Ridge Forest Research Articles

Population status of the highly endangered Lycaena helle (Papilionoidea, Lycaenidae) in the Šumava Mts. two decades after establishment

The process of translocation of endangered species represents a useful conservation tool, but subsequent monitoring of translocated populations is often neglected, although it may supply critical information for conservation work. The EU-protected glacial relic Lycaena helle (Lycaenidae) went extinct in the Czech Republic, where a few lowland populations historically existed, in the 1950s. In 2002, a mountain-dwelling population was established in Šumava Mts., among grasslands and fenlands surrounding the abandoned village of Nové Údolí, from 2/33 ♂♂/♀♀ originating in the Türnitz Alps, Austria. The transferred population was surveyed a decade later and again 21 years after the transfer. During the second (2023) survey, we visited 212 grassland patches to record the species’ presence and relative abundance, and to ascertain its habitat preferences. A third of the surveyed patches were occupied by L. helle, in a total area of occupied grasslands was 66.6 ha scattered over 4.5 km2, with approximately 2,400 adult individuals, recorded up to 4.2 km from the original release point. L. helle typically occupies wet tussocky grasslands with closed edges, minimum management and high cover of its larval host plant, the mid-to late-successional forb Bistorta officinalis. It avoids drier managed grasslands rich in flowering plants. The expansion rate from the release point (0.1 km/year during the first decade, 0.2 km/year over two decades) was slower than in two earlier L. helle transfers, targeting Morvan and Forez Mts., France (≈ 0.5 km/year in both cases). We attribute this to the relief of the release locality, a­ shallow depression surrounded by higher-elevated forested ridges, but we expect faster expansion once the continuous woodlands are crossed.

Empirical Study on the Impact of Different Types of Forest Environments in Wuyishan National Park on Public Physiological and Psychological Health

Amidst the challenges of global environmental change and urbanization, the salutary effects of natural environments on public health are increasingly being recognized. This study investigates the specific effects of varied forest environments in China’s Wuyishan National Park on physiological and psychological health. Eight distinct forest environments were carefully selected, and a repeated-measures ANOVA approach was used to evaluate 41 participants over three days. Physiological assessments included Heart Rate Variability, Skin Conductance Level, and surface Electromyography, complemented by psychological evaluations using the Profile of Mood States. The key findings include the following: (1) Notable variations in physiological indicators were observed among different forest types. In valley tea gardens and broadleaf forest streamside, significant changes in heart rate indicators highlighted the influence of these settings on autonomic nervous activities. Skin Conductance Level and surface Electromyography also indicated varying emotional arousal and pleasure across the forests. The mixed broadleaf and coniferous forest valley, along with the rock-bedded streamscape, elicited emotions of low arousal but high pleasure, inducing feelings of calmness and pleasure. The valley’s tea gardens were associated with low arousal and pleasure, suggesting tranquility without positive emotional induction, while the broadleaf ridge forest induced high arousal and pleasure, reflecting an exciting and joyful environment. (2) The study found that different forest environments had a notable impact on participants’ mood states, indicating reductions in tension, anger, fatigue, and depression, along with an increase in vigor levels. In summary, forest environments offer unique psychological and physiological health benefits compared to urban settings. These findings underscore the importance of integrating forest environments into urban development and public health frameworks, and the need to further explore their impact on the health of diverse populations.

The Prediction of NBA Players Salary

The purpose of this paper is to find the relationship between player data and their salaries through data analysis and modeling of NBA players. Unlike previous papers, this paper divides players into five parts according to different positions and uses more independent variables than previous studies to build models. This article uses 53 sets of player data and their corresponding salaries and conducts preliminary judgment and screening of the data according to the correlation and Boruta formula, and then uses LASSO, RIDGE, Elastic Net, and Random Forest to perform secondary screening and modeling of the data for different positions respectively. The initial screening narrowed the variables from 50 to less than 30. The LASSO and Elastic Net models R-squares are around 0.8, and RIDGE and Random Forest models R-squares are about 0.5. This means that a certain item of LASSO and Elastic Net has a good fit for the data. Then the players income can be predicted according to the two models to help the team build an excellent team with the least amount of money.

