drones has demonstrated encouraging outcomes, regardless of whether the detection was performed by human observers or automated algorithms. In the case of koala detection in eucalyptus plantations, there is a risk to spotters during forestry operations. In addition, fatigue and tedium associated with the difficult and repetitive task of checking every tree means automated detection options are particularly desirable. However, obtaining high detection rates with minimal false alarms remains a challenging task, particularly when there is low contrast between the animals and their surroundings. Koalas are also small and often partially or fully occluded by canopy, tree stems, or branches, or the background is highly complex. Biologically inspired vision systems are known for their superior ability in suppressing clutter and enhancing the contrast of dim objects of interest against their surroundings. This paper introduces a biologically inspired detection algorithm to locate koalas in eucalyptus plantations and evaluates its performance against ten other detection techniques, including both image processing and neural-network-based approaches. The nature of koala occlusion by canopy cover in these plantations was also examined using a combination of simulated and real data. The results show that the biologically inspired approach significantly outperformed the competing neural-network- and computer-vision-based approaches by over 27%. The analysis of simulated and real data shows that koala occlusion by tree stems and canopy can have a significant impact on the potential detection of koalas, with koalas being fully occluded in up to 40% of images in which koalas were known to be present. Our analysis shows the koala's heat signature is more likely to be occluded when it is close to the centre of the image (i.e., it is directly under a drone) and less likely to be occluded off the zenith. This has implications for flight considerations. This paper also describes a new accurate ground-truth dataset of aerial high-dynamic-range infrared imagery containing instances of koala heat signatures. This dataset is made publicly available to support the research community.

Reduced canopy cover and development compromises weed suppression by buckwheat in cover crop mixtures

Buckwheat (Fagopyrum esculentum Moench) is a common cover crop typically grown for its rapid establishment and superior weed suppression. One challenge of incorporating buckwheat into crop rotations, however, is its short generation time, which requires in-season management to prevent viable seed production and volunteers in subsequent crops. Mixing buckwheat at reduced seeding rates with other cover crop species is one way for producers to reduce volunteer potential; however, this may compromise weed suppression. To investigate mechanisms behind buckwheat weed suppression and how using buckwheat in mixtures can affect suppression, we collected a series of morphological measurements in buckwheat monocultures and in three, two-way and four, three-way cover crop species mixtures and modeled their response over the growing season. We found that while buckwheat height and relative growth rate were unaffected with increasing species richness, there was a significant reduction in maximum leaf area index (3.75 vs. 2.85 vs. 2.82 cm2 cm-2) in mixture. Buckwheat monocultures provided superior season-long weed suppression compared to mixtures (85% vs. 53% vs. 50%). Principal component analysis showed that increased height and leaf area index values were associated with greater weed suppression. The link between reduced leaf area index and weed suppression in mixtures compared to buckwheat monocultures suggests that the rapid leaf development and canopy cover associated with buckwheat is a key mechanism behind weed suppression. In practice, producers should expect a dilution effect and weed suppression to be compromised when the buckwheat seeding rate is reduced in mixtures.

The invasion of Japanese hop (Humulus japonicus) in a restored floodplain forest

Abstract Japanese hop (Humulus japonicus Sieb. & Zucc.) is an emerging invasive plant that has been observed to invade and spread throughout wetlands. As an annual vine, H. japonicus can smother native vegetation, forming dense stands and reducing biodiversity. At a restored floodplain forest in Joslin, Illinois, formerly used as an experimental site to test the effectiveness of different reforestation methods, H. japonicus has invaded stands of the previously dominant invasive, reed canarygrass (Phalaris arundinacea L.). We conducted an observational field study to examine the spatio-temporal dynamics of H. japonicus invasion relative to gradients in canopy cover and species composition. Ten transects, with half the transect extending into and half extending beyond H. japonicus patches, were established in October 2022. Seven quadrats per transect were surveyed for vegetation cover and canopy cover in October 2022, June 2023, and October 2023. Transects were evenly split between forested and open areas based on the reforestation treatments. H. japonicus cover significantly increased from October 2022 to October 2023, which has resulted in a slight decrease and replacement of P. arundinacea across the site. Shade reduced H. japonicus cover, indicating its preference for sunlit conditions. Species richness was higher in forested transects compared to open ones, most likely due to the absence of both P. arundinacea and H. japonicus in shaded transects. Along transects, quadrats that had been invaded by H. japonicus differed in species composition from quadrats that had not been invaded in both October 2022 and October 2023. H. japonicus cover was much lower in June than October, suggesting that temporal niche partitioning may allow P. arundinacea to persist, and indicating that monitoring for H. japonicus should occur late in the growing season. Both invasive species are shade intolerant, suggesting that planting fast-growing trees should be an effective long-term solution for controlling invasion.

