Old and ancient trees are life history lottery winners and vital evolutionary resources for long-term adaptive capacity

Trees can live for many centuries with sustained fecundity and death is largely stochastic. We use a neutral stochastic model to examine tree demographic patterns that emerge over time, across a range of population sizes and empirically observed mortality rates. A small proportion of trees (~1% at 1.5% mortality) are life-history 'lottery winners', achieving ages >10-20× the median age. Maximum age increases with bigger populations and lower mortality rates. One-quarter of trees (~24%) achieve ages that are three to four times greater than the median age. Three age classes (mature, old and ancient) contribute unique evolutionary diversity across complex environmental cycles. Ancient trees are an emergent property of forests that requires many centuries to generate. They radically change variance in generation time and population fitness, bridging centennial environmental cycles. These life-history 'lottery' winners are vital to long-term forest adaptive capacity and provide invaluable data about environmental history and individual longevity. Old and ancient trees cannot be replaced through restoration or regeneration for many centuries. They must be protected to preserve their invaluable diversity.

On the Management of Large-Diameter Trees in China’s Forests

Large-diameter trees have mainly been used for timber production in forestry practices. Recently, their critical roles played in biodiversity conservation and maintenance of ecosystem functions have been recognized. However, current forestry policy on the management of large-diameter trees is weak. As China is the biggest consumer of large-diameter timbers, how to maintain sustainable large-diameter timber resources as well as maximize ecological functions of the forests is a critical question to address. Here we summarize historical uses, distribution patterns, and management strategies of large-diameter trees in China. We found that large-diameter trees are mainly distributed in old-growth forests. Although China’s forest cover has increased rapidly in the past decades, large-diameter trees are rarely found in plantation forests and secondary forests. We suggest that knowledge of large-diameter trees should be widely disseminated in local forestry departments, especially their irreplaceable value in terms of biodiversity conservation and ecosystem functions. Protection of large-diameter trees, especially those in old-growth forests, is critical for sustainable forestry. To meet the increasing demand of large-diameter timbers, plantation forests and secondary forests should apply forest density management with thinning to cultivate more large-diameter trees.

Diversity, distribution and dynamics of large trees across an old-growth lowland tropical rain forest landscape

Large trees, here defined as ≥60 cm trunk diameter, are the most massive organisms in tropical rain forest, and are important in forest structure, dynamics and carbon cycling. The status of large trees in tropical forest is unclear, with both increasing and decreasing trends reported. We sampled across an old-growth tropical rain forest landscape at the La Selva Biological Station in Costa Rica to study the distribution and performance of large trees and their contribution to forest structure and dynamics. We censused all large trees in 238 0.50 ha plots, and also identified and measured all stems ≥10 cm diameter in 18 0.50 ha plots annually for 20 years (1997–2017). We assessed abundance, species diversity, and crown conditions of large trees in relation to soil type and topography, measured the contribution of large trees to stand structure, productivity, and dynamics, and analyzed the decadal population trends of large trees. Large trees accounted for 2.5% of stems and ~25% of mean basal area and Estimated Above-Ground Biomass, and produced ~10% of the estimated wood production. Crown exposure increased with stem diameter but predictability was low. Large tree density was about twice as high on more-fertile flat sites compared to less fertile sites on slopes and plateaus. Density of large trees increased 27% over the study interval, but the increase was restricted to the flat more-fertile sites. Mortality and recruitment differed between large trees and smaller stems, and strongly suggested that large tree density was affected by past climatic disturbances such as large El Niño events. Our results generally do not support the hypothesis of increasing biomass and turnover rates in tropical forest. We suggest that additional landscape-scale studies of large trees are needed to determine the generality of disturbance legacies in tropical forest study sites.

