The growth and survival of individual trees determine the physical structure of a forest with important consequences for forest function. However, given the diversity of tree species and forest biomes, quantifying the multitude of demographic strategies within and across forests and the way that they translate into forest structure and function remains a significant challenge. Here, we quantify the demographic rates of 1,961 tree species from temperate and tropical forests and evaluate how demographic diversity (DD) and demographic composition (DC) differ across forests, and how these differences in demography relate to species richness, aboveground biomass, and carbon residence time. We find wide variation in DD and DC across forest plots, patterns that are not explained by species richness or climate variables alone. There is no evidence that DD has an effect on either aboveground biomass or carbon residence time. Rather, the DC of forests, specifically the relative abundance of large statured species, predicted both biomass and carbon residence time. Our results demonstrate the distinct demographic compositions of globally distributed forests, reflecting biogeography, recent history, and current plot conditions. Linking the demographic composition of forests to resilience or vulnerability to climate change, will improve the precision and accuracy of predictions of future forest composition, structure and function.
Tropical rainforests are subject to extensive degradation by commercial selective logging. Despite pervasive changes to forest structure, selectively logged forests represent vital refugia for global biodiversity. The ability of these forests to buffer temperature-sensitive species from climate warming will be an important determinant of their future conservation value, although this topic remains largely unexplored. Thermal buffering potential is broadly determined by: (i) the difference between the "macroclimate" (climate at a local scale, m to ha) and the "microclimate" (climate at a fine-scale, mm to m, that is distinct from the macroclimate); (ii) thermal stability of microclimates (e.g. variation in daily temperatures); and (iii) the availability of microclimates to organisms. We compared these metrics in undisturbed primary forest and intensively logged forest on Borneo, using thermal images to capture cool microclimates on the surface of the forest floor, and information from dataloggers placed inside deadwood, tree holes and leaf litter. Although major differences in forest structure remained 9-12 years after repeated selective logging, we found that logging activity had very little effect on thermal buffering, in terms of macroclimate and microclimate temperatures, and the overall availability of microclimates. For 1°C warming in the macroclimate, temperature inside deadwood, tree holes and leaf litter warmed slightly more in primary forest than in logged forest, but the effect amounted to <0.1°C difference between forest types. We therefore conclude that selectively logged forests are similar to primary forests in their potential for thermal buffering, and subsequent ability to retain temperature-sensitive species under climate change. Selectively logged forests can play a crucial role in the long-term maintenance of global biodiversity.
Tropical forests play a major role in the carbon cycle of the terrestrial biosphere. Recent field studies have provided detailed descriptions of the carbon cycle of mature tropical forests, but logged or secondary forests have received much less attention. Here, we report the first measures of total net primary productivity (NPP) and its allocation along a disturbance gradient from old-growth forests to moderately and heavily logged forests in Malaysian Borneo. We measured the main NPP components (woody, fine root and canopy NPP) in old-growth (n = 6) and logged (n = 5) 1 ha forest plots. Overall, the total NPP did not differ between old-growth and logged forest (13.5 ± 0.5 and 15.7 ± 1.5 Mg C ha-1 year-1 respectively). However, logged forests allocated significantly higher fraction into woody NPP at the expense of the canopy NPP (42% and 48% into woody and canopy NPP, respectively, in old-growth forest vs 66% and 23% in logged forest). When controlling for local stand structure, NPP in logged forest stands was 41% higher, and woody NPP was 150% higher than in old-growth stands with similar basal area, but this was offset by structure effects (higher gap frequency and absence of large trees in logged forest). This pattern was not driven by species turnover: the average woody NPP of all species groups within logged forest (pioneers, nonpioneers, species unique to logged plots and species shared with old-growth plots) was similar. Hence, below a threshold of very heavy disturbance, logged forests can exhibit higher NPP and higher allocation to wood; such shifts in carbon cycling persist for decades after the logging event. Given that the majority of tropical forest biome has experienced some degree of logging, our results demonstrate that logging can cause substantial shifts in carbon production and allocation in tropical forests.
Accurate estimates of forest biomass stocks and fluxes are needed to quantify global carbon budgets and assess the response of forests to climate change. However, most forest inventories consider tree mortality as the only aboveground biomass (AGB) loss without accounting for losses via damage to living trees: branchfall, trunk breakage, and wood decay. Here, we use ~151,000 annual records of tree survival and structural completeness to compare AGB loss via damage to living trees to total AGB loss (mortality + damage) in seven tropical forests widely distributed across environmental conditions. We find that 42% (3.62 Mg ha-1 year-1 ; 95% confidence interval [CI] 2.36-5.25) of total AGB loss (8.72 Mg ha-1 year-1 ; CI 5.57-12.86) is due to damage to living trees. Total AGB loss was highly variable among forests, but these differences were mainly caused by site variability in damage-related AGB losses rather than by mortality-related AGB losses. We show that conventional forest inventories overestimate stand-level AGB stocks by 4% (1%-17% range across forests) because assume structurally complete trees, underestimate total AGB loss by 29% (6%-57% range across forests) due to overlooked damage-related AGB losses, and overestimate AGB loss via mortality by 22% (7%-80% range across forests) because of the assumption that trees are undamaged before dying. Our results indicate that forest carbon fluxes are higher than previously thought. Damage on living trees is an underappreciated component of the forest carbon cycle that is likely to become even more important as the frequency and severity of forest disturbances increase.