Inverting Chlorophyll Content in Jujube Leaves Using a Back-Propagation Neural Network–Random Forest–Ridge Regression Algorithm with Combined Hyperspectral Data and Image Color Channels

Chlorophyll content is highly susceptible to environmental changes, and monitoring these changes can be a crucial tool for optimizing crop management and providing a foundation for research in plant physiology and ecology. This is expected to deepen our scientific understanding of plant ecological adaptation mechanisms, offer a basis for improving agricultural production, and contribute to ecosystem management. This study involved the collection of hyperspectral data, image data, and SPAD data from jujube leaves. These data were then processed using SG smoothing and the isolated forest algorithm, following which eigenvalues were extracted using a combination of Pearson’s phase relationship method and the Partial Least Squares Regression–continuous projection method. Subsequently, seven methods were employed to analyze the results, with hyperspectral data and color channel data used as independent variables in separate experiments. The findings indicated that the integrated BPNN-RF-Ridge Regression algorithm provided the best results, with an R2 of 0.8249, MAE of 2.437, and RMSE of 2.9724. The inclusion of color channel data as an independent variable led to a 3.2% improvement in R2, with MAE and RMSE increasing by 1.6% and 3.9%, respectively. These results demonstrate the effectiveness of integrated methods for the determination of chlorophyll content in jujube leaves and underscore the potential of using multi-source data to improve the model fit with a minimal impact on errors. Further research is warranted to explore the application of these findings in precision agriculture for jujube yield optimization and income-related endeavors, as well as to provide insights for similar studies in other plant species.

Forest yield prediction under different climate change scenarios using data intelligent models in Pakistan.

This study aimed to develop and evaluate data driven models for prediction of forest yield under different climate change scenarios in the Gallies forest division of district Abbottabad, Pakistan. The Random Forest (RF) and Kernel Ridge Regression (KRR) models were developed and evaluated using yield data of two species (Blue pine and Silver fir) as an objective variable and climate data (temperature, humidity, rainfall and wind speed) as predictive variables. Prediction accuracy of both the models were assessed by means of root mean squared error (RMSE), mean absolute error (MAE), correlation coefficient (r), relative root mean squared error (RRMSE), Legates-McCabe's (LM), Willmott's index (WI) and Nash-Sutcliffe (NSE) metrics. Overall, the RF model outperformed the KRR model due to its higher accuracy in forecasting of forest yield. The study strongly recommends that RF model should be applied in other regions of the country for prediction of forest growth and yield, which may help in the management and future planning of forest productivity in Pakistan.

Шакал (Canis aure¬us) на півночі Полісся України: виявлення у природі, статус та повільне розселення

The golden jackal continues to slowly inhabit the north of Central Polissia and to disperse. Mostly single individuals are found. The social structure of the jackal is flexible and groups of more than two individuals are found in places of food concentration. A similar situation occurred in the Ubort River valley near the Ukrainian–Belarusian border, when visual encounters of jackal family consisting of probably 3–4 animals were very frequent near the burial place of livestock corpses. In the north of Central Polissia of Ukraine, the jackal has been recorded since 2014. The species is rare here. According to the registration of tracks, this predator is found on a less forested forest ridge between the settlements of Ovruch–Velidnyky–Slovechno–Levkovychi and in the valley of the Ubort River, which is a natural corridor of the species’ northward dispersal. Given Ukraine’s course towards EU membership and the position of the Baltic countries on the jackal, our country will obviously have to take into account the special status of the jackal as a species that has expanded its range on its own. Accordingly, this predator should not be considered an invasive species. Obviously, the problem with the jackal in forested regions of north of Ukraine will be much less severe than in the south in the floodplains of large rivers. In the Polissia, in trophically rich broadleaf forests with mosaic forest cover, the jackal is likely to coexist successfully with the wolf. Interspecific relations between wolves and jackals do not take the form of direct pursuit, but rather by marking territory. It has been found that jackals respond to chemical and visual markings of wolves during dispersal and try to quickly leave areas with high wolf population density. Unlike solitary wolves in the wild, solitary jackals are able to forage for food much more efficiently and therefore have a higher chance of survival in the wild. The preconceived notion of the jackal as a problematic species may not allow for an unbiased assessment of its impact on ecosystems. In its relations with humans, the jackal in the Polissia is a less problematic species compared to wolves, foxes, or American minks. It is necessary to inform the Ukrainian public, authorities and politicians about existing international legal instruments and European experience in managing populations of carnivorous mammals, including the golden jackal.

