The status of forest carbon markets in Latin America

Tropical rainforests of Latin America (LATAM) are one of the world's largest carbon sinks, with substantial future carbon sequestration potential and contributing a major proportion of the global supply of forest carbon credits. LATAM is poised to contribute predominantly towards high-quality forest carbon offset projects designed to reduce emissions from deforestation and forest degradation, halt biodiversity loss, and provide equitable conservation benefits to people. Thus, carbon markets, including compliance carbon markets and voluntary carbon markets continue to expand in LATAM. However, the extent of the growth and status of forest carbon markets, pricing initiatives, stakeholders, amongst others, are yet to be explored and extensively reviewed for the entire LATAM region. Against this backdrop, we reviewed a total of 299 articles, including peer-reviewed and non-scientific gray literature sources, from January 2010 to March 2023. Herein, based on the extensive literature review, we present the results and provide perspectives classified into five categories: (i) the status and recent trends of forest carbon markets (ii) the interested parties and their role in the forest carbon markets, (iii) the measurement, reporting and verification (MRV) approaches and role of remote sensing, (iv) the challenges, and (v) the benefits, opportunities, future directions and recommendations to enhance forest carbon markets in LATAM. Despite the substantial challenges, better governance structures for forest carbon markets can increase the number, quality and integrity of projects and support the carbon sequestration capacity of the rainforests of LATAM. Due to the complex and extensive nature of forest carbon projects in LATAM, emerging technologies like remote sensing can enable scale and reduce technical barriers to MRV, if properly benchmarked. The future directions and recommendations provided are intended to improve upon the existing infrastructure and governance mechanisms, and encourage further participation from the public and private sectors in forest carbon markets in LATAM.

Spatially-explicit effects of small-scale clear-cutting on soil fungal communities in Pinus sylvestris stands

Clear-cutting is a common silvicultural practice. Although temporal changes in the soil fungal community after clear-cutting have been widely investigated, little is known about stand-level variations in the spatial distribution of soil fungi, particularly at the clear-cut edge. We performed spatial soil sampling in three clear-cuts (0.5 ha), edge habitats, and surrounding forests 8 years after clear-cutting to examine the impact of clear-cutting on the soil fungal community (diversity, composition, guilds, and biomass) and soil properties in a managed Pinus sylvestris forest in northern Spain. Our analyses showed small differences in the composition of the soil fungal community between edge, forest, and clear-cut zones, with <4 % of the species strictly associated with one or two zones. The richness, diversity, and evenness of the fungal community in the edge zone was not significantly different to that in the forest or clear-cut zones, although the clear-cut core had approximately a third fewer ectomycorrhizal species than the edge or the forest. Saprotrophic fungi were widespread across the clear-cut-forest gradient. Soil fungal biomass varied significantly between zones, ranging from 4 to 5 mg g-1 dry soil in the forest and at the forest edge to 1.7 mg g-1 dry soil in the clear-cut area. Soil organic matter, pH, nitrogen, and phosphorus did not differ significantly between edge, forest, and clear-cutting zones and were not significantly related to the fungal community composition. Overall, our study showed that small-scale clear-cut treatments are optimal to guarantee, in the medium-term, soil fungal communities within harvested areas and at the forest edge that are comparable to soil fungal communities in the forest, even though the amount of fungal biomass in the clear-cut zone is lower than at the forest edge or in the forest.

The global biogeography of tree leaf form and habit

Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17-34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling.

Influence of urban forests on residential property values: A systematic review of remote sensing-based studies

Urban forests provide direct and indirect benefits to human well-being that are increasingly captured in residential property values. Remote Sensing (RS) can be used to measure a wide range of forest and vegetation parameters that allows for a more detailed and better understanding of their specific influences on housing prices. Herein, through a systematic literature review approach, we reviewed 89 papers (from 2010 to 2022) from 21 different countries that used RS data to quantify vegetation indices, forest and tree parameters of urban forests and estimated their influence on residential property values. The main aim of this study was to understand and provide insights into how urban forests influence residential property values based on RS studies. Although more studies were conducted in developed (n = 55, 61.7%) than developing countries (n = 34, 38.3%), the results indicated for the most part that increasing tree canopy cover on property and neighborhood level, forest size, type, greenness, and proximity to urban forests increased housing prices. RS studies benefited from spatially explicit repetitive data that offer superior efficiency to quantify vegetation, forest, and tree parameters of urban forests over large areas and longer periods compared to studies that used field inventory data. Through this work, we identify and underscore that urban forest benefits outweigh management costs and have a mostly positive influence on housing prices. Thus, we encourage further discussions about prioritizing reforestation and conservation of urban forests during the urban planning of cities and suburbs, which could support UN Sustainable Development Goals (SDGs) and urban policy reforms.