Remote sensing is revolutionizing the way we study forests, and recent technological advances mean we are now able - for the first time - to identify and measure the crown dimensions of individual trees from airborne imagery. Yet to make full use of these data for quantifying forest carbon stocks and dynamics, a new generation of allometric tools which have tree height and crown size at their centre are needed. Here, we compile a global database of 108753 trees for which stem diameter, height and crown diameter have all been measured, including 2395 trees harvested to measure aboveground biomass. Using this database, we develop general allometric models for estimating both the diameter and aboveground biomass of trees from attributes which can be remotely sensed - specifically height and crown diameter. We show that tree height and crown diameter jointly quantify the aboveground biomass of individual trees and find that a single equation predicts stem diameter from these two variables across the world's forests. These new allometric models provide an intuitive way of integrating remote sensing imagery into large-scale forest monitoring programmes and will be of key importance for parameterizing the next generation of dynamic vegetation models.
Sea turtles are vulnerable to climate change since their reproductive output is influenced by incubating temperatures, with warmer temperatures causing lower hatching success and increased feminization of embryos. Their ability to cope with projected increases in ambient temperatures will depend on their capacity to adapt to shifts in climatic regimes. Here, we assessed the extent to which phenological shifts could mitigate impacts from increases in ambient temperatures (from 1.5 to 3°C in air temperatures and from 1.4 to 2.3°C in sea surface temperatures by 2100 at our sites) on four species of sea turtles, under a "middle of the road" scenario (SSP2-4.5). Sand temperatures at sea turtle nesting sites are projected to increase from 0.58 to 4.17°C by 2100 and expected shifts in nesting of 26-43 days earlier will not be sufficient to maintain current incubation temperatures at 7 (29%) of our sites, hatching success rates at 10 (42%) of our sites, with current trends in hatchling sex ratio being able to be maintained at half of the sites. We also calculated the phenological shifts that would be required (both backward for an earlier shift in nesting and forward for a later shift) to keep up with present-day incubation temperatures, hatching success rates, and sex ratios. The required shifts backward in nesting for incubation temperatures ranged from -20 to -191 days, whereas the required shifts forward ranged from +54 to +180 days. However, for half of the sites, no matter the shift the median incubation temperature will always be warmer than the 75th percentile of current ranges. Given that phenological shifts will not be able to ameliorate predicted changes in temperature, hatching success and sex ratio at most sites, turtles may need to use other adaptive responses and/or there is the need to enhance sea turtle resilience to climate warming.
Mangroves play a globally significant role in carbon capture and storage, known as blue carbon ecosystems. Yet, there are fundamental biogeochemical processes of mangrove blue carbon formation that are inadequately understood, such as the mechanisms by which mangrove afforestation regulates the microbial-driven transfer of carbon from leaf to below-ground blue carbon pool. In this study, we addressed this knowledge gap by investigating: (1) the mangrove leaf characteristics using state-of-the-art FT-ICR-MS; (2) the microbial biomass and their transformation patterns of assimilated plant-carbon; and (3) the degradation potentials of plant-derived carbon in soils of an introduced (Sonneratia apetala) and a native mangrove (Kandelia obovata). We found that biogeochemical cycling took entirely different pathways for S. apetala and K. obovata. Blue carbon accumulation and the proportion of plant-carbon for native mangroves were high, with microbes (dominated by K-strategists) allocating the assimilated-carbon to starch and sucrose metabolism. Conversely, microbes with S. apetala adopted an r-strategy and increased protein- and nucleotide-biosynthetic potentials. These divergent biogeochemical pathways were related to leaf characteristics, with S. apetala leaves characterized by lower molecular-weight, C:N ratio, and lignin content than K. obovata. Moreover, anaerobic-degradation potentials for lignin were high in old-aged soils, but the overall degradation potentials of plant carbon were age-independent, explaining that S. apetala age had no significant influences on the contribution of plant-carbon to blue carbon. We propose that for introduced mangroves, newly fallen leaves release nutrient-rich organic matter that favors growth of r-strategists, which rapidly consume carbon to fuel growth, increasing the proportion of microbial-carbon to blue carbon. In contrast, lignin-rich native mangrove leaves shape K-strategist-dominated microbial communities, which grow slowly and store assimilated-carbon in cells, ultimately promoting the contribution of plant-carbon to the remarkable accumulation of blue carbon. Our study provides new insights into the molecular mechanisms of microbial community responses during reforestation in mangrove ecosystems.
