Real Forests Research Articles

From Virtual Trees to Real Forests: Public Participation in Virtual Forest Realization Projects in China

With the rapid development of Internet technology, the channels for the public to participate in forest protection and ecological construction have been expanded. In China, virtual forest realization projects have successfully heightened environmental awareness among the public. However, these projects have also faced a “green gap”, characterized by a substantial disconnect between environmental intentions and actual participation behaviors. Based on 69 articles about virtual forest realization projects in China, this paper aims to reveal the roots of the intention–behavior gap, influencing factors, and potential mitigation strategies. Our findings indicate the following: (1) While virtual forest realization initiatives have made progress, they still face multiple challenges such as governmental inefficiencies and platform traffic bottlenecks. (2) The factors influencing public participation in virtual forest realization projects can generally be categorized into three types: external situational factors, internal psychological factors, and demographic variables. Initially, external influences like online word-of-mouth and gamified platforms played a crucial role in attracting the public. Over time, internal factors such as public trust in the platform and perceived enjoyment have become more prominent. Inconsistent findings regarding demographic variables suggest a need for further research. (3) Current solutions primarily focus on macro policies and have not fully addressed existing challenges. This study reveals the reasons and influencing factors of the intention–behavior gap, with the goal of offering valuable insights for future public engagement and project optimization.

Complementarity with Real Forests: A Conceptual Framework and Narrative Review of Multidimensional Effects in Virtual Forests

Numerous studies have confirmed the positive impacts of real forests in areas such as stress relief. However, not everyone can visit forests easily. Virtual technologies offer new ways of experiencing forests for people who are hindered by real-life conditions and provide researchers with a manageable mode of study. Recently, there has been an influx of relevant research; however, themes within the overall perspective of the field remain unclear. This study aimed to review the literature and provide an overview of the potential health benefits of virtual forests. Research themes were extracted, and a conceptual framework for the multidimensional effects of virtual forest exposure was proposed from a holistic perspective. We analyzed studies using descriptive analytical methods through the Scopus, Web of Science, and PubMed databases and snowball searches. In total, 58 studies were included. This review identified four themes and segments throughout the virtual forest exposure process: core elements, experiences, effects, and circulation. We propose a new conceptual framework for a holistic perspective that incorporates technological features that are specific to virtual environments and makes connections to real forests. Finally, perspectives for future research in virtual forest therapy and its practical implications are discussed.

Leveraging data-driven and procedural methods for generating high-fidelity visualizations of real forests

Forests are indispensable in mitigating climate change due to their ability to sequester and store large amounts of carbon. Forest restoration and maintenance activities are crucial for retaining and enhancing this capacity. To promote sustainable practices, stakeholders need to assess the potential impacts of forestry operations. But in-depth comprehension of the forest dynamics is challenging due to the complex interactions between various ecosystem components. High-fidelity, immersive visualizations can support sense- and decision-making processes by facilitating the exploration of scientific and non-scientific data in the respective spatial, temporal, and semantic contexts. However, producing accurate representations of diverse ecosystems is complex and time-consuming. In this paper, we introduce a forest visualization prototype providing realistic representations of forest stands and different simulated scenarios. The utilized data-driven and procedural approach ensures efficiency, reproducibility, and accuracy. Furthermore, we present an array of requirements for realistic forest visualizations gathered through questionnaires and interviews with forestry experts.

A Novel Strategy for Constructing Large-Scale Forest Scene: Integrating Forest Hierarchical Models and Tree Growth Models to Improve the Efficiency and Stability of Forest Polymorphism Simulation