Survival, cause‐specific mortality, and population growth of white‐tailed deer in western Virginia

AbstractUnderstanding the role of recruitment in population dynamics of white‐tailed deer (Odocoileus virginianus) is important for management. In the central Appalachian Mountains, deer are part of a largely forested ecosystem that supports 3 carnivore species thought to be capable of influencing white‐tailed deer recruitment: black bears (Urus americanus), coyotes (Canis latrans), and bobcats (Lynx rufus). Yet little is known about predation, how other environmental factors influence recruitment, or the importance of neonate survival to white‐tailed deer population performance in the region. Our objectives were to identify causes of mortality for neonates, analyze effects of landscape attributes on survival of neonates, estimate survival rates for neonates and adult female white‐tailed deer, and to model population growth trends based on current vital rates and hypothetical harvest and neonate survival scenarios. During 2019–2020, we captured 57 neonate deer in Bath County, Virginia, USA, by monitoring 38 pregnant females equipped with global positioning system collars and vaginal implant transmitters and by conducting transect searches for recently born neonates. We observed 37 neonate mortalities and identified cause of death using field and genetic evidence. Mortalities included 28 predation events and 9 deaths from other causes (e.g., abandonment, malnutrition, disease). Black bears accounted for 48.6% of neonate mortalities, and 64.2% of predation events (n = 18), followed by bobcats (n = 5) and coyotes (n = 3). Annual survival for adult female deer was 0.871 and neonate survival to 12 weeks old was 0.310. Elevation was a significant predictor of neonate survival; mortality risk increased 20% for every 100‐m increase in elevation. Models of annual population growth using observed vital rates predicted an increasing population (λ = 1.10). A 10% increase in female harvest would still result in a potential population increase of 2% (λ = 1.02), but a 20% increase in harvest rate would result in a potential 7% decline (λ = 0.93). Neonate survival was higher near fertile valley bottoms and lower along forested ridges characterized by shallow, infertile soils and limited edge or early successional forests. While predation, largely influenced by black bears, was the leading cause of neonate mortality and contributed to low neonate survival, we observed little evidence of population decline, and suggest there is opportunity for a modest increase in harvest of female deer.

Allometric Aboveground Biomass Models for Northern Delhi Ridge Forest

Bio energy obtained through forest biomass is a promising renewable energy option that provides a more environmentally sustainable alternative to fossil resources by reducing the net flux of greenhouse gases to the atmosphere. India, a developing nation is also in the process of building forest biomass models to study the potential of forests in short and long - term carbon mitigation. Earlier, traditional and destructive sampling were the popular methods for the aforesaid purpose. Recently, non - destructive methods have been adopted applying different allometric equations mostly developed outside India. Thus, there was a need to develop non- destructive allometric aboveground (AGB) models complementing the Indian climate. Also, there was a scarcity of domestic/local AGB models for arid, semi- arid, northern tropical thorn forest of India. The objectives of this study were to develop site-specific and mixed- species allometric models to predict AGB, at the Northern Delhi Ridge Forest (NDRF) using nonlinear mathematical functions. The model has a wide scope and can be applied to adjoining areas as well having similar climatic conditions. Three allometric combinations were tried to fit the aboveground biomass data obtained from the ridge forest. A three- parametric Richard’s model (with predictor variable x=D2H) was best fitted to AGB (R2adj= 0.9463) values for larger trees. Meanwhile, for juvenile plants, a three- parametric Richard function was best fitted (R2adj= 0.9733) when (x = DH) was used as a predictor variable. Cross- validation of model parameters exhibited statistical stability.

Ensemble machine learning-based recommendation system for effective prediction of suitable agricultural crop cultivation.

