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.

Grassland productivity response to droughts in northern China monitored by satellite-based solar-induced chlorophyll fluorescence

Solar-induced chlorophyll fluorescence (SIF) has been applied to a wide range of ecological studies, such as monitoring and assessing drought, vegetation productivity, and crop yield. Previous studies have shown that SIF is highly related to gross primary production (GPP), but its correlation with aboveground biomass (AGB) still needs further exploration. In this study, we explored the potential of SIF for monitoring and assessing the effects of climate change and meteorological drought on grassland AGB changes in the northern grassland of China. By examining the relationship between the Orbiting Carbon Observatory 2 (OCO-2) SIF and drought indices, we assessed the response of northern grassland productivity to meteorological drought conditions. The results show that SIF is very sensitive to meteorological drought and can capture drought events and the dynamics of grassland growth in different grassland types. The correlation between SIF, drought indices, and AGB varied with grassland type. A gradient boosting decision tree (GBDT) was used to explore the relationships between SIF and the impact variables in the grassland ecosystem. We found that climatic factors (e.g., annual mean growing season precipitation, annual mean growing season temperature, and annual mean vapor pressure deficit) and human activity (e.g., grazing intensity) significantly impacted the interannual variability of grassland productivity. Our results indicate that SIF changes can reflect the seasonal dynamics of vegetation growth in the northern grassland of China. Therefore, SIF can be used as benchmark data for evaluating the performance of terrestrial ecosystem models in simulating ecosystem productivity in this region. The high sensitivity of SIF to drought suggests that it is a useful tool for monitoring and assessing drought events.

Projected impacts of future climate change on the aboveground biomass of seagrasses at global scale

Seagrasses are crucial marine ecosystems that have experienced declines due to anthropogenic and climate change impacts. The projected future climate change suggests additional seagrass losses, but no global-scale estimates are currently available on the potential changes in aboveground biomass of seagrasses. We modelled and quantified the current potential aboveground biomass (AGB) of seagrasses on the global scale and projected future AGB under contrasting Shared Socioeconomic Pathway (SSP) scenarios, from low emissions (SSP1-1.9) to high emissions (SSP3-7.0 and SSP5-8.5). A machine learning algorithm (Boosted Regression Trees) fitted a comprehensive AGB dataset against biological and anthropogenic meaningful predictors. The model performed with high accuracy (deviance explained: 0.83), highlighting the role of genus and temperature conditions in defining global AGB patterns. The model estimated a present-day average AGB of 133.83 gDW·m2 (DW, dry weight) and a total global AGB of 0.0673 Pg DW. Future projections were highly dependent on the emission scenario, with losses in AGB ranging between 4.25 % and 9.25 % and in overall AGB between 9.96 % and 10.26 % across scenarios. Particularly, the higher emission scenario projected severe regional losses along the coastlines of the Tropical Eastern Pacific, the Eastern Indo-Pacific, the Temperate Northern Pacific, and the Tropical Atlantic, and gains along the Temperate Southern Africa and the Arctic regions. Our global estimates underline that fulfilling the Paris Agreement, as well as conserving and monitoring populations most affected by combined anthropogenic pressures would help to limit seagrass AGB declines, thereby supporting the multiple ecological services of seagrasses.