Forest Ecosystems Research Articles

Co-Management Effects on Forest Restoration in Protected Areas of Bangladesh: A Remote Sensing and GIS-Based Analysis

Co-management is a promising forest governance strategy that integrates local communities’ traditional rights and forest dependencies while aiming to improve forest cover and ecosystem health. Bangladesh, facing high deforestation rates and limited per capita forest area, has implemented co-management initiatives since 2003 to restore forest cover and support the livelihoods of forest-dependent communities. While the socio-economic impacts of co-management are well studied, its effects on forest cover remain underexplored. This study addresses that gap by using three common spectral vegetation indices (NDVI, EVI, and MSAVI), calculated from Landsat 7 data, to analyze forest cover changes in five major protected areas under co-management. The results indicated that dense forest cover (41–71%) was initially prevalent in these areas, but a significant decline occurred between 2004 and 2015, with slope values ranging from −3.7 to −0.96. In contrast, the non-co-managed control site exhibited a much smaller decline (slope: −0.48 to −0.62) across all indices. Notable increases in agricultural land and forest–agriculture mosaics were also observed in the protected areas under co-management. Global Forest Watch data further confirmed substantial forest cover loss, particularly in CWS (158.77 ha) and SNP (0.49 ha). These findings highlight the need to reassess co-management strategies to address ongoing forest degradation.

Modelling Tree Allometries to Understand the Impact of African Savannah Elephant Herbivory Dynamics on the Vegetation Structure and Tree Cover Change in a Protected Area

ABSTRACTIn landscapes with high elephant density, trees often exhibit more open canopies with fewer branches and foliage due to browsing pressure. This can result in altered tree morphology, with trees exhibiting stunted growth, multiple stems or unusual branching patterns in response to repeated damage from browsing. The objectives of this research were to (i) model the vegetation structure allometries, (ii) assess the impact of African savannah elephant (Loxodonta africana) herbivory on the vegetation structure and (iii) assess tree cover change and vegetation performance over time in Mana Pools National Park in Zimbabwe. We established 26 plots of 30 × 30 m size. Selection of sampling plots was done following several steps. First, a fish net grid with 30 × 30 m polygons was created and projected on the polygon of Mana Pools National Park. The polygons for exclusion zones were then clipped from the fish net grid using the clip tool in ArcGIS Pro 3.0. Then, selection of sampling plots was done initially by stratified random sampling using the Sampling Design Tool add in for ArcGIS Pro 3.0. Landsat images for the years 2003, 2013 and 2023 were used to assess land use land cover (LULC) time series and to calculate Normalised Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) for the period. A generalised linear model (GLM) was used to analyse tree allometries. Further statistical investigations were performed using Bayesian piecewise regression (BPR) and Bayesian regression modelling (BRM). Basal area, number of stems, height, long canopy, diameter and basal circumference were all significantly different (p < 0.05) across all sampled plots. The change in growing conditions occurring as a tree grows beyond the reach of the African savannah elephant browsing indicates a natural system breakpoint. The best‐fitting models were a simple linear model and a two breakpoint model for the plant population exposed to elephant herbivory. LULC, NDVI and SAVI confirm evidence of high tree regeneration over 2 decades. Understanding the dynamics in vegetation and LULC changes is critical for effective conservation and management of the habitats for African savannah elephants, as well as for maintaining the health and resilience of forest ecosystems.

Monitoring weekly δ 13С variations along the cambium-xylem continuum in the Canadian eastern boreal forest.