Advanced Plant Phenotyping: Unmanned Aerial Vehicle Remote Sensing and CimageA Software Technology for Precision Crop Growth Monitoring

In production activities and breeding programs, large-scale investigations of crop high-throughput phenotype information are needed to help improve management and decision-making. The development of UAV (unmanned aerial vehicle) remote sensing technology provides a new means for the large-scale, efficient, and accurate acquisition of crop phenotypes, but its practical application and popularization are hindered due to the complicated data processing required. To date, there is no automated system that can utilize the canopy images acquired through UAV to conduct a phenotypic character analysis. To address this bottleneck, we developed a new scalable software called CimageA. CimageA uses crop canopy images obtained by UAV as materials. It can combine machine vision technology and machine learning technology to conduct the high-throughput processing and phenotyping of crop remote sensing data. First, zoning tools are applied to draw an area-of-interest (AOI). Then, CimageA can rapidly extract vital remote sensing information such as the color, texture, and spectrum of the crop canopy in the plots. In addition, we developed data analysis modules that estimate and quantify related phenotypes (such as leaf area index, canopy coverage, and plant height) by analyzing the association between measured crop phenotypes and CimageA-derived remote sensing eigenvalues. Through a series of experiments, we confirmed that CimageA performs well in extracting high-throughput remote sensing information regarding crops, and verified the reliability of retrieving LAI (R2 = 0.796) and estimating plant height (R2 = 0.989) and planting area using CimageA. In short, CimageA is an efficient and non-destructive tool for crop phenotype analysis, which is of great value for monitoring crop growth and guiding breeding decisions.

Temporally resolved growth patterns reveal novel information about the polygenic nature of complex quantitative traits.

Plant height can be an indicator of plant health across environments and used to identify superior genotypes. Typically plant height is measured at a single timepoint when plants reach terminal height. Evaluating plant height using unoccupied aerial vehicles allows for measurements throughout the growing season, facilitating a better understanding of plant-environment interactions and the genetic basis of this complex trait. To assess variation throughout development, plant height data was collected from planting until terminal height at anthesis (14 flights 2018, 27 in 2019, 12 in 2020, and 11 in 2021) for a panel of ~500 diverse maize inbred lines. The percent variance explained in plant height throughout the season was significantly explained by genotype (9-48%), year (4-52%), and genotype-by-year interactions (14-36%) to varying extents throughout development. Genome-wide association studies revealed 717 significant single nucleotide polymorphisms associated with plant height and growth rate at different parts of the growing season specific to certain phases of vegetative growth. When plant height growth curves were compared to growth curves estimated from canopy cover, greater Fréchet distance stability was observed in plant height growth curves than for canopy cover. This indicated canopy cover may be more useful for understanding environmental modulation of overall plant growth and plant height better for understanding genotypic modulation of overall plant growth. This study demonstrated that substantial information can be gained from high temporal resolution data to understand how plants differentially interact with the environment and can enhance our understanding of the genetic basis of complex polygenic traits.

Determination of forest canopy cover of different sized stands with diverse structure using ALS data: case study of the Białowieża Forest (Poland)

ABSTRACT The need for objective methods to determine tree canopy cover (CC) across large numbers of stands has led to the development of techniques that utilise airborne laser scanning (ALS) data, which provides a reproducible and detailed representation of canopy geometry. We developed a method for determining CC area and evaluated the estimation accuracy for stands of different sizes, structure and composition. This method is based on tree crown geometries obtained from ALS data, and verified with field measurements using data for 3245 stands of the Białowieża Forest District in Poland. In relatively large stands (3–5 ha), the theoretical error of prediction decreased from 0.13 to 0.10 with increasing stand area. In stands larger than 10 ha, however, the error in estimating CC was less than ±0.10. Although every estimation method comes with its own assumptions and errors, the presented method eliminates the subjectivity in observer bias prevalent in traditional field-based ocular assessments and provides a more transparent and methodologically uniform approach for estimating CC in forests.