Agriculture is the most critical sector for food supply on the earth, and it is also responsible for supplying raw materials for other industrial productions. Currently, the growth in agricultural production is not sufficient to keep up with the growing population, which may result in a food shortfall for the world's inhabitants. As a result, increasing food production is crucial for developing nations with limited land and resources. It is essential to select a suitable crop for a specific region to increase its production rate. Effective crop production forecasting in that area based on historical data, including environmental and cultivation areas, and crop production amount, is required. However, the data for such forecasting are not publicly available. As such, in this paper, we take a case study of a developing country, Bangladesh, whose economy relies on agriculture. We first gather and preprocess the data from the relevant research institutions of Bangladesh and then propose an ensemble machine learning approach, called K-nearest Neighbor Random Forest Ridge Regression (KRR), to effectively predict the production of the major crops (three different kinds of rice, potato, and wheat). KRR is designed after investigating five existing traditional machine learning (Support Vector Regression, Naïve Bayes, and Ridge Regression) and ensemble learning (Random Forest and CatBoost) algorithms. We consider four classical evaluation metrics, i.e., mean absolute error, mean square error (MSE), root MSE, and R 2, to evaluate the performance of the proposed KRR over the other machine learning models. It shows 0.009 MSE, 99% R 2 for Aus; 0.92 MSE, 90% R 2 for Aman; 0.246 MSE, 99% R 2 for Boro; 0.062 MSE, 99% R 2 for wheat; and 0.016 MSE, 99% R 2 for potato production prediction. The Diebold-Mariano test is conducted to check the robustness of the proposed ensemble model, KRR. In most cases, it shows 1% and 5% significance compared to the benchmark ML models. Lastly, we design a recommender system that suggests suitable crops for a specific land area for cultivation in the next season. We believe that the proposed paradigm will help the farmers and personnel in the agricultural sector leverage proper crop cultivation and production.

Assessment of the Forest Fire Risk and Its Indicating Significances in Zhaoqing City Based on Landsat Time-Series Images

An efficient monitoring of forest fire risk and its dynamic changes is an important way to prevent and reduce forest fire hazards. This study integrated the ignition effect of fire sources and the impact of landform into the calculation of forest fire risk using digital-terrain-slope factor, and developed an optimized forest fire risk model (fire-potential-index slope, FPIS). Combined with Landsat 8 satellite images, the study retrieved and analyzed the variations of forest fire risk in Zhaoqing City, Guangdong province, for four consecutive periods in the dry season, 2019. It was found that the high forest fire risk area was mainly distributed in the valley plains of Huaiji district, Fengkai district and Guangning district, the depressions of the Sihui district, and mountain-edge areas of Dinghu district and Gaoyao district, and accounted for 8.9% on 20 October but expanded to 19.89% on 7 December 2019. However, the further trend analysis indicated that the forest fire risk with significant increasing trend only accounted for 6.42% in Zhaoqing. Compared to the single high forest fire risk results, the changing trend results effectively narrowed the key areas for forest fire prevention (2.48%–12.47%) given the actual forest fires in the city. For the four forest fire events (Lingshan mountain, Hukeng industrial area, Xiangang county and Huangniuling ridge forest fires), it was found that the forest fire risk with significant increasing trend in these regions accounted for 26.63%, 35.84%, 54.6% and 73.47%, respectively, which further proved that the forest fire risk changing trend had a better indicated significance for real forest fire events than the high forest fire risk results itself (1.89%–71.69%). This study suggested that the forest fire risk increasing trend could be well used to reduce the probability of misjudgment and improve the accuracy of the early-warning areas when predicting forest fires.

ANCIENT MAYA ARCHAEOLOGY OF THE MOUNTAIN PINE RIDGE FOREST RESERVE

The Mountain Pine Ridge Forest Reserve is renowned for its natural beauty, but few ancient Maya archaeological sites have ever been recorded there. The paucity of known monumental centers has resulted in it receiving little archaeological attention and an overall view that it is largely devoid of cultural heritage. Yet, the region has long been regarded as the primary source of vital raw materials for the ancient Maya, such as granitic rock for grinding stones. Contrary to the commonly held view that the reserve is a vacant archaeological landscape, recent research by the Rio Frio Regional Archaeological Project is revealing the Mountain Pine Ridge Forest Reserve is a region is rich with a variety of types of archaeological sites, many unique to it. Here we report on the newly documented monumental center of Nohoch Batsó, and the Buffalo Hill Quarries, an industrial-scale multicomponent granitic rock quarry and ground stone implement workshop, the first of its kind ever recorded in the Maya Lowlands

Study of Tree Diversity and Biomass in Natural and Managed Site of Ridge Forest Ecosystem, Delhi Forest, India

