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.

Assessment of Differential Forest Growth Following Disturbance in Minnesota, USA

We used LiDAR metrics and satellite imagery to examine regeneration on forested sites disturbed via harvest or natural means over a 44-year period. We tested the effectiveness of older low-density LiDAR elevation data in producing information related to existing levels of above ground biomass (AGB). To accomplish this, we paired the elevation data with a time series of wetness and greenness indices derived from Landsat satellite imagery to model changes in AGB for sites experiencing different agents of change. Current AGB was determined from high-density LiDAR acquired in northern Minnesota, USA. We then compared high-density LiDAR-based AGB and estimates modeled using Landsat and low-density LiDAR indices for 10,068 sites. Clear differences were found in standing AGB and accumulation rates between sites disturbed by different agents of change. Biomass accumulation following disturbance appears to decrease rapidly following an initial spike as stands 1asZX respond to newly opened growing space. Harvested sites experienced a roughly six-fold increase in the rate of biomass accumulation compared to sites subjected to stand replacing fire or insect and disease, and a 20% increase in productivity when compared to sites subjected to wind mediated canopy loss. Over time, this resulted in clear differences in standing AGB.

Influence of soil moisture level on metabolism of non-structural carbohydrates in Quercus robur leaves

The long-term increases in average temperature and intensification of droughts which characterise the current state of the Earth’s climate system have a negative impact on forest ecosystems and can lead to a decrease in their area and deterioration of the living conditions of their components. In the conditions of the Ukrainian Steppe an important environmental, antierosion, water-protective and soil-protective role belongs to the ravine forests. The most valuable component of the ravine forests is presented by natural populations of common oak (Quercus robur L.), which are able to tolerate the arid climate typical of the steppe region. But with global warming, the endurance of this species is changing. It is believed that a significant role in plant adaptation to drought and high temperatures may belong to non-structural carbohydrates. Therefore, it is important to study changes in the concentration of these substances in the leaves of this leading species under the action of adverse hydrothermal conditions. The article analyzes the content and dynamics of soluble sugars (glucose, fructose, sucrose) and starch in the leaves of Quercus robur L. under different forest growth conditions of the ravine forest (hygromesophilic (CL2–3), mesoxerophilic (CL1) and xerophilic (CL0)). The research was conducted in the forest in the Viyskove area (steppe zone of Ukraine) in the thalweg and at different levels of slope of southern exposure. Content of glucose, fructose, sugar and starch in Quercus robur leaves was determined. It was found that when exposed to high temperatures and increasing water stress during the vegetation period in xerophilic (CL0–1) and mesoxerophilic (CL1) forest growth conditions, the concentration of both glucose and sucrose in the leaves of Q. robur increases and it becomes much higher than in conditions of more optimal water supply. At the same time, the disaccharide content increases more significantly than that of monosaccharide. The greatest amount of these sugars is observed in the driest months (July, August), when conditions for providing plants with water are the most stressful. When water stress grows the increase in concentration of glucose and sucrose is correlated with reduction of starch content. It has been found that the concentration of fructose in Q. robur leaves in droughty conditions of growing was comparable to more favourable conditions of moisture. In September, there is a decline in the content of all forms of non-structural carbohydrates in the leaves of plants of all variants compared to the previous month, especially in conditions of adverse water supply. Therefore, forest growth conditions do not affect the nature of the dynamics of soluble sugars and starch in the leaves of Q. robur, although they change their quantitative indicators. Based on the protective function of sugars under the action of stressors on plants, we can assume that in conditions of significant lack of moisture in the soil their accumulation in the leaves in areas with mesoxerophilic and xerophilic hygrotopes plays an important role in increasing Q. robur drought resistance.