Calculation of narrower confidence intervals for tree mortality rates when we know nothing but the location of the death/survival events

Many ecological applications, like the study of mortality rates, require the estimation of proportions and confidence intervals for them. The traditional way of doing this applies the binomial distribution, which describes the outcome of a series of Bernoulli trials. This distribution assumes that observations are independent and the probability of success is the same for all the individual observations. Both assumptions are obviously false in many cases.I show how to apply bootstrap and the Poisson binomial distribution (a generalization of the binomial distribution) to the estimation of proportions. Any information at the individual level would result in better (narrower) confidence intervals around the estimation of proportions. As a case study, I applied this method to the calculation of mortality rates in a forest plot of tropical trees in Lambir Hills National Park, Malaysia.I calculated central estimates and 95% confidence intervals for species-level mortality rates for 1,007 tree species. I used a very simple model of spatial dependence in survival to estimate individual-level risk of mortality. The results obtained by accounting for heterogeneity in individual-level risk of mortality were comparable to those obtained with the binomial distribution in terms of central estimates, but the precision increased in virtually all cases, with an average reduction in the width of the confidence interval of ~20%.Spatial information allows the estimation of individual-level probabilities of survival, and this increases the precision in the estimates of mortality rates. The general method described here, with modifications, could be applied to reduce uncertainty in the estimation of proportions related to any spatially structured phenomenon with two possible outcomes. More sophisticated approaches can yield better estimates of individual-level mortality and thus narrower confidence intervals.

The importance of large-diameter trees in the wet tropical rainforests of Australia

Large trees are keystone structures in many terrestrial ecosystems. They contribute disproportionately to reproduction, recruitment and succession, and influence the structure, dynamics and diversity of forests. Recently, researchers have become concerned about evidence showing rapid declines in large, old trees in a range of ecosystems across the globe. We used ≥10 cm diameter at breast height (DBH) stem inventory data from 20, 0.5 ha forest plots spanning the wet tropical rainforest of Queensland, Australia to examine the contribution of large-diameter trees to above ground biomass (AGB), richness, dominance, mortality and recruitment. We show consistencies with tropical rainforest globally in that large-diameter trees (≥70 cm DBH) contribute much of the biomass (33%) from few trees (2.4% of stems ≥10 cm DBH) with the density of the largest trees explaining much of the variation (62%) in AGB across plots. Measurement of AGB in the largest 5% of trees allows plot biomass to be predicted with ~85% precision. In contrast to rainforest in Africa and America, we show that a high proportion of tree species are capable of reaching a large-diameter in Australian wet tropical rainforest resulting in weak biomass hyperdominance (~10% of species account for 50% of the biomass) leading to high potential resilience to regional disturbances and global environmental change. We show that the high AGB in Australian tropical forests is driven primarily by the high density of large trees coupled with contributions from high densities of medium size trees. Australian wet tropical rainforests are well positioned to maintain the current densities of large-diameter trees and high AGB into the future due to the species richness of large trees and a high density of replacement smaller trees.

Diversity and density patterns of large old trees in China

Large old trees are keystone ecological structures that provide vital ecosystem services to humans. However, there are few large-scale empirical studies on patterns of diversity and density of large old trees in human-dominated landscapes. We present the results of the first nationwide study in China to investigate the patterns of diversity and density of large old trees in human-dominated landscapes. We collated data on 682,730 large trees ≥100 years old from 198 Chinese regions to quantify tree species diversity, tree density and maximum tree age patterns. We modelled the effects of natural environmental variables (e.g. climate and topography) and anthropogenic variables (e.g. human population density and city age) on these measures. We found a low density of large old trees across study regions (0.36 trees/km²), and large variation in species richness among regions (ranging from 1 to 232 species). More than 95% of trees were <500 years old. The best fit models showed that: (1) Species diversity (species richness adjusted by region size) was positively associated with mean annual rainfall and city age; (2) Density of clustered trees, which are mostly remnants of ancient woods, was negatively influenced by human population density and rural population (% of total population). In contrast, the density of scattered trees, which are mostly managed by local people, was positively correlated with mean annual rainfall and human population density. To better protect large old trees in cities and other highly-populated areas, conservation policy should protect ancient wood remnants, mitigate the effects environmental change (e.g. habitat fragmentation), minimize the negative effects of human activities (e.g. logging), and mobilize citizens to participate in conservation activities (e.g. watering trees during droughts).