Tree diversity and biomass (above and below-ground) were studied in natural and managed sites of Delhi Ridge Forest. The study was conducted in the Northern Ridge (NR) and South-Central Ridge (SCR) of the forest ecosystems. In the natural site of both the ridges, Prosopis juliflora (IVI= 105) was the dominant species due to its invasive nature. Eucalyptus tereticornis (IVI =41.7) and Pongamia pinnata (IVI= 63.5) was were dominant species in the managed site of NR and SCR, respectively. Rare species in the natural site was Wrightia tinctoria. In managed site, Thuja orientalis (IVI=4.08) and Ficus bengalensis (IVI= 4.6) were rare. The maximum biomass was found in aboveground biomass of the natural site of Delhi NR forest i.e. aboveground biomass (AGB) ranged was from 44.59 Mg ha-1 to 89.99 Mg ha-1 while the belowground biomass (BGB) was 17.29 ranged from 9.16 Mg ha-1 to 17.29 Mg ha-1. The least AGB was in the managed site of SCR (44.59 Mg ha-1). The total biomass of the NR ranged between 70.35 to 107.28 Mg ha-1. In SCR, it ranged between 53.75 to 96.22 Mg ha-1 which was low as compared to NR due to high human disturbance and poor soil quality. AGB and tree density was found to be maximum in 10-30 cm diameter class in all the sites of Ridge Forest. Prosopis juliflora was the most important tree species in ridge ecosystem as it allocated approximately 50% of the total biomass. Trees of Delhi ridge forest falls under lower diameter classes due to disturbance regime. Variations in species composition, density, diameter distributionpattern, biomass and Carbon stock in the Northern and South-Central Ridge were attributed to two different forest management practices adopted. Hence, both the Ridge Forest had potential for carbon sequestration due to presence of large number of trees belonging to small dbh classes.

Phytosociology and Diversity Assessment of tree species of Northern Delhi Ridge Forest

The interaction of biodiversity with the physical environment is the bedrock of sustainable development.The world’s forests covered more than 4 billion hectares, accounting for 31% of total land area or 0.6 ha percapita. Tropical forests in India, which are mostly deciduous, are poorly understood in terms ofphytodiversity, phytosociology, and quantification regimes. Ridge forests of Delhi are of great interest forbiodiversity management in the city. Phtyodiversity inventories set a baseline for other forest managementstudies and initiatives. The Northern Delhi Ridge also known as the Kamla Nehru Ridge the study area forthe current work, is located in Delhi, India, one of the significant biodiversity rich areas in the Delhi, tostudy the phytosociological attributes of tree species from the sampled inventory of different tree taxa. Thestudy revealed that average tree density per hectare for the Northern ridge forest as 322 trees/ha.

Paullinieae (Sapindaceae) das restingas do estado do Rio de Janeiro, Brasil: taxonomia e distribuição

Abstract Paullinieae is a predominantly neotropical tribe comprising six genera (Cardiospermum, Lophostigma, Paullinia, Serjania, Thinouia and Urvillea), of which Lophostigma is the only one not found in Brazil. This study was conducted in the sandy coastal plains (restingas) of Rio de Janeiro state, which from the mouth of the Itabapoana river in the north, bordering Espírito Santo state, to Ponta da Trindade (including Ilha Grande) in the south, bordering São Paulo state. This ecosystem has great biodiversity, but has been constantly threatened by deforestation, human occupation and degradation resulting from tourism. In this area we found 30 species in five genera: Cardiospermum (1 sp.), Paullinia (9 spp.), Serjania (15), Thinouia (2) and Urvillea (3). The taxonomic treatment includes a key to identify the taxa, and for each species a morphological description, illustrations, a map of its geographical distribution, ecological information, phenological data, and conservation status. Most species occurred in ridge forests, followed by dune thicket and non-flooded scrub formations. Among of the 30 species, four (Paullinia coriacea, P. ternata, Serjania fluminensis and S. littoralis) were recorded only in the sandy coastal plains, and four are endemic to Rio de Janeiro state (Serjania eucardia, S. fluminensis, S. littoralis and S. tenuis). In addition, four species are already included in the Red List of Brazilian Flora and another three are indicated in this study as threatened. This research is important not only to improve knowledge of Paullinieae species found in Rio de Janeiro’s sandy coastal plains, but also to provide information to be used for conservation measures in the State, as well as in other coastal plains of Brazil.