Modeling large-scale scenarios of diversity in real forests is a hot topic in forestry research. At present, there is a common problem of simple and poor model scalability in large-scale forest scenes. Forest growth is often carried out using a holistic scaling approach, which does not reflect the diversity of trees in nature. To solve this problem, we propose a method for constructing large-scale forest scenes based on forest hierarchical models, which can improve the dynamic visual effect of large-scale forest landscape polymorphism. In this study, we constructed tree hierarchical models of corresponding sizes using the detail attribute data of 29 subplots in the Shanxia Experimental Forest Farm in Jiangxi Province. The growth values of trees of different ages were calculated according to the hierarchical growth model of trees, and the growth dynamic simulation of large-scale forest scenes constructed by the integrated model and hierarchical model was carried out using three-dimensional visualization technology. The results indicated that the runtime frame rate of the scene constructed by the hierarchical model was 30.63 fps and the frame rate after growth was 29.68 fps, which met the operational requirements. Compared with the traditional integrated model, the fluctuation value of the frame rate of the hierarchical model was 0.036 less than that of the integrated model, and the scene ran stably. The positive feedback rate of personnel evaluation reached 95%. In this study, the main conclusion is that our proposed method achieves polymorphism in large-scale forest scene construction and ensures the stability of large-scale scene operation.

The Bølling-Allerød Transition in the Eastern Baltic: Environmental Responses to Climate Change.

This paper presents the results of a study on the Kulikovo section (south-eastern Baltic Sea coast), a sediment sequence exposing deposits of a post-glacial basin that existed along the edge of the glacier in the Late Pleistocene. The research was targeted at the reconstruction of the dynamics of the local environmental systems in response to climatic oscillations of the Lateglacial (the Older Dryas-first half of the Allerød). The evolution of the local biotic components on the territories of the Baltic region after the ice retreat is still poorly understood. Data from geochronological, lithological, diatom, algo-zoological and palynological analyses provide a reconstruction of local aquatic and terrestrial biocenoses and their response to short-term warmings and coolings that took place 14,000-13,400 cal yr BP. This study has demonstrated that, during the Older Dryas and first part of the Allerød (GI-1d and GI-1c), the aquatic and terrestrial environment of the Kulikovo basin underwent several changes, resulting in eight stages of the basin evolution, most probably related to the short-term climatic fluctuations that could have had a duration of several decades. The data obtained in this study have revealed the fairly dynamic and complex evolution of the pioneer landscapes, as indicated by the changes in the hydrological regime of the area and by the traced successions of plant communities from the pioneer swampy vegetation to park and real forests towards the middle of the Allerød.

From Virtual Trees to Real Forests: The Impact of Gamification Affordances on Green Consumption Behaviors in Ant Forest

ABSTRACT Gamification, an outcome of technological advancement, serves as a promising environmental communication strategy to promote green behavior. However, little is known regarding the key affordances which attract users, or of the potential mechanism of gamification affordances on green consumption behaviors. Focusing on the gamification paradigm, this study sheds light upon this topic by constructing a serial mediation model to explore the impacts of gamification affordances on green consumption behaviors, as well as the serial mediating role of value perceptions (i.e. hedonic, utilitarian, social) and environmental concerns. This study employed a dual-stage design comprising the qualitative method via text-coding analysis using 18,069 comment postings, and the quantitative method via an online survey in China with 486 respondents to validate the model using the example of Ant Forest. Results indicate that gamification affordances positively affect users’ value perceptions, which in turn promote environmental concerns. Moreover, value perceptions and environmental concerns are shown to serially mediate the link between gamification affordances and green consumption behaviors. These findings help advance knowledge in the domain of gamification and environmental communication, and provide practical suggestions as to how to better communicate with users on environmental issues.

Taxonomy and Biogeography of Andinia-Complex (Orchidaceae)

The results of a revision of the orchid genus Andinia are presented. The proposed classification is based on outcomes of morphological and molecular studies. Additionally, the similarity of the climatic niches occupied by representatives of the Andinia-complex was calculated and visualized. The highest number of Andinia representatives is found in the Eastern Cordillera real montane forests, while Neooreophilus species are found in two ecoregions—the Eastern Cordillera real montane forests, and the Northwestern Andes. According to the level of endemism, a very unique orchid flora was noted in the Guajira–Barranquilla xeric scrub ecoregion, as well as in the Isthmian-Pacific and the Ucayali moist forests, where single endemic species occur. In the proposed classification, nine genera are recognized within the Andinia-complex, three of which (Xenosiella, Chicalia, and Minuscula) are described in this paper. A key to the identification of all genera is provided. Additionally, sections Amplectentes and Bilamellatae of Neooreophilus are elevated to the subgeneric rank, and subgenus Aenigma is here considered as a separate genus. A complete list of representatives of each taxon is provided, and new combinations are proposed accordingly. A new species of Neooreophilus from Colombia is described.