Assessing Nitrogen Fertilization in Processing Pepper: Critical Nitrogen Curve, Yield Response, and Crop Development

Groundwater pollution in intensive horticultural areas is becoming an increasingly important problem. Over-fertilization of these crops, combined with poor irrigation management, leads to groundwater contamination through leaching. Previous research on the effect of N on sweet peppers grown in greenhouses is abundant, but data on outdoor cultivation, especially considering variety and site influences, are lacking. Therefore, this study evaluates nitrogen (N) fertilization in open-field processing-pepper crop in Extremadura, Spain to mitigate this environmental impact. Field trials were conducted in 2020, 2021, and 2022 to determine the optimum N fertilizer rate for processing peppers, with the aim of reducing environmental impacts such as nitrate leaching while maintaining crop yields. The trial consisted of applying different N doses, 0, 60, 120, and 180 kg N/ha in 2020 and 2021 and 0, 100, and 300 kg N/ha in 2022. There were four replications of each treatment, arranged in randomized blocks. Measurements included crop yield, biomass, intercepted photosynthetically active radiation (PAR), and canopy cover. The study also developed a critical nitrogen curve (CNC) to determine the minimum N concentration required for optimal growth. The commercial yield results showed that there were no significant differences between the two treatments with higher N inputs in the three years; therefore, the application of more than 120 kg N/ha did not significantly increase yield. Nitrogen-free treatments resulted in earlier fruit maturity, concentrating the harvest and reducing waste. In addition, excessive N application led to environmental problems such as groundwater contamination due to nitrate leaching. The study concludes that outdoor pepper crops in this region can achieve optimal yields with lower N rates (around 120 kg N/ha) compared to current practices, taking into account that initial soil N values were higher than 100 kg N/ha, thereby reducing environmental risks and fertilizer costs. It also established relationships between biomass, canopy cover, and N uptake to improve fertilization strategies. These data support future crop modeling and sustainable fertilization practices.

Nest site selection and threats to nesting colonies of white-rumped Vulture (Gyps bengalensis) in Himachal Pradesh

White-rumped Vulture (Gyps bengalensis) suffered the most significant population decline among the three species of Gyps vultures impacted by the South Asia-wide diclofenac toxicity of the 1990s. Although the population lost about 99 % of its individuals, nesting populations still remain in a few pockets in India. One such population is known from the Himalayan foothills in the Kangra region, representing the northernmost nesting population of the species in India. From 2020–2024, we carried out an extensive study on the nesting ecology of the species, identifying 17 colonies with 617 active nests in 553 trees in an area of 5739 SqKm, constituting the highest nesting population reported in India. The smallest colony had ten nests, while the largest had 68. Except for a single nest on a Ficus religiosa tree, all others were on old-growth Chir Pine, Pinus roxburghii, having an average GBH of 254.8 cm (± 49.3 SD). By analyzing 18 variables, we determined vulture preferences for nest tree characteristics. Results indicate that nesting site selection primarily depends on GBH, canopy cover and nearest nest distance. About 80 % of nests were found between 600 and 800 m elevation. The primary threats include forest fire, resin tapping, and tree felling. We recommend protecting larger-sized old-growth forests through awareness campaigns with forest managers and local communities to safeguard the nest sites of the critically endangered bird.

Habitat Utilization of Endemic Green Pit Viper (<i>Peltopelor trigonocephalus</i>) in the Wet Zone, Sri Lanka

The endemic arboreal pit viper Peltopelor trigonocephalus is restricted to three climatic zones of Sri Lanka. In this study, the habitat utilization of P. trigonocephalus was investigated by active search and the quadrate method between April 2021 and March 2022. Data on 49 individuals of P. trigonocephalus were collected from riparian, forest, and open habitats. A high encounter rate was recorded in riparian habitats which included areas with thick vegetation. Based on Principal Component Analysis, some habitat variables were key determining factors of microhabitat preference of this species. Ambient temperature, distance to stream, canopy cover and light intensity were significantly affecting the occupied microhabitat structure. Ambushing behavior was more prominent and time-consuming than other behaviors, with 42.59% of recorded sit-and-wait hunting activity. The results of this research indicate that P. trigonocephalus actively selects and utilizes the most suitable macro and microhabitats in wet zones, providing crucial insights for the conservation and management of the species as well as its natural habitat.

Public Perception of Urban Green Spaces and its Tree Diversity in Delhi

The relationship between man and nature plays an important role in the everyday lives of human societies. Places like Delhi and its people face major challenges and issues of urbanisation affecting their health and well-being. Urban greens such as parks play a major role in bringing greenness into the lives of urban dwellers. Trees are seen as a major green component in the urban greens. This paper attempts to understand how public sees green spaces and their uses. Tree diversity index (The Shannon Index also known as Shannon Weiner Index, is a statistical index that measures diversity by estimating species richness and evenness.) canopy cover, and tree trunk diameter have been taken as indicators of greenness of park. Tree distribution at the species level is studied in one of the parks managed by Delhi Development Authority as ‘Landmark greens’. The park users’ perception is studied using an ethnographic method. Whereas the Shannon index is 2.2, which is a moderate value, 50 per cent of the visitors could only identify the popular species namely Neem, Banyan, Ashok, and Peepal. People are aware of the potential benefits of trees and plants or the role of green spaces in their overall well-being. Some of the visitors are the regular ones as they use the park with a purpose to heal from respiratory tract infection, obesity, diabetes, and palpitation, while there are 22 per cent visitors who found the park unsafe during certain instances.

