Forest carbon offset (FCO) projects play an increasingly important role in mitigating climate change through market mechanisms in both compliance and voluntary markets. However, there are challenges and barriers to developing an FCO project, such as carbon leakage and cost-effectiveness. There have been few attempts to summarize and synthesize all types and aspects of existing challenges and possible solutions for FCO projects. This paper systematically reviews and discusses the current challenges involved in developing FCO projects, and then draws on the experience and lessons of existing projects to show how those challenges were addressed in world-leading voluntary carbon standards, namely the Verified Carbon Standard, the American Carbon Registry, the Climate Action Reserve, and Plan Vivo. These voluntary markets have rich experience in FCO projects and are responsible for a significant share of the market. From the 53 publications used in this analysis, three broad thematic categories of challenges emerged. These were related to methodology, socio-economic implications, and implementation. Methodological challenges, particularly additionality, permanence, and leakage, were the focus of 46% of the selected research papers, while socio-economic challenges, including transaction, social, and opportunity costs, were addressed by 35%. The remaining 19% of the research articles focused on implementational challenges related to monitoring, reporting, and verification. Major voluntary standards adequately addressed most of the methodological and implementational barriers by adopting various approaches. However, the standards did not adequately address socio-economic issues, despite these being the second most frequently discussed theme in the papers analyzed. More research is clearly needed on the socio-economic challenges involved in the development of FCO projects. For the development of high-quality forestry carbon offset projects, there are many challenges and no simple, universal recipe for addressing them. However, it is crucial to build upon the current science and move forward with carbon projects which ensure effective, long-term carbon sinks and maximize benefits for biodiversity and people; this is particularly important with a growing public and private interest in this field.

Subri River Forest Reserve (SR) is the most extensive forest area in Ghana with an accompanying rich floral species. Over the years, logging from both legally prescribed and illegal operations remain the predominant forest disturbance in SR. Gap creation following logging is crucial in determining tree species composition and diversity. Hence, the study evaluated the composition and diversity of naturally regenerated tree species in logging gaps of different sizes and, again examined the roles of these tree species in fulfilling the economic and ecological agenda of sustainable forest management after logging in SR. Twelve gaps were randomly selected: 4 each were grouped into small size (≤ 200 m²), medium size (201–300 m²), and large size (≥ 300 m²). Data were gathered from 1 m² circular area at gap centres and repeatedly inside 1 m width strip along 20 m individual N-S-E-W transects. Species diversity differed significantly between gap sizes. Higher diversity indices were measured in large size gaps. Gap sizes shared similar species. There were significant differences among various height groupings of tree species across all three gap sizes. Pioneers preferred medium to large size gaps, while shade-tolerant tree species preferred small size gaps for their abundance. Vulnerable and Lower Risk Near Threatened tree species under Conservation Status and, Premium and Commercial tree species under Utilisation Status preferred small size gaps for their proliferation and conservation. Therefore, we recommend the single tree-based selective logging for ensuring creations of small to medium size (200–300 m²) gaps through adjustments to the logging permit process, revision of Allocation Quota Permit, strict adherence to the 40-year polycyclic selection system, along with more dedicated enforcement and monitoring. Changes along these protocols would tremendously facilitate natural regeneration of different suites of timber species resulting in the improvement of the overall biodiversity conservation associated with the forest, more sustainable forest harvests and more income to those who receive permits.

Knowing what native trees can recruit on degraded areas allows selecting the best species to restore these sites. However, as this information is not often available, experimentation is required before large-scale planting. This study used ex situ experiments to make these decisions on recruitment. Competition with r-strategist plants, excessive solar radiation and water shortage commonly impair tree recruitment in open habitats. The experiments focused on the interactions among these factors and were conducted with three pioneer species from seasonally dry forests of northwest Argentina, Anadenanthera colubrina, Ceiba chodatii and Jacaranda mimosifolia. Seeds of each species were sown at two light levels (sunlight/shade), two rainfall levels (full/reduced) and two levels of interspecific competition (with/without competitor) in a tree nursery. Seedling emergence and survival were monitored over a year and the results indicate that species differentially respond to varying levels of light and water. Seedlings of A. colubrina tolerated water shortages under elevated solar radiation, which are desirable features for forest restoration. Seedlings of C. chodatii tolerated shade and drought, suggesting that they require shading for establishing in open areas. However, J. mimosifolia seedlings neither tolerated full sunlight nor water shortages, suggesting that this species requires shading and regular watering if used in reforestation. Regardless of the effects of light and water, the survival of all species was reduced by interspecific competition. These results highlight the importance of experimentation for selecting the best species for forest restoration and can enhance the cost/benefit ratios of these actions.

Multi-generational planting of Eucalyptus species degrades soil quality but the introduction of legumes can improve soil fertility and microbial diversity. However, the effects of introducing non-legume native tree species on soil nutrients and bacterial community structure remain poorly understood. This study investigated the impacts of the conversion of third generation monoculture Eucalyptus plantations to mixed systems including Eucalyptus urograndis with Cinnamomum camphora (EC) and E. urograndis with Castanopsis hystrix (EH), on soil chemical and biochemical properties and bacterial community structure, diversity and functions. First generation E. urophylla plantations were the control. Results show that planting the third generation Eucalyptus led to a significant decrease in pH, organic matter, nutrient content, enzyme activities (invertin, acid phosphataes, and urease), and bacterial α-diversity compare to the controls. However, the mixed planting showed significant improvement in soil chemical and biochemical attributes and bacterial α-diversity, although the E. urograndis and C. hystrix planting had no improvement. Chloroflexi (oligotrophic bacteria) were significantly enriched in third generation Eucalyptus and Eucalyptus +  C. hystrix, while proteobacteria increased significantly in the E. urograndis with C. camphora plantings. The relative abundance of multiple metabolic pathways increased significantly in the third generation Eucalyptus plantations whereas membrane transport-related genes were enriched in soils of the mixed systems. The changes in bacterial community structures in the two mixed systems were driven by diversity, organic matter and acid phosphatase, while bacterial functions were affected by invertase,

Pine wilt disease caused by the pinewood nematode Bursaphelenchus xylophilus has led to the death of a large number of pine trees in China. This destructive disease has the characteristics of bring wide-spread, fast onset, and long incubation time. Most importantly, in China, the fatality rate in pines is as high as 100%. The key to reducing this mortality is how to quickly find the infected trees. We proposed a method of automatically identifying infected trees by a convolution neural network and bounding box tool. This method rapidly locates the infected area by classifying and recognizing remote sensing images obtained by high resolution earth observation Satellite. The recognition accuracy of the test data set was 99.4%, and the remote sensing image combined with convolution neural network algorithm can identify and determine the distribution of the infected trees. It can provide strong technical support for the prevention and control of pine wilt disease.