Blooms of microalgal red tides and macroalgae (e.g., green and golden tides caused by Ulva and Sargassum) have caused widespread problems around China in recent years, but there is uncertainty around what triggers these blooms and how they interact. Here, we use 30 years of monitoring data to help answer these questions, focusing on the four main species of microalgae Prorocentrum donghaiense, Karenia mikimotoi, Noctiluca scintillans, and Skeletonema costatum) associated with red tides in the region. The frequency of red tides increased from 1991 to 2003 and then decreased until 2020, with S. costatum red tides exhibiting the highest rate of decrease. Green tides started to occur around China in 1999 and the frequency of green tides has since been on the increase. Golden tides were first reported to occur around China in 2012. The frequency of macroalgal blooms has a negative linear relationship with the frequency and coverage of red tides around China, and a positive correlation with total nitrogen and phosphorus loads as well as with atmospheric CO2 and sea surface temperature (SST). Increased outbreaks of macroalgal blooms are very likely due to worsening levels of eutrophication, combined with rising CO2 and SST, which contribute to the reduced frequency of red tides. The increasing grazing rate of microzooplankton also results in the decline in areas affected by red tides. This study shows a clear shift of algal blooms from microalgae to macroalgae around China over the past 30 years driven by the combination of eutrophication, climate change, and grazing stress, indicating a fundamental change in coastal systems in the region.
There are limited data for greenhouse gas (GHG) emissions from smallholder agricultural systems in tropical peatlands, with data for non-CO2 emissions from human-influenced tropical peatlands particularly scarce. The aim of this study was to quantify soil CH4 and N2 O fluxes from smallholder agricultural systems on tropical peatlands in Southeast Asia and assess their environmental controls. The study was carried out in four regions in Malaysia and Indonesia. CH4 and N2 O fluxes and environmental parameters were measured in cropland, oil palm plantation, tree plantation and forest. Annual CH4 emissions (in kg CH4 ha-1 year-1 ) were: 70.7 ± 29.5, 2.1 ± 1.2, 2.1 ± 0.6 and 6.2 ± 1.9 at the forest, tree plantation, oil palm and cropland land-use classes, respectively. Annual N2 O emissions (in kg N2 O ha-1 year-1 ) were: 6.5 ± 2.8, 3.2 ± 1.2, 21.9 ± 11.4 and 33.6 ± 7.3 in the same order as above, respectively. Annual CH4 emissions were strongly determined by water table depth (WTD) and increased exponentially when annual WTD was above -25 cm. In contrast, annual N2 O emissions were strongly correlated with mean total dissolved nitrogen (TDN) in soil water, following a sigmoidal relationship, up to an apparent threshold of 10 mg N L-1 beyond which TDN seemingly ceased to be limiting for N2 O production. The new emissions data for CH4 and N2 O presented here should help to develop more robust country level 'emission factors' for the quantification of national GHG inventory reporting. The impact of TDN on N2 O emissions suggests that soil nutrient status strongly impacts emissions, and therefore, policies which reduce N-fertilisation inputs might contribute to emissions mitigation from agricultural peat landscapes. However, the most important policy intervention for reducing emissions is one that reduces the conversion of peat swamp forest to agriculture on peatlands in the first place.
Tree allometric models, essential for monitoring and predicting terrestrial carbon stocks, are traditionally built on global databases with forest inventory measurements of stem diameter (D) and tree height (H). However, these databases often combine H measurements obtained through various measurement methods, each with distinct error patterns, affecting the resulting H:D allometries. In recent decades, terrestrial laser scanning (TLS) has emerged as a widely accepted method for accurate, non-destructive tree structural measurements. This study used TLS data to evaluate the prediction accuracy of forest inventory-based H:D allometries and to develop more accurate pantropical allometries. We considered 19 tropical rainforest plots across four continents. Eleven plots had forest inventory and RIEGL VZ-400(i) TLS-based D and H data, allowing accuracy assessment of local forest inventory-based H:D allometries. Additionally, TLS-based data from 1951 trees from all 19 plots were used to create new pantropical H:D allometries for tropical rainforests. Our findings reveal that in most plots, forest inventory-based H:D allometries underestimated H compared with TLS-based allometries. For 30-metre-tall trees, these underestimations varied from -1.6 m (-5.3%) to -7.5 m (-25.4%). In the Malaysian plot with trees reaching up to 77 m in height, the underestimation was as much as -31.7 m (-41.3%). We propose a TLS-based pantropical H:D allometry, incorporating maximum climatological water deficit for site effects, with a mean uncertainty of 19.1% and a mean bias of -4.8%. While the mean uncertainty is roughly 2.3% greater than that of the Chave2014 model, this model demonstrates more consistent uncertainties across tree size and delivers less biased estimates of H (with a reduction of 8.23%). In summary, recognizing the errors in H measurements from forest inventory methods is vital, as they can propagate into the allometries they inform. This study underscores the potential of TLS for accurate H and D measurements in tropical rainforests, essential for refining tree allometries.