Deforestation scenarios show the importance of secondary forest for meeting Panama’s carbon goals

Context Tropical forest loss has a major impact on climate change. Secondary forest growth has potential to mitigate these impacts, but uncertainty regarding future land use, remote sensing limitations, and carbon model accuracy have inhibited understanding the range of potential future carbon dynamics. Objectives We evaluated the effects of four scenarios on carbon stocks and sequestration in a mixed-use landscape based on Recent Trends (RT), Accelerated Deforestation (AD), Grow Only (GO), and Grow Everything (GE) scenarios. Methods Working in central Panama, we coupled a 1-ha resolution LiDAR derived carbon map with a locally derived secondary forest carbon accumulation model. We used Dinamica EGO 4.0.5 to spatially simulate forest loss across the landscape based on recent deforestation rates. We used local studies of belowground, woody debris, and liana carbon to estimate ecosystem scale carbon fluxes. Results Accounting for 58.6 percent of the forest in 2020, secondary forests (< 50 years) accrue 88.9 percent of carbon in the GO scenario by 2050. RT and AD scenarios lost 36,707 and 177,035 ha of forest respectively by 2030, a carbon gain of 7.7 million Mg C (RT) and loss of 2.9 million Mg C (AD). Growing forest on all available land (GE) could achieve 56 percent of Panama’s land-based carbon sequestration goal by 2050. Conclusions Our estimates of potential carbon storage demonstrate the important contribution of secondary forests to land-based carbon sequestration in central Panama. Protecting these forests will contribute significantly to meeting Panama’s climate change mitigation goals and enhance water security.

Vitality Analysis Algorithm in the Study of Plant Individuals and Populations

Background: The article presents an algorithm of the vitality analysis of plant individuals in the populations that enables the assessment of the prospects for the existence of species within certain phytocenoses and provides important information on the conditions of their growth. There are three basic stages of the algorithm: the first stage is the selection of qualitative characters, which characterize the viability of individuals; the second stage is the assessment of the vitality of specific plant individuals included in the sampling; the third stage is an integral assessment of the population vitality structure. Objective: The goal of the study is to develop the basic algorithm for vitality analysis of populations based on the assessment of the vitality of plant individuals, as well as the authors’ algorithms for vitality analysis, considering the characteristic features of species, in particular, their different life strategies (C-type and R-type). The algorithm of the vitality analysis is demonstrated on the example of populations of the annual weed Persicaria scabra Moench (Polygonaceae), which grows in the pea crop planting (Sumy Region, Ukraine). Methods: The algorithm of vitality analysis is based on the method of Yu. A. Zlobin, which includes 3 main stages. The vitality analysis of populations is carried out on the basis of the assessment of the vitality of certain individuals. The assessment of the vitality structure of populations is the third stage of vitality analysis, where the population belonging to the prosperous, equilibrium, or depressive types is determined depending on the ratio of individuals of different vitality classes (a, b, c). The calculation of the vitality analysis provides for the transformation of absolute values into unit fractions. It ensures the equivalence of the contribution of each of the features used in the assessment of the vitality of individuals and populations as a whole. Results: The article presents a basic algorithm for vitality analysis of plant populations. It also shows the algorithm for vitality analysis considering some biological and ecological characters of the studied species, which may be used in special and relatively rare cases. Some examples of analyses with a well-defined primary strategy ‒ competitors (C-type) or explerents (R-type) have been presented in the article. To calculate the morphoparameters of plant individuals and populations, the most convenient is the statistical package “Statistics”, which provides for the possibility of calculation automation via the command line. The division of populations into three types according to vitality is of general nature. The method of assessing the population vitality is inherently comparative, and this feature is considered to be its advantage. Conclusion: Vitality analysis is useful in assessing the populations of rare plant species, meadow grasses, chemical contamination on the population of plants, identifying any changes in the status populations of forest herbs in the change of forest growth conditions, as well as a number of species of forest-forming tree species. The proposed variants of the algorithm to calculate the vitality of plant species and local populations are characterized by the high biological informative value and flexibility. The incorporated information on the vitality structure of populations in quantitative PVA models to predict their dynamics will significantly increase the reliability of forecasts regarding the prospects for the existence of phytopopulations of species in various plant communities.

Integration of Forest Growth Component in the FEST-WB Distributed Hydrological Model: The Bonis Catchment Case Study

In this paper, the FEST-FOREST model is presented. A FOREST module is written in the FORTRAN-90 programming language, and was included in the FEST-WB distributed hydrological model delivering the FEST-FOREST model. FEST-FOREST is a process-based dynamic model allowing the simulation at daily basis of gross primary production (GPP) and net primary production (NPP) together with the carbon allocation of a homogeneous population of trees (same age, same species). The model was implemented based on different equations from literature, commonly used in Eco-hydrological models. This model was developed within the framework of the INNOMED project co-funded under the ERA-NET WaterWorks2015 Call of the European Commission. The aim behind the implementation of the model was to simulate in a simplified mode the forest growth under different climate change and management scenarios, together with the impact on the water balance at the catchment. On a first application of the model, the results are considered very promising when compared to field measured data.