Native diversity buffers against severity of non-native tree invasions

Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species1,2. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies3,4. Here, leveraging global tree databases5-7, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity. We find that anthropogenic factors are key to predicting whether a location is invaded, but that invasion severity is underpinned by native diversity, with higher diversity predicting lower invasion severity. Temperature and precipitation emerge as strong predictors of invasion strategy, with non-native species invading successfully when they are similar to the native community in cold or dry extremes. Yet, despite the influence of these ecological forces in determining invasion strategy, we find evidence that these patterns can be obscured by human activity, with lower ecological signal in areas with higher proximity to shipping ports. Our global perspective of non-native tree invasion highlights that human drivers influence non-native tree presence, and that native phylogenetic and functional diversity have a critical role in the establishment and spread of subsequent invasions.

Climate teleconnections modulate global burned area

Climate teleconnections (CT) remotely influence weather conditions in many regions on Earth, entailing changes in primary drivers of fire activity such as vegetation biomass accumulation and moisture. We reveal significant relationships between the main global CTs and burned area that vary across and within continents and biomes according to both synchronous and lagged signals, and marked regional patterns. Overall, CTs modulate 52.9% of global burned area, the Tropical North Atlantic mode being the most relevant CT. Here, we summarized the CT-fire relationships into a set of six global CT domains that are discussed by continent, considering the underlying mechanisms relating weather patterns and vegetation types with burned area across the different world's biomes. Our findings highlight the regional CT-fire relationships worldwide, aiming to further support fire management and policy-making.

Evaluation of mushroom production potential by combining spatial optimization and LiDAR-based forest mapping data

High-resolution forest mapping technology is a powerful data source to assess the production capacity of forests regarding wood and non-wood ecosystem services. The study shows how to evaluate the potential benefits from forest management treatments devoted to increase mushroom supply. The study was developed in Central Spain, over a forest with important cultural and economic values attached to mushrooms. Airborne laser scanning (ALS), mushroom production models and mathematical programming as spatial optimization method are used to sequence, spatially and temporally, silviculture-oriented actions to enlarge mushroom provisioning. We present a tactical forest planning solution to incentivize mushroom yield driven by clustered silvicultural treatments applied to fine-grained segments derived from ALS data, and along a 5-year plan while embedding temporal and spatial dependencies. Mushroom yield can increase up to 18 % from current conditions if all area is treated. Our model integrates constraints to optimize the selection of segments yielding the highest benefits in terms of mushroom yield and timber removals during the treatments. The temporal sequencing was successful, so the annual interventions are scheduled aligned in space and in time to ease the actionability and realism of model outputs. The assessment of production potential is an informative, spatially and temporally explicit exercise to inform decision-makers on investment opportunities to enhance the supply of non-wood ecosystem services, tested with mushroom in this study but extendable to more non-wood ecosystem services.

Co-limitation towards lower latitudes shapes global forest diversity gradients

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers.

Changes in global terrestrial live biomass over the 21st century

Live woody vegetation is the largest reservoir of biomass carbon, with its restoration considered one of the most effective natural climate solutions. However, terrestrial carbon fluxes remain the largest uncertainty in the global carbon cycle. Here, we develop spatially explicit estimates of carbon stock changes of live woody biomass from 2000 to 2019 using measurements from ground, air, and space. We show that live biomass has removed 4.9 to 5.5 PgC year^-1 from the atmosphere, offsetting 4.6 ± 0.1 PgC year^-1 of gross emissions from disturbances and adding substantially (0.23 to 0.88 PgC year^-1) to the global carbon stocks. Gross emissions and removals in the tropics were four times larger than temperate and boreal ecosystems combined. Although live biomass is responsible for more than 80% of gross terrestrial fluxes, soil, dead organic matter, and lateral transport may play important roles in terrestrial carbon sink.

Production and turnover of mycorrhizal soil mycelium relate to variation in drought conditions in Mediterranean Pinus pinaster, Pinus sylvestris and Quercus ilex forests

In forests, ectomycorrhizal mycelium is pivotal for driving soil carbon and nutrient cycles, but how ectomycorrhizal mycelial dynamics vary in ecosystems with drought periods is unknown. We quantified the production and turnover of mycorrhizal mycelium in Mediterranean Pinus pinaster, Pinus sylvestris and Quercus ilex forests and related the estimates to standardised precipitation index (SPI), to study how mycelial dynamics relates to tree species and drought-moisture conditions. Production and turnover of mycelium was estimated between July and February, by quantifying the fungal biomass (ergosterol) in ingrowth mesh bags and using statistical modelling. SPI for time scales of 1-3 months was calculated from precipitation records and precipitation data over the study period. Forests dominated by Pinus trees displayed higher biomass but were seasonally more variable, as opposed to Q. ilex forests where the mycelial biomass remained lower and stable over the season. Production and turnover, respectively, varied between 1.4-5.9 kg ha^-1  d^-1 and 7.2-9.9 times yr^-1 over the different forest types and were positively correlated with 2-month and 3-month SPI over the study period. Our results demonstrated that mycorrhizal mycelial biomass varied with season and tree species and we speculate that production and turnover are related to physiology and plant host performance during drought.