Intra-annual variations of carbon stable isotope ratios (δ13C) in different tree compartments could represent valuable indicators of plant carbon source-sink dynamics, at weekly time scale. Despite this significance, the absence of a methodological framework for tracking δ13C values in tree rings persists due to the complexity of tree ring development. To fulfill this knowledge gap, we developed a method to monitor weekly variability of δ13C in the cambium-xylem continuum of black spruce species [Picea mariana (Mill.) BSP.] during the growing season. We collected and isolated the weekly incremental growth of the cambial region and the developing tree ring from five mature spruce trees over three consecutive growing seasons (2019-2021) in Simoncouche and two growing seasons (2020-2021) in Bernatchez, both located in the boreal forest of Quebec, Canada. Our method allowed for the creation of intra-annual δ13C series for both the growing cambium (δ13Ccam) and developing xylem cellulose (δ13Cxc) in these two sites. Strong positive correlations were observed between δ13Ccam and δ13Cxc series in almost all study years. These findings suggest that a constant supply of fresh assimilates to the cambium-xylem continuum may be the dominant process feeding secondary growth in the two study sites. On the other hand, rates of carbon isotopic fractionation appeared to be poorly affected by climate variability, at an inter- weekly time scale. Hence, increasing δ13Ccam and δ13Cxc trends highlighted here possibly indicate shifts in carbon allocation strategies, likely fostering frost resistance and reducing water uptake in the late growth season. Additionally, these trends may be related to the black spruce trees' responses to the seasonal decrease in photosynthetically active radiation. Our findings provide new insights into the seasonal carbon dynamics and growth constraints of black spruce in boreal forest ecosystems, offering a novel methodological approach for studying carbon allocation at fine temporal scales.

Multi-Scenario Simulation of Land Use and Assessment of Carbon Stocks in Terrestrial Ecosystems Based on SD-PLUS-InVEST Coupled Modeling in Nanjing City

In the context of achieving the goal of carbon neutrality, exploring the changes in land demand and ecological carbon stocks under future scenarios at the urban level is important for optimizing regional ecosystem services and developing a land-use structure consistent with sustainable development strategies. We propose a framework of a coupled system dynamics (SD) model, patch generation land-use simulation (PLUS) model, and integrated valuation of ecosystem services and trade-offs (InVEST) model to dynamically simulate the spatial and temporal changes of land use and land-cover change (LUCC) and ecosystem carbon stocks under the NDS (natural development scenario), EPS (ecological protection scenario), RES (rapid expansion scenario), and HDS (high-quality development scenario) in Nanjing from 2020 to 2040. From 2005 to 2020, the expansion rate of construction land in Nanjing reached 50.76%, a large amount of ecological land shifted to construction land, and the ecological carbon stock declined dramatically. Compared with 2020, the ecosystem carbon stocks of the EPS and HDS increased by 2.4 × 106 t and 1.5 × 106 t, respectively, with a sizable ecological effect. It has been calculated that forest and cultivated land are the two largest carbon pools in Nanjing, and the conservation of both is decisive for the future carbon stock. It is necessary to focus on enhancing the carbon stock of forest ecosystems while designating differentiated carbon sink enhancement plans based on the characteristics of other land types. Fully realizing the carbon sink potential of each ecological functional area will help Nanjing achieve its carbon neutrality goal. The results of the study not only reveal the challenges of ecological conservation in Nanjing but also provide useful guidance for enhancing the carbon stock of urban terrestrial ecosystems and formulating land-use planning in line with sustainable development strategies.

Early-successional species show higher tolerance of drought than late-successional species across Europe

Climate change is exacerbating forest disturbances through more frequent and more intense droughts and fires, undermining their ability to recover from such disturbances. The response of fast-growing early-successional species to drought is poorly understood, despite their key role in ecological succession and their ability to enhance ecosystem resilience. Here, we compared the growth responses to drought events of three early-successional species (silver birch, black poplar, and Scots pine) with that of one late-successional species (European beech) across their natural distribution ranges in Europe. We used tree-ring widths of 6340 trees from 109 forest sites to establish species-specific tree-ring chronologies. We then used multiple linear regression to analyze which climatic or growth variables (pre-drought growth and growth during drought) best explained the tree responses to drought. Silver birch, Scots pine, and black poplar showed superior drought tolerance, with a slight, non-significant growth reduction under drought, whereas European beech showed a significant decrease in growth. The variables that influenced growth during and after the drought were species-specific. Annual precipitation and growth variables were key predictors of post-drought growth for Scots pine, black poplar, and European beech. Scots pine and silver birch grew better with increasing latitude, i.e., in Northern Europe than in Central Europe, while European beech and black poplar showed more growth at sites with high precipitation during the vegetation and dormant period, respectively. This study provides insights into the drought tolerance of early-successional species and highlights their ability to promote ecological succession and facilitate the transition to drought-resistant, late-successional forest ecosystems.