Numerical Investigation on the Effects of Forest Heterogeneity on Wind-Turbine Wake

This work aims at investigating the effects of forest heterogeneity on a wind-turbine wake under a neutrally stratified condition. Three types of forests, homogeneous (idealized), a real forest having natural heterogeneity, and an idealized forest having a strong heterogeneity, are considered in this study. For each type, three forest densities with Leaf Area Index (LAI) values of 0.42,1.7, and 4.25 are investigated. The data of the homogeneous forest are estimated from a dense forest site located in Ryningsnäs, Sweden, while the real forest data are obtained using an aerial LiDAR scan over a site located in Pihtipudas, about 140 km north of Jyväskylä, Finland. The idealized forest is made up of small forest patches to represent a strong heterogeneous forest. The turbine definition used to model the wake is the NREL 5 MW reference wind turbine, which is modeled in the numerical simulations by the Actuator Line Model (ALM) approach. The numerical simulations are implemented with OpenFOAM based on the Unsteady Reynolds Averaged Navier–Stokes (U-RANS) approach. The results highlight the effects of forest heterogeneity levels with different densities on the wake formation and recovery of a stand-alone wind-turbine wake. It is observed that the homogeneous forests have higher turbulent kinetic energy (TKE) compared to the real forests for an LAI value less than approximately 2, while forests with an LAI value above 2 show a higher TKE in the real forest than in the homogeneous and the strong heterogeneous (patched) forest. Technically, the deficits in the wake region are more pronounced in the strong heterogeneous forests than in other forest cases.

Clumping Effects in Leaf Area Index Retrieval From Large-Footprint Full-Waveform LiDAR

Clumping effect denotes the nonrandomness of foliage. It deviates from the random distribution assumption of Beer’s law which is usually applied to leaf area index (LAI) retrieval from large-footprint full-waveform light detection and ranging (LiDAR). Some studies correct for large gaps-induced between-crown clumping, yet ignore the within-crown clumping. The error of LAI caused by these clumping effects and the influence of the forest structure parameters on them have not been quantitatively studied. This study quantified the between-crown, within-crown, and total clumping indices through a theoretical derivation, clarifying the mechanism of clumping; we used airborne LiDAR point clouds data in 11 290 footprints (diameter = 25 m) to estimate these indices in real forests. We found that: 1) the underestimation of LAI caused by directly applying Beer’s law could be up to 93%, and it decreases with fractional crown coverage but increases with crown length and leaf area density; 2) the method of correcting between-crown clumping improves LAI retrieval for cylindrical canopies effectively; however, 3) considerable underestimation (up to 58%) exists if we neglect the within-crown clumping for other canopies, which has not been realized before; and 4) both the between-crown and the within-crown clumping can be the dominant contributor, and the within-crown clumping was greater than the between-crown clumping in 47% of the studied footprints. In the two physically based LAI retrieval methods, Beer’s law has been commonly used due to its simplicity. Pathways to improve future LAI retrieval would be instrument improvement to capture the between-crown gaps and method study to correct the within-crown clumping further.

Divergent Pathways of Nitrogen-Fixing Trees through Succession Depend on Starting Nitrogen Supply and Priority Effects.

AbstractNitrogen-fixing trees are a major potential source of nitrogen in terrestrial ecosystems. The degree to which they persist in older forests has considerable implications for forest nitrogen budgets. We characterized nitrogen-fixing tree abundance across stand age in the contiguous United States and analyzed a theoretical model to help understand competitive outcomes and successional trajectories of nitrogen-fixing and nonfixing trees. Nitrogen-fixing tree abundance is bimodal in all regions except the northeastern United States, even in older forests, suggesting that competitive exclusion (including priority effects) is more common than coexistence at the spatial scale of our analysis. Our model analysis suggests conditions under which alternative competitive outcomes are possible and when they are transient (lasting decades or centuries) versus persistent (millennia). Critically, the timescale of the feedbacks between nitrogen fixation and soil nitrogen supply, which is thought to drive the exclusion of nitrogen-fixing trees through succession, can be long. Therefore, the long transient outcomes of competition are more relevant for real forests than the long-term equilibrium. Within these long-term transients, the background soil nitrogen supply is a major determinant of competitive outcomes. Consistent with the expectations of resource ratio theory, competitive exclusion is more likely at high and low nitrogen supply, while intermediate nitrogen supply makes coexistence or priority effects possible. However, these outcomes are modified by the nitrogen fixation strategy: obligate nitrogen fixation makes coexistence more likely than priority effects, compared with perfectly facultative fixation. These results advance our understanding of the successional trajectories of nitrogen-fixing trees and their effects on ecosystem development in secondary succession.