Coupled effects of climate teleconnections on drought, Santa Ana winds and wildfires in southern California

Projections of future climate change impacts suggest an increase of wildfire activity in Mediterranean ecosystems, such as southern California. This region is a wildfire hotspot and fire managers are under increasingly high pressures to minimize socio-economic impacts. In this context, predictions of high-risk fire seasons are essential to achieve adequate preventive planning. Regional-scale weather patterns and climatic teleconnections play a key role in modulating fire-conducive conditions across the globe, yet an analysis of the coupled effects of these systems onto the spread of large wildfires is lacking for the region. We analyzed seven decades (1953-2018) of documentary wildfire records from southern California to assess the linkages between weather patterns and large-scale climate modes using various statistical techniques, including Redundancy Analysis, Superposed Epoch Analysis and Wavelet Coherence. We found that high area burned is significantly associated with the occurrence of adverse weather patterns, such as severe droughts and Santa Ana winds. Further, we document how these fire-promoting events are mediated by climate teleconnections, particularly by the coupled effects of El Niño Southern Oscillation and Atlantic Multidecadal Oscillation.

Emerging threats linking tropical deforestation and the COVID-19 pandemic

Tropical deforestation drivers are complex and can change rapidly in periods of profound societal transformation, such as those during a pandemic. Evidence suggests that the COVID-19 pandemic has spurred illegal, opportunistic forest clearing in tropical countries, threatening forest ecosystems and their resident human communities. A total of 9583 km2 of deforestation alerts from Global Land Analysis & Discovery (GLAD) were detected across the global tropics during the first month following the implementation of confinement measures of local governments to reduce COVID-19 spread, which is nearly double that of 2019 (4732 km2). We present a conceptual framework linking tropical deforestation and the current pandemic. Zoonotic diseases, public health, economy, agriculture, and forests may all be reciprocally linked in complex positive and negative feedback loops with overarching consequences. We highlight the emerging threats to nature and society resulting from this complex reciprocal interplay and possible policy interventions that could minimize these threats.

Mushroom productivity trends in relation to tree growth and climate across different European forest biomes

Although it is logical to think that mycorrhizal mushroom production should be somehow related to the growth of the trees from which the fungi obtain carbohydrates, little is known about how mushroom yield patterns are related to tree performance. In this study, we delved into the understanding of the relationships between aboveground fungal productivity, tree radial growth patterns and climatic conditions across three latitudinally different bioclimatic regions encompassing Mediterranean, temperate and boreal forest ecosystems in Europe. For this purpose, we used a large assemblage of long-term data of weekly or biweekly mushroom yield monitoring in Spain, Switzerland and Finland. We analysed the relationships between annual mushroom yield (considering both biomass and number of sporocarps per unit area), tree ring features (tree ring, earlywood and latewood widths), and meteorological conditions (i.e. precipitation and temperature of summer and autumn) from different study sites and forest ecosystems, using both standard and partial correlations. Moreover, we fitted predictive models to estimate mushroom yield from mycorrhizal and saprotrophic fungal guilds based on climatic and dendrochronological variables. Significant synchronies between mushroom yield and climatic and dendrochronological variables were mostly found in drier Mediterranean sites, while few or no significant correlations were found in the boreal and temperate regions. We observed positive correlations between latewood growth and mycorrhizal mushroom biomass only in some Mediterranean sites, this relationship being mainly mediated by summer and autumn precipitation. Under more water-limited conditions, both the seasonal wood production and the mushroom yield are more sensitive to precipitation events, resulting in higher synchrony between both variables. This comparative study across diverse European forest biomes and types provides new insights into the relationship between mushroom productivity, tree growth and weather conditions.

Designing a network of green infrastructure to enhance the conservation value of protected areas and maintain ecosystem services