Plio‐Pleistocene decline of mesic forest underpins diversification in a clade of Australian Panesthia cockroaches

AbstractThe progressive aridification of the Australian continent, and coincident decline of mesic forest, has been a powerful driver of allopatric and environmental speciation in native species. The relictual mesic forests of the eastern seaboard now harbour a diverse group of endemic fauna, including the wood‐feeding cockroaches of the genus Panesthia, which reached the continent via two separate invasions from Melanesia. The more recent of these colonization events gave rise to a group of five recognized species, occurring in mainland woodlands, sclerophylls and rainforests, as well as the forests and grasslands of the Lord Howe Island Group. Due to limited sampling in molecular studies and doubt regarding the standing taxonomy, there is little certainty about relationships among the species and poor understanding of the effects of ancient climatic change upon their evolution. We undertook a comprehensive phylogenetic analysis of the clade, using complete mitogenomes and nuclear ribosomal markers from nearly all known morphospecies and populations. Our time‐calibrated phylogenetic analyses reveal an additional six unrecognized, highly divergent lineages and suggest that these have arisen primarily through vicariance as rainforests fragmented during Plio‐Pleistocene glacial cycles (2–5 million years ago). Ancestral niche estimations also evidence a tropical rainforest origin for the group, followed by at least three niche transitions into drier forest, including one associated with the singular colonization of the Lord Howe Island Group. Finally, we find evidence of frequent, parallel wing reduction, in potential association with the contraction of forest habitats into small refugia. Our results reiterate the far‐reaching role of ancient aridification in driving speciation, niche expansion and morphological evolution in Australian fauna.

Evaluation of Carbon Sequestration and Oxygen-Release Potential of Six Mulberry Tree Varieties During Summer

Human activities lead to an increase in greenhouse gases in the environment, among which carbon dioxide (CO2) is one of the most prominent, giving rise to global warming and climate change. Climate change, along with the resulting environmental degradation, is one of the most challenging difficulties faced by humanity in the twenty-first century. The forest ecosystem, with plants being its most important component, plays a pivotal role in regulating climate. Carbon sequestration and oxygen release (CSOR) by plants are major ecological service functions that play an important role in mitigating the negative impacts of the greenhouse effect and help to achieve carbon peaking and neutrality. The CSOR of mulberry (Morus spp.), a species of economic and ecological significance, is not yet understood. Six mulberry tree varieties were selected to evaluate their CSOR potential during summer. We took into consideration whole-plant diurnal assimilation amounts (P), carbon sequestration per unit leaf area (WCO2), oxygen release per unit leaf area (WO2), carbon sequestration per unit land area (PCO2), and oxygen release per unit land area (PO2). Zhongsang 1302 showed the greatest potential for CSOR among the six mulberry varieties. The PCO2 value of the Zhongsang 1302 variety was 1531.84 g·m−2 during summer, followed by Suhu 16 (1380.12 g·m−2), Husang 32 (1005.63 g·m−2), Zhongsang 9703 (990.01 g·m−2), Yu 711 (940.43 g·m−2), and Jin 10 (848.29 g·m−2). Moreover, the Pearson correlation and path analyses showed that photosynthetic rate (PN) and leaf area index (LAI) mainly affect the overall CSOR potential in mulberry. These findings not only enrich theoretical research on CSOR in mulberry, but also serve as an important reference for the use of different mulberry tree varieties in improving climate conditions and achieving carbon peaking and neutrality.

Algae-fungi symbioses and bacteria-fungi co-exclusion drive tree species-specific differences in canopy bark microbiomes.