Efficient synthetic generation of ecological data with preset spatial association of individuals

Many experiments cannot feasibly be conducted as factorials. Simulations using synthetically generated data are viable alternatives to such factorial experiments. The main objective of the present research is to develop a methodology and platform to synthetically generate spatially explicit forest ecosystems represented by points with a predefined spatial pattern. Using algorithms with polynomial complexity and parameters that control the number of clusters, the degree of clusterization, and the proportion of nonrandom trees, we show that spatially explicit forest ecosystems can be generated time efficiently, which enables large factorial simulations. The proposed method was tested on 1200 synthetically generated forest stands, each of 25 ha, using 10 spatial indices: Clark–Evans aggregation index; Ripley’s K; Besag’s L; Morisita’s dispersion index; Greig–Smith index; the size dominance index of Hui; index of nonrandomness of Pielou; directional index and mean directional index of Corral–Rivas; and size differentiation index of Von Gadow. The size of individual trees was randomly generated aiming at variograms such as real forests. We obtained forest stands with the expected spatial arrangement and distribution of sizes in less than 1 h. To ensure replicability of the study, we have provided free, fully functional software that executes the stated tasks.

Individual tree identification using a new cluster-based approach with discrete-return airborne LiDAR data

Individual tree identification is a key step for forest surveying and monitoring. To identify individual trees with airborne LiDAR data, a local maximum (LM) filter technique is typically performed. With LM, the highest point in a filtering window is generally considered to represent the tree position. This assumption, however, has great limitations, especially for mixed forests. To address this problem, we developed a new approach, the cluster center of higher points (CCHP), for tree position detection with LiDAR data. CCHP assumes that a tree position is located at the clustering center of higher points within a spatial neighborhood, and the center can be detected by a location-based recursive algorithm. The developed CCHP method was applied to a simulated forest and then verified in two real urban forests. In comparison with the variable window-sized LM filter method and layer stacking method, CCHP successfully identified 97% of trees in the simulated forest, while only 78% and 81% of the trees were recognized by LM and layer stacking methods respectively. The average absolute and relative offsets of CCHP are 0.33 m and 6.59%, respectively, and over 80% of the detected trees have an offset of less than 10% of the tree crown radius. CCHP also correctly detected 93.80% and 88.74% of individual trees in the first and second real forests, respectively, but the detection rates from the variable window-sized LM approach and layer stacking were less than 80%. In addition, the tree positions located by CCHP are considerably more accurate than the other two methods. Therefore, CCHP is proven to be promising for detecting individual tree positions from airborne LiDAR data for both simulated and real forests.

Downstream protection value: Detecting critical zones for effective fuel-treatment under wildfire risk

The destructive potential of wildfires has been exacerbated by climate change, causing their frequencies and intensities to continuously increase globally. Generating fire-resilient landscapes via efficient and calculated fuel-treatment plans is critical to protecting native forests, agricultural resources, biodiversity, and human communities. To tackle this challenge, we propose a framework that integrates fire spread, optimization, and simulation models. We introduce the concept of Downstream Protection Value (DPV), a flexible metric that assays and ranks the impact of treating a unit of the landscape, by modeling a forest as a network and the fire propagation as a tree graph. Using our open-source decision support system, custom performance metrics can be optimized to minimize wildfire losses, obtaining effective treatment plans. Experiments with real forests show that our model is able to consistently outperform alternative methods and accurately detect high-risk and potential ignition areas, focusing the treatment on the most critical zones. Results indicate that our methodology is able to decrease the expected area burned and fire propagation rate by more than half in comparison to alternative methods under ignition and weather uncertainty.