Prediction of forest aboveground net primary production from high-resolution vertical leaf-area profiles

Temperature and precipitation explain about half the variation in aboveground net primary production (ANPP) among tropical forest sites, but determinants of remaining variation are poorly understood. Here, we test the hypothesis that the amount of leaf area, and its vertical arrangement, predicts ANPP when other variables are held constant. Using measurements from airborne lidar in a lowland Neotropical rain forest, we quantify vertical leaf-area profiles and develop models of ANPP driven by leaf area and other measurements of forest structure. Vertical leaf-area profiles predict 38% of the variation among plots. This number is 4.5 times greater than models using total leaf area (disregarding vertical arrangement) and 2.1 times greater than models using canopy height alone. Furthermore, ANPP predictions from vertical leaf-area profiles were less biased than alternate metrics. Variation in ANPP not attributable to temperature or precipitation can be predicted by the vertical distribution of leaf area in this system.

Density-dependent adult recruitment in a low-density tropical tree

An important class of negative feedbacks in population dynamics is the activity of host-specific enemies that disproportionately kill individuals in locations where they are common. This mechanism, called the Janzen–Connell hypothesis, has been proposed as a determinant of the large number of species in tropical forests. A critical but untested assumption of the hypothesis is that density-dependent mortality among juvenile trees reduces the probability of adult recruitment. Here, we show that adult recruitment is negatively density dependent in a low-density tree population using time series from high-resolution remote sensing. However, this density dependence was not strong enough to stabilize the size of the adult population, which increased significantly in size.

The Janzen–Connell hypothesis is a well-known explanation for why tropical forests have large numbers of tree species. A fundamental prediction of the hypothesis is that the probability of adult recruitment is less in regions of high conspecific adult density, a pattern mediated by density-dependent mortality in juvenile life stages. Although there is strong evidence in many tree species that seeds, seedlings, and saplings suffer conspecific density-dependent mortality, no study has shown that adult tree recruitment is negatively density dependent. Density-dependent adult recruitment is necessary for the Janzen–Connell mechanism to regulate tree populations. Here, we report density-dependent adult recruitment in the population of Handroanthus guayacan, a wind-dispersed Neotropical canopy tree species. We use data from high-resolution remote sensing to track individual trees with proven capacity to flower in a lowland moist forest landscape in Panama and analyze these data in a Bayesian framework similar to capture–recapture analysis. We independently quantify probabilities of adult tree recruitment and detection and show that adult recruitment is negatively density dependent. The annualized probability of adult recruitment was 3.03% ⋅ year⁻¹. Despite the detection of negative density dependence in adult recruitment, it was insufficient to stabilize the adult population of H. guayacan, which increased significantly in size over the decade of observation.

Hidden collapse is driven by fire and logging in a socioecological forest ecosystem

Increasing numbers of ecosystems globally are at risk of collapse. However, most descriptions of terrestrial ecosystem collapse are post hoc with few empirically based examples of ecosystems in the process of collapse. This limits learning about collapse and impedes development of effective early-warning indicators. Based on multidecadal and multifaceted monitoring, we present evidence that the Australian mainland Mountain Ash ecosystem is collapsing. Collapse is indicated by marked changes in ecosystem condition, particularly the rapid decline in populations of keystone ecosystem structures. There also has been significant decline in biodiversity strongly associated with these structures and disruptions of key ecosystem processes. In documenting the decline of the Mountain Ash ecosystem, we uncovered evidence of hidden collapse. This is where an ecosystem superficially appears to be relatively intact, but a prolonged period of decline coupled with long lag times for recovery of dominant ecosystem components mean that collapse is almost inevitable. In ecosystems susceptible to hidden collapse, management interventions will be required decades earlier than currently perceived by policy makers. Responding to hidden collapse is further complicated by our finding that different drivers produce different pathways to collapse, but these drivers can interact in ways that exacerbate and perpetuate collapse. Management must focus not only on reducing the number of critical stressors influencing an ecosystem but also on breaking feedbacks between stressors. We demonstrate the importance of multidecadal monitoring programs in measuring state variables that can inform quantitative predictions of collapse as well as help identify management responses that can avert system-wide collapse.