With over 3 trillion trees, forest ecosystems comprise nearly one-third of the terrestrial surface of the Earth. Very little attention has been given to the exploration of the above-ground plant microbiome of trees, its complex trophic interactions, and variations among tree species. To address this knowledge gap, we applied a primer-independent shotgun metatranscriptomic approach to assess the entire living canopy bark microbiome comprising prokaryotic and eukaryotic primary producers, decomposers, and various groups of consumers. With almost 1500 genera, we found a high microbial diversity on three tree species with distinct bark textures: oak (Quercus robur), linden (Tilia cordata), both with rough bark, and maple (Acer pseudoplatanus) with smooth bark. Core co-occurrence network analysis revealed a rich food web dominated by algal primary producers, and bacterial and fungal decomposers, sustaining a diverse community of consumers, including protists, microscopic metazoans and predatory bacteria. Whereas maple accommodated a depauperate microbiome, oak and linden accommodated a richer microbiome mainly differing in their relative community composition: Bacteria exhibited an increased dominance on linden, whereas co-occurring algae and fungi dominated on oak, highlighting the importance of algal-fungal lichen symbioses even at the microscopic scale. Further, due to bacteria-fungi co-exclusion, bacteria on bark are not the main beneficiaries of algae-derived carbon compounds as it is known from aquatic systems.

The contributions of rainfall and fog to leaf water of tree and epiphyte communities in a tropical cloud forest.

Tropical cloud forest ecosystems are expected to face reduced water inputs due to climatic changes. Here, we study the ecophysiological responses of trees and epiphytes within in an Asian cloud forest to investigate the contributions of rainfall, fog, and soil to leaf water in 60 tree and 30 vascular epiphyte species. We measured multiple functional traits, and δ2H, and δ18O isotope ratios for leaf water, soil water, rainfall, and fog in the wettest (July) and driest (February) months. Using a Bayesian stable isotope mixing model, we quantified the relative contributions of soil water, fog, and rainfall to leaf water. Rainfall contributes almost all the leaf water of the epiphytes in July, whereas fog is the major source in February. Epiphytes cannot tap xylem water from host trees, and hence depended on fog water when rainfall was low. Most of leaf water was absorbed from soil water in July, while fog was an important source for leaf water in February despite the soil moisture content value was high. In February, lower temperatures, along with reduced photosynthesis and transpiration rates, likely contributed to decreased soil water uptake, while maintaining higher soil moisture levels despite the limited rainfall. These contrasting contributions of different water sources to leaf water under low and high rainfall and for different plant groups outline the community-level ecophysiological responses to changes in rainfall. While direct measurements of water flux, particularly in roots and stems, are needed, our results provide valuable insights on tropical cloud forest hydrology under scenarios of decreased fog immersion due to climatic changes.

Thinning-induced decrease in fine root biomass, but not other fine root traits in global forests

In forest ecosystems, changes in the expression of tree absorptive root traits following management interventions are expected to influence post-thinning forest structure and function. Fine root traits are expected to be especially responsive to forest thinning—one of the most common forest management interventions and the focus of our research here—influencing tree-level responses to environmental change, and thereby contributing to post-thinning stand-level dynamics and ecosystem processes. However, there remains limited understanding surrounding whether or not forest thinning influences the expression of root morphological, chemical, and physiological traits associated with belowground resource acquisition. We conducted a global meta-analysis to evaluate the response of 13 fine root traits to forest thinning. Our study included analysis of 769 paired observations of root traits values pre- and post-thinning, derived from 89 peer-reviewed publications. Our meta-analysis found that forest thinning leads to a decrease in fine root biomass by 11.7% on average, while other root traits including fine root length, root C and N concentrations, root lifespan, and root respiration rates, are largely unresponsive to thinning treatments. Thinning tended to reduce fine root biomass at early stand recovery stages, with increases in fine root biomass being detected at later seral stages, especially in heavy thinning experiments. The effect of thinning on fine root biomass was most pronounced in deeper soil horizons. The influence of thinning on fine root trait expression was not affected by ecosystem or stand type, with the exception of biomass which decreased in temperate and coniferous forests. Our results demonstrate variations of fine root traits to forest management, as well as the importance of stand recovery time and thinning intensity in regulating fine root trait expression in retention trees. These patterns may have strong implications for governing soil carbon stocks in managed forests associated with decreased root inputs into deeper soils. Overall, our findings can enhance our comprehension of how forest management affects fine root trait expression, and relationship between managed forests and belowground ecosystem structure and function.