Root Systems

38 CARSON ASH BEKER Root Systems  Trees in real forests share information below ground. Through root systems, mycorrhizal networks, they transmit information. —Dr. Susanne Simard Transmission: Enter forest; enter Us, one (1) Red Riding Hood. Transmission: Received. Red Riding Hood enters the forest where her grandmother entered before, but does not leave. Transmission: Lost. Transmission: A crow flies above the canopy, lifted in its wings. From above, the forest is shaped like the dot of a green question mark. And beyond? Transmission: Signal lost. Why? Where did the crow go? Where did Red Riding Hood go? Transmission: To: Forest Eyes That Look And Don’t Blink Question: What was she wearing? Red Riding Hood is a girl wearing a provocative cloak = Danger Red Riding Hood is a boy wearing a hoodie = Danger Red Riding Hood was neither a girl nor a boy; in fact, the first time they put on the red riding hood was the first time they knew an answer to the question, What are you? In the red folds of that red hood— 39 Transmission: Received. Answer: I am Red Riding Hood. You need this type of I to do things like enter the woods. And get lost. Transmission: A crow flies above the canopy of the forest. The air that spins around the trees captures the smell of a squirrel, not alive but alive inside with bugs. The smell circles upward and catches the crow, so it dives. Transmission: When a bird flies, is the flight in the feathers or in the bird? This is a trick question, distracts the crow from the bigger question of the hawk approaching, compressing air. Where go the crow? The crow falls, is eaten. The crow falls, is eaten. Some of the crow hits the ground—two wings; loam, redwood pine— and begins to sink slowly. Decomposition. Transmission. Transmission. Transmission: A crow flies and flies above a green forest that is not there anymore, no more than the crow is there. The crow and the forest are here, in transmission. Transmission: The crow fell and the forest ended. Question: Why did the forest end? Transmission: [Cut. Not received.] Transmission: A lumberjack cuts trees, cuts root systems, cuts lines. Transmission: Around the crow there is wolf. What’s the deal with this wolf? Transmission: The wolf ate only one wing. He should have eaten two. Longing for flight without being able to. That’s the kind of thing that makes fairy-tale wolves cruel. 40 Root Intersection: Under The Outhouse Behind Grandma’s House: So Many Transmissions! The lumberjack destroyed the forest. Grandmaandthelumberjackarehavingtea.Theyhaveteaevery Wednesday. Their stories cross at the root systems under Grandma’s outhouse. He was trespassing. She was generous. It was embarrassing. They had tea. The lumberjack carries in his heart the spit of his father (also a lumberjack) because: splinters. After tea, the lumberjack goes out back. To chop some wood, he says. But really to use the outhouse, with its sunken-in roof open to the canopy and the stars, looking. Transmission: Brightness Of Stars: Cookies: Compost: Decomposition And she, Grandmother, crosses the kitchen and puts on his lumberjack flannel and the smell of sweat and wood shavings (Transmission), and she looks in the mirror, and she likes what she sees—the way her short white hair now stands up, the way the sag of her two breasts in the flannel seems to say something different than Old&Tired. Transmission: Take That&Fuck You Grandma pushes her legs out and sticks her thumbs into the waistband of her grey pajamas and scowls at her reflection. She takes a fork, and now it’s a cigarette, and she props one foot against the wall behind her, which is where the lumberjack finds her, walking through the door, he buckling up his pants, she smoking a cigarette-fork. “I’ll trade you for a day,” is the lumberjack’s transmission. Transmission: The lumberjack is thinking how nice it would be to stay here in the kitchen, near the outhouse, and bake. He puts on the apron. Grandmother walks out the back door and picks up the ax. 41 Transmission: How did Red Riding Hood get mixed up with the wolf? Response...