Chronosequence predictions are robust in a Neotropical secondary forest, but plots miss the mark

Tropical secondary forests (TSF) are a global carbon sink of 1.6 Pg C/year. However, TSF carbon uptake is estimated using chronosequence studies that assume differently aged forests can be used to predict change in aboveground biomass density (AGBD) over time. We tested this assumption using two airborne lidar datasets separated by 11.5 years over a Neotropical landscape. Using data from 1998, we predicted canopy height and AGBD within 1.1 and 10.3% of observations in 2009, with higher accuracy for forest height than AGBD and for older TSFs in comparison to younger ones. This result indicates that the space-for-time assumption is robust at the landscape-scale. However, since lidar measurements of secondary tropical forest are rare, we used the 1998 lidar dataset to test how well plot-based studies quantify the mean TSF height and biomass in a landscape. We found that the sample area required to produce estimates of height or AGBD close to the landscape mean is larger than the typical area sampled in secondary forest chronosequence studies. For example, estimating AGBD within 10% of the landscape mean requires more than thirty 0.1 ha plots per age class, and more total area for larger plots. We conclude that under-sampling in ground-based studies may introduce error into estimations of the TSF carbon sink, and that this error can be reduced by more extensive use of lidar measurements.

Adult mortality in a low-density tree population using high-resolution remote sensing

We developed a statistical framework to quantify mortality rates in canopy trees observed using time series from high-resolution remote sensing. By timing the acquisition of remote sensing data with synchronous annual flowering in the canopy tree species Handroanthus guayacan, we made 2,596 unique detections of 1,006 individual adult trees within 18,883 observation attempts on Barro Colorado Island, Panama (BCI) during an 11-yr period. There were 1,057 observation attempts that resulted in missing data due to cloud cover or incomplete spatial coverage. Using the fraction of 123 individuals from an independent field sample that were detected by satellite data (109 individuals, 88.6%), we estimate that the adult population for this species on BCI was 1,135 individuals. We used a Bayesian state-space model that explicitly accounted for the probability of tree detection and missing observations to compute an annual adult mortality rate of 0.2%·yr^-1 (SE = 0.1, 95% CI = 0.06-0.45). An independent estimate of the adult mortality rate from 260 field-checked trees closely matched the landscape-scale estimate (0.33%·yr^-1 , SE = 0.16, 95% CI = 0.12-0.74). Our proof-of-concept study shows that one can remotely estimate adult mortality rates for canopy tree species precisely in the presence of variable detection and missing observations.

Landscape-scale consequences of differential tree mortality from catastrophic wind disturbance in the Amazon

Wind disturbance can create large forest blowdowns, which greatly reduces live biomass and adds uncertainty to the strength of the Amazon carbon sink. Observational studies from within the central Amazon have quantified blowdown size and estimated total mortality but have not determined which trees are most likely to die from a catastrophic wind disturbance. Also, the impact of spatial dependence upon tree mortality from wind disturbance has seldom been quantified, which is important because wind disturbance often kills clusters of trees due to large treefalls killing surrounding neighbors. We examine (1) the causes of differential mortality between adult trees from a 300-ha blowdown event in the Peruvian region of the northwestern Amazon, (2) how accounting for spatial dependence affects mortality predictions, and (3) how incorporating both differential mortality and spatial dependence affect the landscape level estimation of necromass produced from the blowdown. Standard regression and spatial regression models were used to estimate how stem diameter, wood density, elevation, and a satellite-derived disturbance metric influenced the probability of tree death from the blowdown event. The model parameters regarding tree characteristics, topography, and spatial autocorrelation of the field data were then used to determine the consequences of non-random mortality for landscape production of necromass through a simulation model. Tree mortality was highly non-random within the blowdown, where tree mortality rates were highest for trees that were large, had low wood density, and were located at high elevation. Of the differential mortality models, the non-spatial models overpredicted necromass, whereas the spatial model slightly underpredicted necromass. When parameterized from the same field data, the spatial regression model with differential mortality estimated only 7.5% more dead trees across the entire blowdown than the random mortality model, yet it estimated 51% greater necromass. We suggest that predictions of forest carbon loss from wind disturbance are sensitive to not only the underlying spatial dependence of observations, but also the biological differences between individuals that promote differential levels of mortality.