Assessing the ecological complexity and uncertainty of predicting forest ecosystem services under climate change

Climate change affects Central European forest ecosystems in different ways and, consequently, these changes result in different feedbacks on the provision of forest ecosystem services. Regarding the complexity and the variability in climate-forest interactions outcome, forest decision makers necessitate reliable information about changes in the forest ecosystem services for planning and adaptation purposes. However, forest productivity predictions incorporate multiple levels of uncertainty that have to be regarded to ensure building realistic expectations in forest decision-making. Besides the chosen forest simulation model, uncertainties come from the climate change data represented by a set of representative concentration pathways (RCP), within the underlying ensemble of global circulation and regional climate models (GCM-RCM), and further in the treatment of the CO2-fertilization effect. We considered the mentioned uncertainties in a framework on simulating forest growth and water services for two forest sites, a Sessile oak and a Scots pine stand in Rhineland-Palatine, Germany. The framework revealed a high variability in future forest ecosystem services. Particularly, the variability among the selected GCM-RCM models within the same Representative Concentration Pathway (RCP) was higher than the variability among different RCPs (RCP2.6 and RCP8.5 representing the low and high CO2-emission scenarios, respectively). Sessile oak productivity increased under all scenarios, whereas Scots pine growth declined in the lower end of the RCP8.5 scenario. Water services remained mostly stable at both sites. Moreover, we applied a panel data model to estimate what climate indices caused changes in the forest ecosystem services. We found that Scots pine is more sensitive to a multitude of climate indices, such as temperature changes and Sessile oak showed strong response to the CO2-fertilization. We propose applying this framework to evaluate forest management options under climate change.

Niche divergence mechanisms of closely related hybridising bird species. Modeling approach based on remote sensing data of forest habitats

Describing mechanisms that ensure stable co-occurrence of sympatric species is fundamental to understanding the complexity of ecological community dynamics. In this study, the Pied flycatcher and the Collared flycatcher were used as model species for the analysis of co-occurrence patterns of closely related hybridising species that inhabit overlapping forest habitats. I hypothesise that spatial niche partitioning between species emerges as a vital adaptive response to interspecific competition and manifests itself in significant shifts in habitat preferences in syntopic areas but not in the allotopic ones. The study leverages a comprehensive dataset that includes species density in 372 randomly selected 1 km² grid cells across the territory of Poland. The analysis of habitat preferences was performed with linear mixed-effect modeling, whereas a contrast analysis was used to investigate changes in habitat preferences resulting from the presence of a competitor. The findings indicate that both species modify their habitat preferences when transitioning between syntopic and allotopic sites. Remarkably, in regions without competitors, such shifts are significantly less pronounced, as demonstrated by the Pied flycatcher that prefers the same habitats both in allopatric regions and allotopic sites. When these results are compared with other studies on closely related hybridising and non-hybridising species, it turns out that what influences the degree and number of niches subjected to competition is the time that passes from species divergence. This study highlights the imperative need to incorporate co-occurrence parameters of closely related species into niche and species distribution models to enhance their ecological realism.

Wildlife density estimation by distance sampling: A novel technique with movement compensation.

