Integrated global assessment of the natural forest carbon potential.

Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system1. Remote-sensing estimates to quantify carbon losses from global forests2-5 are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced6 and satellite-derived approaches2,7,8 to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151-363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea2,3,9 that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets.

The number of tree species on Earth.

One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global ground-sourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are ∼73,000 tree species globally, among which ∼9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These findings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness.

Uncertainty in REDD+ carbon accounting: a survey of experts involved in REDD+ reporting.

BACKGROUND: Reducing Emissions from Deforestation and forest Degradation (REDD+) is a program established under the United Nations Framework Convention on Climate Change (UNFCCC) to reduce carbon emissions from forests in developing countries. REDD+ uses an incentive-based approach whereby participating countries are paid to reduce forest carbon loss and increase carbon storage. Country-level carbon accounting is challenging, and estimates of uncertainty in emission reductions are increasingly required in REDD+ reports. This requirement is hard to meet if countries lack the necessary resources, tools, and capabilities. Some REDD+ programs adjust their payments for the uncertainty reported, which presents a perverse incentive because uncertainties are larger if more sources of uncertainty are reported. We surveyed people involved in REDD+ reporting to assess current capacities and barriers to improving estimates of uncertainty. RESULTS: Representatives from 27 countries (44% of REDD+ countries at the time of survey implementation) responded to the survey. Nearly all respondents thought it important to include uncertainty in REDD+ reports, but most felt that the uncertainty reporting by their countries was inadequate. Our independent assessment of reports by these countries to the UNFCCC supported this opinion: Most countries reported uncertainty in activity data (91%) but not in emission factors (4-14%). Few countries use more advanced approaches to estimate uncertainty, such as Monte Carlo and Bayesian techniques, and many respondents indicated that they lack expertise, knowledge, or technical assistance. Other barriers include lack of financial resources and appropriate data. Despite these limitations, nearly all respondents indicated a strong desire to improve estimates of uncertainty in REDD+ reports. CONCLUSIONS: The survey indicated that people involved in REDD+ reporting think it highly important to improve estimates of uncertainty in forest carbon accounting. To meet this challenge, it is essential to understand the obstacles countries face in quantifying uncertainty so we can identify where best to allocate efforts and funds. Investments in training and resources are clearly needed to better quantify uncertainty and would likely have successful outcomes given the strong desire for improvement. Tracking the efficacy of programs implemented to improve estimates of uncertainty would be useful for making further refinements.

Spatial database of planted forests in East Asia.

Planted forests are critical to climate change mitigation and constitute a major supplier of timber/non-timber products and other ecosystem services. Globally, approximately 36% of planted forest area is located in East Asia. However, reliable records of the geographic distribution and tree species composition of these planted forests remain very limited. Here, based on extensive in situ and remote sensing data, as well as an ensemble modeling approach, we present the first spatial database of planted forests for East Asia, which consists of maps of the geographic distribution of planted forests and associated dominant tree genera. Of the predicted planted forest areas in East Asia (948,863 km2), China contributed 87%, most of which is located in the lowland tropical/subtropical regions, and Sichuan Basin. With 95% accuracy and an F1 score of 0.77, our spatially-continuous maps of planted forests enable accurate quantification of the role of planted forests in climate change mitigation. Our findings inform effective decision-making in forest conservation, management, and global restoration projects.

Exploring characteristics of national forest inventories for integration with global space-based forest biomass data.

National forest inventories (NFIs) are a reliable source for national forest measurements. However, they are usually not developed for linking with remotely sensed (RS) biomass information. There are increasing needs and opportunities to facilitate this link towards better global and national biomass estimation. Thus, it is important to study and understand NFI characteristics relating to their integration with space-based products; in particular for the tropics where NFIs are quite recent, less frequent, and partially incomplete in several countries. Here, we (1) assessed NFIs in terms of their availability, temporal distribution, and extent in 236 countries from FAO's Global Forest Resources Assessment (FRA) 2020; (2) compared national forest biomass estimates in 2018 from FRA and global space-based Climate Change Initiative (CCI) product in 182 countries considering NFI availability and temporality; and (3) analyzed the latest NFI design characteristics in 46 tropical countries relating to their integration with space-based biomass datasets. We observed significant NFI availability globally and multiple NFIs were mostly found in temperate and boreal countries while most of the single NFI countries (94 %) were in the tropics. The latest NFIs were more recent in the tropics and many countries (35) implemented NFIs from 2016 onwards. The increasing availability and update of NFIs create new opportunities for integration with space-based data at the national level. This is supported by the agreement we found between country biomass estimates for 2018 from FRA and CCI product, with a significantly higher correlation in countries with recent NFIs. We observed that NFI designs varied greatly in tropical countries. For example, the size of the plots ranged from 0.01 to 1 ha and more than three-quarters of the countries had smaller plots of ≤0.25 ha. The existing NFI designs could pose specific challenges for statistical integration with RS data in the tropics. Future NFI and space-based efforts should aim towards a more integrated approach taking advantage of both data streams to improve national estimates and help future data harmonization efforts. Regular NFI efforts can be expanded with the inclusion of some super-site plots to enhance data integration with currently available space-based applications. Issues related to cost implications versus improvements in the accuracy, timeliness, and sustainability of national forest biomass estimation should be further explored.