Foraging and nesting ecology of the Stygian Owl (Asio stygius robustus) in the Mountain Pine Ridge region of Belize

Little is known about the foraging ecology and breeding biology of the Stygian Owl (Asio stygius robustus) across Central America. We located one Stygian Owl roost site in the Mountain Pine Ridge Forest Reserve in the Cayo District of Belize, where we collected pellets over a one-year period (n = 145; Mar 2009–Feb 2010). All identified prey items (n = 194) were passerines (69%), bats (19%), or beetles (12%). We used a proportions test and found seasonal variation in diet, with increased passerine prey consumed in the dry season (Jan–May) and increased beetle prey consumed in the wet season (Jun–Dec). This shift in diet may be influenced by temporal variation of passerine abundance and the emergence of beetles at the start of the wet season. In December 2010, we affixed an adult male Stygian Owl with a VHF transmitter, recorded regular movements using triangulation, and located an occupied nest with a single nestling in sub-montane pine forest habitat. The tagged male had a home range of 36 km2 and was documented regularly flying up to 16 km from the nest site through broad-leaved forest to hunt in agricultural habitat, while roosting and nesting only in sub-montane pine forest. The use of human-created habitats, such as agriculture, could unveil threats not previously of concern for this species (e.g., pesticide use). Our findings further our knowledge on seasonal diet for Stygian Owls and highlight distinct habitat usage for both roosting and foraging, which has important conservation implications for an understudied Neotropical owl.

Herbidospora solisilvae sp. nov., a novel cellulose-degrading actinobacterium isolated from forest soil.

An aerobic, non-motile, Gram-stain positive, cellulose-degrading actinobacterium, designated strain NEAU-GS84T, was isolated from a forest soil sample collected from Linchun Ridge Forest Park in Sanya, Hainan Province, China, and characterized using a polyphasic approach. Morphological and chemotaxonomic characteristics indicated that strain NEAU-GS84T could belong to the genus Herbidospora. The 16S rRNA gene sequence analysis indeed confirmed that strain NEAU-GS84T belonged to the genus Herbidospora and was most closely related to Herbidospora yilanensis JCM 18062T (99.2% 16S rRNA gene sequence similarity) and Herbidospora galbida NEAU-GS14T (99.0%). The cell wall of strain NEAU-GS84T contained meso-diaminopimelic acid as the major diamino acid and the whole-cell hydrolysates mainly contained glucose, madurose and ribose. The major polar lipids were diphosphatidylglycerol, phosphatidylmethylethanolamine, phosphatidylethanolamine, hydroxyphosphatidylethanolamin, phosphoglycolipids, two phosphatidylinositol mannosides and one unidentified phospholipid. The predominant menaquinone was MK-10(H4). Major fatty acids were 10-methly C17:0, C17:0 and iso-C16:0. These chemotaxonomic data substantiated the affiliation of strain NEAU-GS84T to the genus Herbidospora. The DNA G+C content was 70.7mol%. The genome size of strain NEAU-GS84T is about 8.37Mb and contained 41 cellulose-binding domain synthesis genes, 13 β-glucosidase synthesis genes, 6 endoglucanase synthesis genes and 9 xylanase synthesis genes. Based on digital DNA-DNA hybridization and average nucleotide identity values, the new strain NEAU-GS84T could be differentiated from its closest relatives. Therefore, the strain represents a novel species of the genus Herbidospora, for which the name Herbidospora solisilvae sp. nov. is proposed. The type strain is NEAU-GS84T (= CCTCC AA 2018041T = JCM 33460T).

Vegetation Patterns in Waisoi Primary Rainforest, Southeast Viti Levu, Fiji

The vegetation composition and structure of “pristine” primary lowland rainforest in Waisoi, south Viti Levu, Fiji were assessed quantitatively by recording all trees with a diameter at breast height > 1 cm within sample plots covering the topographic range of the Waisoi area. The tree flora comprised 78 recognizable taxa, 68 of which were recorded to species. Of these 68 species, 61% were endemic. Four forest types were evaluated; “River Flat,” “Slope,” “Ridge,” and “Quasi-montane.” Differences in stem density, species richness, and diversity were observed across the forest types. The River Flat and Quasi-montane forest types were distinct from each other and from Slope and Ridge forests. Canopy structure was characterized for each of these forest types and illustrated with profile diagrams.