Estimates of population density are fundamental to wildlife conservation and management. Distance sampling from line transects is a widely used sample count method and is most often analysed using Distance software. However, this method has limited capabilities with mobile populations (e.g., birds), which tend to encounter an observer more often than immobile ones. This paper presents a novel distance sampling method based on a different set of models and assumptions, named WildlifeDensity after its associated software. It is based on mechanistic modelling of visual detections of individuals or groups according to radial distance from the observer or perpendicular distance from the transect line. It also compensates for population-observer relative movement to avoid the detection overestimates associated with highly mobile populations. The models are introduced in detail and then tested in three ways: 1) WildlifeDensity is applied to several 'benchmark' populations of known density and no-to-low mobility, 2) the movement compensation model is tested on two highly mobile songbird populations, and 3) a fairly difficult case is analysed: a low-density, highly mobile bird population in a forest habitat. The results show that 1) using either radial or perpendicular distance data from surveys of immobile populations, WildlifeDensity provides similar estimates (and errors) to Distance, with radial WildlifeDensity analysis appearing to be slightly better for surveys of low-mobility populations (kangaroos), 2) the movement compensation model effectively removes the correlation between observer speed and detection numbers, and 3) WildlifeDensity provides acceptable estimates where conventional Distance analysis overestimates density due to high movement. In summary, WildlifeDensity extends the capabilities of distance sampling by 1) compensating for movement, 2) not requiring complete detectability on the transect line and 3) supporting the use of radial distances, which simplifies fieldwork and increases measurement accuracy.

ECONOMIC VALUATION OF ECOSYSTEM SERVICES FOR THE MAINTENANCE OF TOURISM ACTIVITY IN THE CENTRAL AMAZON, BRAZIL

The valuation of ecosystem services provides essential information that makes it possible to estimate the economic value of environmental resources and their benefits. The aim was to estimate the value of the forest's cultural ecosystem services provided to maintain tourist activity in Presidente Figueiredo, Amazonas. The contingent valuation method (CVM) was used to estimate the willingness to pay (WTP) of users (tourists and visitors) and the willingness to accept (WTA) of landowners, local business owners and other interviewees. The results of the interviews indicate that 71% of users would be willing to pay an average of R$16.57 day-1visit-1, while 100% of interviewees would be willing to conserve the forests in exchange for receiving R$327.63 ha-1year-1. In conclusion, most of the interviewees agreed that valuing the forest's ecosystem services is fundamental to maintaining tourist activity.

Mapping Forest Carbon Stock Distribution in a Subtropical Region with the Integration of Airborne Lidar and Sentinel-2 Data

Forest carbon stock is an important indicator reflecting a forest ecosystem’s structures and functions. Its spatial distribution is valuable for managing natural resources, protecting ecosystems and biodiversity, and further promoting sustainability, but accurately mapping the forest carbon stock distribution in a large area is a challenging task. This study selected Changting County, Fujian Province, as a case study to explore a method to map the forest carbon stock distribution using the integration of airborne Lidar, Sentinel-2, and ancillary data in 2022. The Bayesian hierarchical modeling approach was used to estimate the local forest carbon stock based on airborne Lidar data and field measurements, and then the random forest approach was used to develop a regional forest carbon stock estimation model based on the Sentinel-2 and ancillary data. The results indicated that the Lidar-based carbon stock distribution effectively provided sample plots with good spatial representativeness for modeling regional carbon stock with a coefficient of determination (R2) of 0.7 and root mean square error (RMSE) of 12.94 t/ha. The average carbon stocks were 48.55 t/ha, 55.51 t/ha, and 57.04 t/ha for Masson pine, Chinese fir, and broadleaf forests, respectively. The carbon stock in non-conservation regions was 15.2–16.1 t/ha higher than that in conservation regions. This study provides a promising method through the use of airborne Lidar data as a linkage between sample plots and Sentinel-2 data to map the regional carbon stock distribution in those subtropical regions where serious soil erosion has led to a relatively sparse forest canopy density. The results are valuable for local government to make scientific decisions for promoting ecosystem restoration due to water and soil erosion.