Gender and violent crime modify associations between greenspace and cardiovascular disease mortality in Philadelphia, PA

Few studies have explored variability of associations between greenspace and cardiovascular (CVD) mortality according to demographic or neighborhood contextual factors. We estimated overall and sex-stratified associations between greenspace and CVD mortality rates in Philadelphia, PA, and quantified effect modification of the sex-stratified associations by neighborhood violent crime rates. Sex- and age-stratified census tract CVD mortality rates (years 2008–2015) were linked with proportion tree canopy cover, grass/shrub cover, and total vegetation cover, and proportion of adult residents reporting access to a park. We used multivariable negative binomial models to estimate overall and sex-stratified associations between neighborhood greenspace and CVD mortality rates, and quantified effect modification by tract-level rates of violent crime. Higher proportion tree canopy cover and higher proportion adults reporting access to parks were associated with modestly lower rates of CVD mortality, with more pronounced estimates in males than females. In tracts with higher rates of crime, higher tree canopy coverage and perceived park access were associated with lower CVD mortality rates. We did not observe strong evidence of sex-based differences in interaction between neighborhood crime rates and greenspace. Results from this study reveal variability of associations between greenspace and CVD mortality rates according to sex categories, and according to neighborhood social environments. There is a need for further research exploring the extent to which differences in perceived safety explain gender-based differences in associations between greenspace and cardiovascular outcomes.

Variation in species-specific responses to habitat fragmentation and land cover structure in urban small mammal communities

Abstract Urbanization is a key driver of habitat loss and fragmentation worldwide, yet many urban ecosystems contain vegetated habitat patches that support diverse wildlife communities. Managing urban systems to support robust wildlife communities requires us to understand the mechanisms that drive the response of species to the urban environment. Small mammals are key components of terrestrial ecosystems (e.g., seed predators, prey) and likely also carry out these roles in urban ecosystems; however, the effects of urbanization on small mammal communities are understudied. To identify how species-specific responses to urban environments shape community composition, we quantified both overall community and species-specific changes in small mammal abundance across an urbanization gradient in a Midwestern US metropolitan area. We combined small mammal trapping and land cover data to generate a hierarchical community abundance model. Species diversity increased with increasing proportional cover of human-modified land cover (i.e., impervious surfaces and turfgrass). This finding is driven by high species diversity on sites bordering streams in mowed parks and low diversity on sites with high tree canopy closure. Additionally, modeling results indicated that species responded differently to landscape attributes, leading to variation in small mammal community composition across the urbanization gradient: prairie-associated species tended to be more abundant in tall vegetation bordering mowed parks while habitat generalists tended to be more abundant on sites with greater canopy closure and shrub cover. Our results suggest that studies that focus on community-level responses (e.g., species richness) to urbanization may miss important species-specific responses. It may be particularly important to assess both species-specific and community-level responses in cities at ecotones (e.g., between forest and grassland) where species with different habitat requirements may replace one another in different types of green spaces, thereby changing community composition without affecting species diversity or richness. Our findings also indicate that vegetated urban patches, especially patches with tall vegetation cover and low canopy cover, are important habitat for prairie-associated small mammal communities, providing conservation options in heavily altered landscapes.

Scale-Dependent Effects of Urban Canopy Cover, Canopy Volume, and Impervious Surfaces on Near-Surface Air Temperature in a Mid-Sized City