The Effects of Canopy Morphology on Flow Over a Two‐Dimensional Isolated Ridge

AbstractMomentum and mass exchanges between the atmosphere and forests situated on complex terrain continue to draw significant research attention primarily because of their significance to a plethora of applications. In this paper, we investigated flows behavior on the leeward side of a two‐dimensional forested ridge under neutrally stratified conditions using large‐eddy simulations (LESs). The goal is to understand how variations in leaf area index (LAI), vertical canopy foliage distributions, and forest edge positions affect mean/turbulent flow statistics, momentum fluxes, and onset of recirculation patterns. Although pressure perturbations are dominated by the hill shape, it is demonstrated here that changes in canopy foliage distribution modulate intensities and patterns of the leeward adverse pressure gradients. Such changes in the adverse pressure gradients alter the mean velocity streamlines including the patterns and magnitudes of the leeward downward mean vertical velocity and the velocity variances and momentum flux in the wake region. While a downwind recirculation zone develops in all cases, the details regarding the incipient location and recirculation zone size vary including positions of the separation and reattachment points. Furthermore, changes in the strength and depth of the zone occur due to canopy‐induced changes in adverse pressure gradients, advection, and canopy drag. Because the recirculation zone impacts the local mean advective terms in momentum and scalar exchanges, the simulations here indicate that canopy morphology‐induced changes in the leeward flows have significant implications to both measurements and models of biosphere‐atmosphere exchange over complex terrain.

The interaction of clonality, breeding system and genomics for a highly threatened plant species and the management implications

Clonal plants provide a challenge to ecological management and restoration programs. Clonal plants frequently occur as few genets over large spatial scales and may persist for hundreds of years. Hence population structures, effective population sizes and breeding systems of clonal plants are not well understood or managed at scales applicable to non-clonal species. This is a critical issue because clonality is a common trait including among threatened plants and more studies into the management requirements of clonal plant species are required. We investigate the impact of reducing the population size of a highly clonal species and how these impacts can be minimized.Persoonia hindiihas a restricted distribution in forested ridges on Newnes Plateau west of Sydney, Australia. We collated data and surveyed populations, undertook assessments of reproductive patterns (flowering; pollination; fruit set and fall), and modelled pollen dispersal among genets. We relate this assessment to planning approaches uninformed by genet structure and reproductive patterns. Small sites likely function as discrete populations, each with low numbers of genets. Genet diversity at this site scale is important as it is associated with increased fruit set. Loss of plants from populations poses a significant risk to population level fitness if genet diversity is reduced. There is an urgent need for more biologically informed approaches for the management of clonal plant species.

PNS147 VISUALIZATION AND COMMUNICATION OF RESULTS FROM BAYESIAN NETWORK META-ANALYSIS: PAST, PRESENT, AND FUTURE

Network meta-analysis (NMA) is commonly conducted within a Bayesian framework, with presentation and communication of results informed by previously published guidance documents. Recently, authors have proposed a multiplicity of approaches to visualize and report findings. This has caused issues in comparability of analyses across publications and complication in interpretation of results by non-statistical stakeholders. We provide recommendations for the use and interpretation of Bayesian NMA results and propose a standard battery of visualizations and statistics to improve understanding of this methodology. We compared communication and visualization of results of Bayesian NMAs from recent publications. Resulting approaches were classified according to their purpose and were assessed as to whether they: (a) support the intended use; (b) introduce difficulty in interpretation; and (c) adhere to a Bayesian decision-making framework. Core visualizations of Bayesian NMAs have remained relatively unchanged since initial publications. The choice of summary differs according to whether the goal is to compare a single agent to comparators (i.e., typically sponsored publications) or to estimate comparative effectiveness more broadly for academic or health technology assessment purposes. Heatmaps have been introduced to provide rapid summaries of various output statistics. Attempts to communicate balance of benefit and harm has focused on bivariate SUCRA plots that may be difficult to interpret when absolute rates differ. Composite forest plots augmented by additional summary characteristics such as probability better offer an attractive option to display interval estimates alongside Bayesian summaries, although the conventional focus on 95% intervals may inadvertently encourage dichotomization of evidence. We introduce two new visualizations: the ridge forest plot and minimally important benefit curves to support Bayesian presentation and interpretation of results. Communication of Bayesian NMAs for non-statistical audiences can be improved through clear recommendations for standard comprehensive reporting. We provide initial recommendations for visualization and communication of Bayesian NMA results.