Investigating the Spatial Pattern of White Oak (Quercus alba L.) Mortality Using Ripley’s K Function across the Ten States of the Eastern US

White oak mortality is a significant concern in forest ecosystems due to its impact on biodiversity and ecosystem functions. Understanding the factors influencing white oak mortality is crucial for effective forest management and conservation efforts. In this study, we aimed to investigate the spatial pattern of WOM rates across the eastern US and explore the underlying processes behind the observed spatial patterns. Multicycle forest inventory and analysis data were compiled to capture all white oak plots. WOM data were selected across plot systems that utilized declining basal areas between two periods. Ripley’s K function was used to study the spatial pattern of WOM rates. Results showed clustered patterns of WOM rates at local and broad scales that may indicate stand-level competition and regional variables affecting white oaks’ dynamics across southern and northern regions. Results also indicated random patterns at broad scales, suggesting variations in topographic and hydrological conditions across the south and northern regions. However, the central region indicated both clustered and random patterns at the local scale that might be associated with inter-species competition and the possibility of environmental heterogeneity, respectively. Furthermore, uniform patterns of WOM rate at a broad scale across all regions might suggest regions with spatially homogeneous environmental factors acting on the dynamics of white oaks. This research might be helpful in identifying impacted areas of white oaks at varying scales. Future research is needed to comprehensively assess biotic and abiotic factors at various spatial scales aimed at mitigating WOM.

A New Species of Heligmonellidae (Nematoda) in Euryoryzomys russatus (Rodentia: Sigmodontinae) in the Atlantic Forest of Northeast Brazil.

The genus Stilestrongylus (Freitas, Lent, and Almeida, 1937) is defined by having 24 or more subequal cuticular ridges, an asymmetrical caudal bursa, and a hypertrophied genital cone. It comprises 25 recognized species, mainly parasitizing cricetids, and shows significant diversification linked to the evolution of its hosts. Stilestrongylus magnumspiculum n. sp. is a newly described nematode species identified in the small intestine of the rodent Euryoryzomys russatus (Cricetidae, Sigmodontinae) from the Atlantic Forest of Northeast Brazil. This study aims to characterize the new species and its prevalence in host populations. A total of 43 Euryoryzomys russatus individuals were collected and analyzed for parasitic infections. Morphological features of Stilestrongylus magnumspiculum n. sp. were examined, focusing on the number of ridges, synlophe characteristics, caudal bursa type, lobe hypertrophy, and the spicule length to body length ratio. The new species exhibited a prevalence of 21% among the sampled hosts. Distinctive morphological features were observed, including:the synlophe structure exhibited specific ridge patterns that differentiate it from other species within the genus; the caudal bursa was identified as a type 2-2-1; hypertrophy of the right lobe was observed, indicating notable morphological adaptation; rays 4 and 5 were found to be equivalent in size and diverged at the distal end; the spicule length to body length ratio (SpL/BL) was measured at 30-36%, representing the largest ratio recorded for the genus. In comparison, other Stilestrongylus species displayed the following ratios: S. rolandoi (21-33%), S. lanfrediae (25-29%), S. kaaguyporai (20-24%), S. inexpectatus (20-23%), and S. stilesi (26-28%). This report presents Stilestrongylus magnumspiculum n. sp. as a new species of nematode, contributing to the diversity of the genus Stilestrongylus. The findings underscore the importance of studying host-parasite interactions within the Atlantic Forest ecosystem and provide a basis for future ecological and parasitological research.

Above ground biomass estimation in the upper Blue Nile basin forests, North-Western Ethiopia

Forest ecosystems play a decisive role in the global climatic condition, as well as, provides a wide range of societal benefits, including fuel-wood, tourism, and ecosystem services are considered as one of the major sources of livelihood for the local people in the upper Blue Nile Basin. Therefore, rapid and accurate estimation of forest biomass is crucial for greatly reducing the uncertainty in carbon stock assessments, and for designing strategic forest management plans. Because, above-ground biomass (AGB) estimation is important in determining the management, environmental, and economic roles of forests in the Blue Nile basin. The study was aimed at estimating above-ground biomass in the Upper Blue Nile Basin forests by integrating field-measured data with predictors from Sentinel-2 image. The relationship between measured AGB and sentinel-2 derived vegetation indices and biophysical parameters showed a good correlation result (r value ranging from 0.67 to 0.74). A stepwise regression analysis was carried out in order to develop AGB estimation model by identifying the most important variable. The result demonstrated that, green normalized difference vegetation index, leaf area index, fraction of absorbed photosynthetic active radiation and fractional vegetation cover achieved good performance in predicting AGB with R2 value > 0.5. AGB was estimated with a coefficient of determination (R2) of 0.59 adjusted R2 of 0.618 and root mean square error of (RMSE) 38.36 t/ha in comparison to field observations. The maximum AGB value of 268.32 t/ha was estimated in the Alemsaga natural forest, which is a highly protected dense forest stand from any entrance and disturbance. Generally, integrating field data with optical remote sensing data provides more reliable result for AGB estimation. Moreover, it is also recommended to employ RADAR and LiDAR remote sensing data products together in order to attain more precise estimate results of AGB with great potential for forest resource monitoring and management.