Cities are significantly warmer than their surrounding rural environments. Known as the ‘urban heat island effect’, it can affect the health of urban residents and lead to increased energy use, public health impacts, and damage to infrastructure. Although this effect is extensively researched, less is known about how landscape characteristics within cities affect local temperature variation. This study examined how tree canopy cover, canopy volume, and impervious surface cover affect daytime near-surface air temperature, and how these effects vary between different scales of analysis (10, 30, 60, 90 m radii), ranging from approximate street corridor to city block size. Temperature data were obtained from a car-mounted sensor, with traverse data points recorded during morning, afternoon, and evening times, plotted throughout the city of Portland, OR. The variability in near-surface air temperature was over 10° F during each traverse period. The results indicate that near-surface air temperature increased linearly with impervious surface cover and decreased linearly with tree canopy cover, with canopy volume reducing the temperature by 1° F for every 500 cubic feet of canopy volume for evening temperatures. The magnitude of the effect of tree canopy increased with spatial scale, with 60 and 90 m scales having the greatest measurable effect. Canopy volume had a positive relationship on presumed nighttime and early-morning temperatures at 60 and 90 m scales, potentially due to the impacts of wind fluctuation and air roughness. Canopy cover still contributed the largest overall decrease in street-scale temperatures. Increasing tree canopy cover and volume effectively explained the lower daytime and evening temperatures, while reducing impervious surface cover remains critical for reducing morning and presumed nighttime urban heat. The results may inform strategies for urban foresters and planners in managing urban land cover and tree planting patterns to build increased resiliency towards moderating urban temperature under warming climate conditions.

Advancing Forest Degradation and Regeneration Assessment Through Light Detection and Ranging and Hyperspectral Imaging Integration

Integrating Light Detection And Ranging (LiDAR) and Hyperspectral Imaging (HSI) enhances the assessment of tropical forest degradation and regeneration, which is crucial for conservation and climate mitigation strategies. This study optimized procedures using combined airborne LiDAR, HSI data, and machine learning algorithms across 12 sites in the Brazilian Amazon, covering various environmental and anthropogenic conditions. Four forest classes (undisturbed, degraded, and two stages of second-growth) were identified using Landsat time series (1984–2017) and auxiliary data. Metrics from 600 samples were analyzed with three classifiers: Random Forest, Stochastic Gradient Boosting, and Support Vector Machine. The combination of LiDAR and HSI data improved classification accuracy by up to 12% compared with single data sources. The most decisive metrics were LiDAR-based upper canopy cover and HSI-based absorption bands in the near-infrared and shortwave infrared. LiDAR produced significantly fewer errors for discriminating second-growth from old-growth forests, while HSI had better performance to discriminate degraded from undisturbed forests. HSI-only models performed similarly to LiDAR-only models (mean F1 of about 75% for both data sources). The results highlight the potential of integrating LiDAR and HSI data to improve our understanding of forest dynamics in the context of nature-based solutions to mitigate climate change impacts.

Ecological implications of row width and cultivar selection on rice (Oryza sativa) and barnyardgrass (Echinochloa crus-galli)

Rice (Oryza sativa L.) producers in the Mid-south are experiencing difficulties with herbicide-resistant weeds such as barnyardgrass [Echinochloa crus-galli (L.) P. Beauv.]. As a result, methods that can alter E. crus-galli ecology are needed. This research evaluated the ecological implications of rice cultivar and row widths on crop and E. crus-galli growth. Overall, for E. crus-galli, as the row width increased, greater density, panicle counts, and seed production occurred. Echinochloa crus-galli density was 120% greater in a 38-cm row width than the 13-cm row width at the preflood rice stage. Reduced early-season rice canopy coverage in the wider row widths allowed for increased E. crus-galli densities. At the preharvest stage, E. crus-galli panicle counts were similar for the 13- and 19-cm rows. Row width did not affect rice yield, indicating wider row widths could be feasible agronomically, but additional weed management efforts would be needed because greater ecological advantages were obtained in narrower rows. Less E. crus-galli seed production occurred in competition with hybrid cultivars compared to inbred cultivars. Overall, the standard row width (19-cm) and hybrid cultivars would provide the greatest ecological advantage over E. crus-galli.

Fight or flight alternative mating tactics may explain the iconic male polymorphism of the European stag beetle

The existence of different male morphologies within a single species is associated with alternative mating tactics across different animal groups, offering textbook examples of evolutionary biology. The European stag beetle Lucanus cervus is a flagship species which has long fascinated naturalists for its charismatic appearance and behavior, with males possessing large mandibles used in ritualized ground fights for females. Males are polymorphic, with larger males possessing disproportionately larger mandibles and being better fighters, while smaller males require less food to develop and may have better chances to escape predation. We discovered an alternative mating tactic that opens a new interpretation on the evolution of the smaller males, based on aggregations of flying males competing to catch flying females in mid-air. Flight aggregations occur earlier in the season and in sites with sparser canopy cover as compared to ground fight aggregations, but most importantly, smaller males tend to prevail due to their greater agility in flight. Competition between males is crucial for reproductive success in this species, and alternative mating tactics involving flight were unknown in beetles, advocating for further research on the ecology and evolution of the iconic male polymorphism of stag beetles.