Effectively tuning plant growth models with different spatial complexity: A statistical perspective

Forest gap models (non-spatial, patch- and individual-based models) and size structure models (non-spatial stand models) rely on two assumptions: the mean field assumption (A-I) and the assumption that plants in one patch do not compete with plants in other patches (A-II). These assumptions lead to differences in plant size dynamics between these models and spatially explicit models (or observations of real forests). Therefore, to more accurately replicate dynamics, these models require model tuning by (1) adjusting model parameter values or (2) introducing a correction term into models. However, these model tuning methods have not been systematically and statistically investigated in models using different patch sizes.We used a simple spatially explicit model that simulated growth and competition processes, and rewrote it as patch models. The patch sizes of the patch models were set between 4 and 1500m2. First, we estimated the parameter values (the intrinsic growth rate, metabolic loss, competition coefficient, and competitive asymmetry) of these models that best reproduce plant size growth under competition using field data from a Sakhalin fir stand, and compared the parameter values among the models. Second, we introduced correction terms into the patch models and estimated the optimal correction term for reproducing plant size growth under competition using the field data.The estimated parameter values of the patch models for all patch sizes differed greatly from those of the spatially explicit models. Therefore, parameter values should not be shared between spatially explicit models and patch models. In addition, the parameter value sets for the models with small patches differed from those with large patches. This is because parameter values for small patches mainly improve biases of A-II, while those for large patches mainly improve biases of A-I. Therefore, parameter values should not be shared between patch models with small patches and with large patches.The estimated correction term in the patch models with large patches excluded the competitive effects of small and medium-sized plants on their neighbors, even though these effects exist in real stands. This exclusion can be ascribed to the discrepancy between their competition in real plant populations and A-I. Therefore, the competitive effects of small and medium-sized plants should not be included in patch models with large patches. Finally, the reproducibility of the models tuned with correction terms was higher than those with adjusted parameters.

Tree Morphologic Plasticity Explains Deviation from Metabolic Scaling Theory in Semi-Arid Conifer Forests, Southwestern USA.

A significant concern about Metabolic Scaling Theory (MST) in real forests relates to consistent differences between the values of power law scaling exponents of tree primary size measures used to estimate mass and those predicted by MST. Here we consider why observed scaling exponents for diameter and height relationships deviate from MST predictions across three semi-arid conifer forests in relation to: (1) tree condition and physical form, (2) the level of inter-tree competition (e.g. open vs closed stand structure), (3) increasing tree age, and (4) differences in site productivity. Scaling exponent values derived from non-linear least-squares regression for trees in excellent condition (n = 381) were above the MST prediction at the 95% confidence level, while the exponent for trees in good condition were no different than MST (n = 926). Trees that were in fair or poor condition, characterized as diseased, leaning, or sparsely crowned had exponent values below MST predictions (n = 2,058), as did recently dead standing trees (n = 375). Exponent value of the mean-tree model that disregarded tree condition (n = 3,740) was consistent with other studies that reject MST scaling. Ostensibly, as stand density and competition increase trees exhibited greater morphological plasticity whereby the majority had characteristically fair or poor growth forms. Fitting by least-squares regression biases the mean-tree model scaling exponent toward values that are below MST idealized predictions. For 368 trees from Arizona with known establishment dates, increasing age had no significant impact on expected scaling. We further suggest height to diameter ratios below MST relate to vertical truncation caused by limitation in plant water availability. Even with environmentally imposed height limitation, proportionality between height and diameter scaling exponents were consistent with the predictions of MST.

A Voronoi tessellation based approach to generate hypothetical forest landscapes

Optimization models used for forest planning can be computationally complex and the demand for real forest data to test them far exceeds the supply. As a result, hypothetical forest landscapes are often used, although their capacity to match the characteristics of real forests is limited and they offer little control over important landscape metrics such as average adjacency. Using four landscape metrics that are believed to be relevant to the computational efficiency of forest harvest scheduling models, we describe a new method for generating hypothetical landscapes of prespecified characterization. The new approach produces landscapes based on Voronoi tessellation, created from points chosen by a combination of random point processes. Through a series of multiple regressions, the proposed algorithm determines appropriate control parameters to ensure that the output landscape will match target characteristics within a given statistical tolerance and with a predefined probability. The new method can produce landscapes with a wide range of specifications, covering the characteristics of real forests and extending into extreme cases unlikely to be encountered in reality. At the same time, the method provides greater flexibility and control over the generated landscapes than previous methods.