Quantifying global warming potential variations from greenhouse gas emission sources in forest ecosystems

Forest ecosystems play a crucial role in regulating greenhouse gas (GHG) emissions and mitigating climate change. This research aimed to evaluate the GHG emissions of various sources within forested ecosystems and assess their respective contributions to global warming potential (GWP), vital for developing more targeted strategies to mitigate climate change, shaping climate policies, carbon accounting, sustainable forest management, and advancing scientific comprehension of ecosystem-climate dynamics. The study comprehensively analysed carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) emissions EDGAR data of deforestation, fires, and natural processes such as organic soil decomposition within forested ecosystems. The assessment quantified the CO2 equivalent emissions for each category from 1990 to 2022 and forecasted till 2030. Our forecast shows that CO2 emissions from deforestation could reach between 3,990 and 4,529 metric ton (Mt) by 2030, with forest fires contributing an additional 750 Mt. Forestland CO2 absorption is expected to decline to -5134.80 Mt by 2030. There is uncertainty surrounding the forecasts for Organic soil CO2 (829.78 Mt) and Other land CO2 (-764.53 Mt). In addition, deforestation was a significant contributor to CO2 emissions, with a GWP ranging from 4000 to 4500, highlighting the complex interplay between natural processes and human activities in shaping atmospheric warming patterns. Additionally, forest fires emit a complex mix of GHGs. The potency of these gases in warming the planet varies considerably, with CH4 exhibiting a GWP range of 500 to 700 Mt CO2 equivalent, and CO2 ranging from 900 and 1350 Mt. These variations depend on fire intensity and its overall impact on the climate system. Forestland acts as powerful carbon sink, capturing atmospheric CO2 with negative GWP values between -7000 and -6000. Researchers suggest a multifaceted strategy such as stricter enforcement of sustainable forestry regulations, investing in projects that promote carbon sequestration, and reforestation. Additionally, advancements in drone technology, satellite imagery, remote sensing and advanced data analytics can aid in detecting and mitigating climate change impacts, ultimately paving the way for carbon neutrality.Graphical

The global distribution and drivers of wood density and their impact on forest carbon stocks.

The density of wood is a key indicator of the carbon investment strategies of trees, impacting productivity and carbon storage. Despite its importance, the global variation in wood density and its environmental controls remain poorly understood, preventing accurate predictions of global forest carbon stocks. Here we analyse information from 1.1 million forest inventory plots alongside wood density data from 10,703 tree species to create a spatially explicit understanding of the global wood density distribution and its drivers. Our findings reveal a pronounced latitudinal gradient, with wood in tropical forests being up to 30% denser than that in boreal forests. In both angiosperms and gymnosperms, hydrothermal conditions represented by annual mean temperature and soil moisture emerged as the primary factors influencing the variation in wood density globally. This indicates similar environmental filters and evolutionary adaptations among distinct plant groups, underscoring the essential role of abiotic factors in determining wood density in forest ecosystems. Additionally, our study highlights the prominent role of disturbance, such as human modification and fire risk, in influencing wood density at more local scales. Factoring in the spatial variation of wood density notably changes the estimates of forest carbon stocks, leading to differences of up to 21% within biomes. Therefore, our research contributes to a deeper understanding of terrestrial biomass distribution and how environmental changes and disturbances impact forest ecosystems.