There is a growing demand for holistic landscape planning to enhance sustainable use of ecosystem services (ESS) and maintenance of the biodiversity that supports them. In this context, the EU is developing policy to regulate the maintenance of ESS and enhance connectivity among protected areas (PAs). This is known as the network of Green Infrastructure (GI). However, there is not a working framework defined to plan the spatial design of such network of GI. Here, we use the software Marxan with Zones, to prioritize the spatial distribution of different management zones that accommodate the needs of a network of GI. These zones included a conservation zone, mainly devoted to protecting biodiversity, a GI zone, that aimed at connecting PAs and maintaining regulating and cultural ESS; and a management zone devoted to exploiting provisioning ESS. We performed four planning scenarios that distribute the targets for ESS and biodiversity in different ways across management zones. We also conducted a sensitivity analysis by increasing ESS targets to explore trade-offs that may occur when managing together biodiversity and ESS. We use Catalonia (northeastern Spain) as a case study. We found that the representation of ESS could be achieved for intermediate targets in all scenarios. There was, however, a threshold on these targets over which trade-offs appeared between maintaining regulating and cultural ESS and biodiversity versus getting access to provisioning ESS. These "thresholds values" were displaced towards higher ESS targets when we moved from more strict to more flexible planning scenarios (i.e., scenarios that allowed mixing representation of objectives for biodiversity and ESS within the same zone). This methodological approach could help design a framework to integrate biodiversity and ESS management in holistic plans and decision making and, at the same time, meeting European mandates concerning the design of GI networks, or similar needs elsewhere.

The spatial level of analysis affects the patterns of forest ecosystem services supply and their relationships

The implementation of the Ecosystem Services (ES) framework (including supply and demand) should be based on accurate spatial assessments to make it useful for land planning or environmental management. Despite the inherent dependence of ES assessments on the spatial resolution at which they are conducted, the studies analyzing these effects on ES supply and their relationships are still scarce. To study the influence of the spatial level of analysis on ES patterns and on the relationships among different ES, we selected seven indicators representing ES supply and three variables that describe forest cover and biodiversity for Catalonia (NE Iberian Peninsula). These indicators were estimated at three different scales: local, municipality and county. Our results showed differences in the ES patterns among the levels of analysis. The higher levels (municipality/county) removed part of the local heterogeneity of the patterns observed at the local scale, particularly for ES indicators characterized by a finely grained, scattered distribution. The relationships between ES indicators were generally similar at the three levels. However, some negative relationships (potential trade-offs) that were detected at the local level changed to positive (and significant) relationships at municipality and county. Spatial autocorrelation showed similarities between patterns at local and municipality levels, but differences with county level. We conclude that the use of high-resolution spatial data is preferable whenever available, in particular when identifying hotspots or trade-offs/synergies is of primary interest. When the main objective is describing broad patterns of ES, intermediate levels (e.g., municipality) are also adequate, as they conserve many of the properties of assessments conducted at finer scales, allowing the integration of data sources and, usually, being more directly relevant for policy-making. In conclusion, our results warn against the uncritical use of coarse (aggregated) spatial ES data and indicators in strategies for land use planning and forest conservation.

Mushroom biomass and diversity are driven by different spatio-temporal scales along Mediterranean elevation gradients

Mushrooms are important non-wood-forest-products in many Mediterranean ecosystems, being highly vulnerable to climate change. However, the ecological scales of variation of mushroom productivity and diversity, and climate dependence has been usually overlooked due to a lack of available data. We determined the spatio-temporal variability of epigeous sporocarps and the climatic factors driving their fruiting to plan future sustainable management of wild mushrooms production. We collected fruiting bodies in Pinus sylvestris stands along an elevation gradient for 8 consecutive years. Overall, sporocarp biomass was mainly dependent on inter-annual variations, whereas richness was more spatial-scale dependent. Elevation was not significant, but there were clear elevational differences in biomass and richness patterns between ectomycorrhizal and saprotrophic guilds. The main driver of variation was late-summer-early-autumn precipitation. Thus, different scale processes (inter-annual vs. spatial-scale) drive sporocarp biomass and diversity patterns; temporal effects for biomass and ectomycorrhizal fungi vs. spatial scale for diversity and saprotrophic fungi. The significant role of precipitation across fungal guilds and spatio-temporal scales indicates that it is a limiting resource controlling sporocarp production and diversity in Mediterranean regions. The high spatial and temporal variability of mushrooms emphasize the need for long-term datasets of multiple spatial points to effectively characterize fungal fruiting patterns.

A Mixed-Effects Model with Different Strategies for Modeling Volume in Cunninghamia lanceolata Plantations

A systematic evaluation of nonlinear mixed-effect taper models for volume prediction was performed. Of 21 taper equations with fewer than 5 parameters each, the best 4-parameter fixed-effect model according to fitting statistics was then modified by comparing its values for the parameters total height (H), diameter at breast height (DBH), and aboveground height (h) to modeling data. Seven alternative prediction strategies were compared using the best new equation in the absence of calibration data, which is often unavailable in forestry practice. The results of this study suggest that because calibration may sometimes be a realistic option, though it is rarely used in practical applications, one of the best strategies for improving the accuracy of volume prediction is the strategy with 7 calculated total heights of 3, 6 and 9 trees in the largest, smallest and medium-size categories, respectively. We cannot use the average trees or dominant trees for calculating the random parameter for further predictions. The method described here will allow the user to make the best choices of taper type and the best random-effect calculated strategy for each practical application and situation at tree level.