A single-bounce method for estimating impulse propagation and attenuation in a forest

There are numerous methods for determining the impact of interactions with multiple scattering objects on a propagating signal. Many of these methods assume that the signal is continuous in time, allowing one to neglect time dependence. Additionally, these methods make assumptions about the spatial distribution of scattering objects, such as lattice or random, and many assume that the scattering objects are all identical. Real forests often have trees of varying trunk diameters and may be arranged in a grid, in clusters, or random, and the assumptions of uniform size and particular spatial distributions introduce error into the assessments. A simple model, based on single bounces from trunks, is developed to begin estimating the propagation of an impulsive signal through this complicated multiple scattering environment. The scattering algorithm takes the frequency-dependent radial scattering pattern of a cylinder into account. Results are compared to data collected in a forest stand where the locations and diameters of trunks were carefully recorded. These comparisons provide insight into whether a single, discrete bounce method is sufficient for modeling impulse propagation in this complex environment, or whether multiple discrete bounces or some other method should be explored.

Ecosystem transformation by emerging infectious disease: loss of large tanoak from California forests

Summary1. Few pathogens are the sole or primary cause of species extinctions, but forest disease has caused spectacular declines in North American overstorey trees and restructured forest ecosystems at large spatial scales over the past 100 years. These events threaten biodiversity associated with impacted host trees and other resources valued by human societies even when they do not directly cause host extinction.2. Invasion of Phytophthora ramorum and emergence of the forest disease sudden oak death has caused a large‐scale decline of tanoak (Notholithocarpus densiflorus) in Californian coastal forests. Here, we describe structural changes to tanoak forests and develop predictive models of infection rates, mortality rates and changes in tanoak biomass and abundance by combining regionally extensive longitudinal field studies and mathematical modelling.3. Pathogen‐invaded stands had smaller average tanoak tree size and higher proportions of large dead tanoak trees compared with uninvaded stands. This pattern is caused in part by a positive relationship between tanoak size and mortality rate, as well as prolific basal sprouting from trees killed by the disease. Tanoak infection, mortality and biomass decline rates were positively related to the prevalence of infection in sporulation‐supporting species, especially California bay laurel (Umbellularia californica).4. We developed a stage‐structured and spatially explicit mathematical model including species dynamics and P. ramorum transmission, where the long‐term outcome of disease ranges from host extinction when densities of bay laurel are high to limited or no disease outbreak. Low densities of tanoak in a matrix of non‐susceptible neighbouring species resulted in slow‐enough transmission to retain overstorey tanoak, suggesting host‐density thresholds may exist in real forests.5. Synthesis. Tanoak is likely to persist in many disease‐impacted forests via vegetative reproduction, but overstorey trees may be eliminated or greatly reduced in abundance, a pattern similar to other forest diseases that have emerged in the last century including chestnut blight and beech bark disease. Our results support a general model of disease‐caused changes to forest trees useful for the analysis of emerging forest pathogens where vegetative reproduction, community‐level epidemiology and stage‐specific mortality rate interact to determine local disease intensity and host decline.

Modelling the forest carbon budget of a Mediterranean region through the integration of ground and satellite data

This paper introduces an innovative modelling strategy aimed at simulating the main terms of net forest carbon budget (net primary production, NPP and net ecosystem exchange, NEE) in Tuscany (Central Italy). The strategy is based on the preliminary calibration and application of parametric and bio-geochemical models (C-Fix and BIOME-BGC, respectively), which simulate the behaviour of forest ecosystems close to equilibrium condition (climax). Next, the ratio of actual over-potential tree volume is computed as an indicator of ecosystem distance from climax and is combined with the model outputs to estimate the NPP and NEE of real forests. The per-pixel application of the new modelling strategy was made possible by the collection of several data layers (maps of forest type and volume, daily meteorological data and monthly normalized difference vegetation index (NDVI) images for the years 1999–2003) which served to characterize the eco-climatic and forest features of the region. The obtained estimates of forest NPP and NEE were evaluated against ground measurements of accumulated woody biomass and net carbon exchange. The results of these experiments testify the good potential of the proposed strategy and indicate some problem areas which should be the subject of future research.