Effects on Global Forests and Wood Product Markets of Increased Demand for Mass Timber

This study evaluated the effects on forest resources and forest product markets of three contrasting mass timber demand scenarios (Conservative, Optimistic, and Extreme), up to 2060, in twelve selected countries in Asia, Europe, North America, and South America. Analyses were carried out by utilizing the FOrest Resource Outlook Model, a partial market equilibrium model of the global forest sector. The findings suggest increases in global softwood lumber production of 8, 23, and 53 million m3 per year by 2060, under the Conservative, Optimistic, and Extreme scenarios, respectively, leading to world price increases of 2%, 7%, and 23%, respectively. This projected price increase is relative to the projected price in the reference scenario, altering prices, production, consumption, trade of forest products, timber harvest, forest growth, and forest stock in individual countries. An increase in softwood lumber prices due to increased mass timber demand would lead to the reduced consumption of softwood lumber for traditional end-use (e.g., light-frame construction), suggesting a likely strong market competition for softwood lumber between the mass timber and traditional construction industries. In contrast, the projected effect on global forest stock was relatively small based on the relatively fast projected biomass growth in stands assumed to be regenerated after harvest.

Plasticity as a Link Between Spatially Explicit, Distance-Independent, and Whole-Stand Forest Growth Models

Models at various levels of resolution are commonly used for both forest management and ecological research. They all have comparative advantages and disadvantages, making desirable a better understanding of the relationships between various approaches. Accounting for crown and root morphological plasticity in the limit where equilibrium among neighbors is reached (perfect plasticity) transforms spatial models into nonspatial, distance-independent versions. The links between spatial and nonspatial models obtained through a perfect plasticity assumption are more realistic than ignoring spatial structure by a mean field approximation. This article also reviews the connection between distance-independent models and size distributions and how distributions evolve over time and relate to whole-stand descriptions. In addition, some ways in which stand-level knowledge feeds back into detailed individual-tree formulations are demonstrated. This presentation is intended to be accessible to nonspecialists. Study Implications Introducing plasticity improves the representation of physio-ecological processes in spatial modelling. Plasticity explains in part the practical success of distance-independent models. The nature of size distributions and their relationship to individual-tree and whole-stand models are discussed. A size distribution is a one-variable distribution; joint distributions for two or more trees depend on the distances between them unless spatial structure is negligible. Limitations of current individual-tree models and questions for future research are discussed.

Simulating the Effects of Thinning Events on Forest Growth and Water Services Asks for Daily Analysis of Underlying Processes

Forest growth function and water cycle are affected by climatic conditions, making climate-sensitive models, e.g., process-based, crucial to the simulation of dynamics of forest and water interactions. A rewarded and widely applied model for forest growth analysis and management, 3PG, is a physiological process-based forest stand model that predicts growth. However, the model runs on a monthly basis and uses a simple soil-water module. Therefore, we downscale the temporal resolution to operate daily, improve the growth modifiers and add a responsive hydrological sub-model to represents the key features of a snow routine, a detailed soil-water model and a separated soil-evaporation calculation. Thereby, we aim to more precisely analyze the effects of thinning events on forest productivity and water services. The novel calibrated 3PG-Hydro model was validated in Norway spruce sites in Southern Germany and confirmed improvements in building forest processes (evapotranspiration) and predicting forest growth (biomass, diameter, volume), as well as water processes and services (water recharge). The model is more sensitive to forest management measures and variability in soil water by (1) individualization of each site’s soil, (2) simulation of percolation and runoff processes, (3) separation of transpiration and evapotranspiration to predict good evapotranspiration even if high thinning is applied, (4) calculation in daily time steps to better simulate variation and especially drought and (5) an improved soil-water modifier. The new 3PG-Hydro model can, in general, better simulate forest growth (stand volume, average diameter), as well as details of soil and water processes after thinning events. The novel developments add complexity to the model, but the additions are crucial and relevant, and the model remains an easy-to-handle forest simulation tool.