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.

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.

Metapopulations in multifractal landscapes: on the role of spatial aggregation.

The use of fractals in ecology is currently pervasive over many areas. However, very few studies have linked fractal properties of landscapes to generating ecological mechanisms and dynamics. In this study I show that lacunarity (a measure of the landscape texture) is a well suited ecologically scaled landscape index that can be explicitly incorporated in metapopulation models such as the classical Levins equation. I show that the average lacunarity of an aggregated landscape is linearly correlated to the habitat that a species with local spatial processed information may perceive. Lacunarity is a computationally feasible index to measure, and is related to the metapopulation capacity of landscapes. A general approach to multifractal landscapes has been conceived, and some analytical results for self-similar landscapes are outlined, including the specific effect of landscape heterogeneity, decoupled from that of contagion by dispersal. Spatially explicit simulations show agreement with the semi-implicit method presented.

Modelling remediation scenarios in historical mining catchments.

Local remediation measures, particularly those undertaken in historical mining areas, can often be ineffective or even deleterious because erosion and sedimentation processes operate at spatial scales beyond those typically used in point-source remediation. Based on realistic simulations of a hybrid landscape evolution model combined with stochastic rainfall generation, we demonstrate that similar remediation strategies may result in differing effects across three contrasting European catchments depending on their topographic and hydrologic regimes. Based on these results, we propose a conceptual model of catchment-scale remediation effectiveness based on three basic catchment characteristics: the degree of contaminant source coupling, the ratio of contaminated to non-contaminated sediment delivery, and the frequency of sediment transport events.

Habitat hydrology and geomorphology control the distribution of malaria vector larvae in rural Africa.

BACKGROUND: Larval source management is a promising component of integrated malaria control and elimination. This requires development of a framework to target productive locations through process-based understanding of habitat hydrology and geomorphology. METHODS: We conducted the first catchment scale study of fine resolution spatial and temporal variation in Anopheles habitat and productivity in relation to rainfall, hydrology and geomorphology for a high malaria transmission area of Tanzania. RESULTS: Monthly aggregates of rainfall, river stage and water table were not significantly related to the abundance of vector larvae. However, these metrics showed strong explanatory power to predict mosquito larval abundances after stratification by water body type, with a clear seasonal trend for each, defined on the basis of its geomorphological setting and origin. CONCLUSION: Hydrological and geomorphological processes governing the availability and productivity of Anopheles breeding habitat need to be understood at the local scale for which larval source management is implemented in order to effectively target larval source interventions. Mapping and monitoring these processes is a well-established practice providing a tractable way forward for developing important malaria management tools.

Complex discrete dynamics from simple continuous population models.

Nonoverlapping generations have been classically modelled as difference equations in order to account for the discrete nature of reproductive events. However, other events such as resource consumption or mortality are continuous and take place in the within-generation time. We have realistically assumed a hybrid ODE bidimensional model of resources and consumers with discrete events for reproduction. Numerical and analytical approaches showed that the resulting dynamics resembles a Ricker map, including the doubling route to chaos. Stochastic simulations with a handling-time parameter for indirect competition of juveniles may affect the qualitative behaviour of the model.

Biomass-diversity responses and spatial dependencies in disturbed tallgrass prairies.

Monotonic, hump-shaped and zero-correlation productivity-diversity relationships have been found to date in many ecosystems. This diversity of responses has puzzled ecologists in their search for general principles on ecosystem functioning. Some state that the scale of observation is crucial in defining this relationship. We have developed a spatial model of tallgrass prairies where biomass and litter dynamics are defined by uncoupled difference equations. In this system, we periodically apply prescribed fire as a disturbance that propagates through neighboring cells. The model shows percolation thresholds at points where small-scale spatial heterogeneity and large-scale, global correlation coexist, resulting in power-law distributions in available areas for non-dominant species. These points maximize the biomass-diversity relationship. Our results suggest that spatial dependencies and the disturbance heterogeneity hypothesis are the cornerstone processes accounting for unimodality in productivity-diversity relationships.