The ecology, distribution, conservation and management of large old trees

Large old trees are some of the most iconic biota on earth and are integral parts of many terrestrial ecosystems including those in tropical, temperate and boreal forests, deserts, savannas, agro-ecological areas, and urban environments. In this review, we provide new insights into the ecology, function, evolution and management of large old trees through broad cross-disciplinary perspectives from literatures in plant physiology, growth and development, evolution, habitat value for fauna and flora, and conservation management. Our review reveals that the diameter, height and longevity of large old trees varies greatly on an inter-specific basis, thereby creating serious challenges in defining large old trees and demanding an ecosystem- and species-specific definition that will only rarely be readily transferable to other species or ecosystems. Such variation is also manifested by marked inter-specific differences in the key attributes of large old trees (beyond diameter and height) such as the extent of buttressing, canopy architecture, the extent of bark micro-environments and the prevalence of cavities. We found that large old trees play an extraordinary range of critical ecological roles including in hydrological regimes, nutrient cycles and numerous ecosystem processes. Large old trees strongly influence the spatial and temporal distribution and abundance of individuals of the same species and populations of numerous other plant and animal species. We suggest many key characteristics of large old trees such as extreme height, prolonged lifespans, and the presence of cavities - which confer competitive and evolutionary advantages in undisturbed environments - can render such trees highly susceptible to a range of human influences. Large old trees are vulnerable to threats ranging from droughts, fire, pests and pathogens, to logging, land clearing, landscape fragmentation and climate change. Tackling such diverse threats is challenging because they often interact and manifest in different ways in different ecosystems, demanding targeted species- or ecosystem-specific responses. We argue that novel management actions will often be required to protect existing large old trees and ensure the recruitment of new cohorts of such trees. For example, fine-scale tree-level conservation such as buffering individual stems will be required in many environments such as in agricultural areas and urban environments. Landscape-level approaches like protecting places where large old trees are most likely to occur will be needed. However, this brings challenges associated with likely changes in tree distributions associated with climate change, because long-lived trees may presently exist in places unsuitable for the development of new cohorts of the same species. Appropriate future environmental domains for a species could exist in new locations where it has never previously occurred. The future distribution and persistence of large old trees may require controversial responses including assisted migration via seed or seedling establishment in new locales. However, the effectiveness of such approaches may be limited where key ecological features of large old trees (such as cavity presence) depend on other species such as termites, fungi and bacteria. Unless other species with similar ecological roles are present to fulfil these functions, these taxa might need to be moved concurrently with the target tree species.

Explaining biomass growth of tropical canopy trees: the importance of sapwood

Tropical forests are important in worldwide carbon (C) storage and sequestration. C sequestration of these forests may especially be determined by the growth of canopy trees. However, the factors driving variation in growth among such large individuals remain largely unclear. We evaluate how crown traits [total leaf area, specific leaf area and leaf nitrogen (N) concentration] and stem traits [sapwood area (SA) and sapwood N concentration] measured for individual trees affect absolute biomass growth for 43 tropical canopy trees belonging to four species, in a moist forest in Bolivia. Biomass growth varied strongly among trees, between 17.3 and 367.3 kg year⁻¹, with an average of 105.4 kg year⁻¹. We found that variation in biomass growth was chiefly explained by a positive effect of SA, and not by tree size or other traits examined. SA itself was positively associated with sapwood growth, sapwood lifespan and basal area. We speculate that SA positively affects the growth of individual trees mainly by increasing water storage, thus securing water supply to the crown. These positive roles of sapwood on growth apparently offset the increased respiration costs incurred by more sapwood. This is one of the first individual-based studies to show that variation in sapwood traits—and not crown traits—explains variation in growth among tropical canopy trees. Accurate predictions of C dynamics in tropical forests require similar studies on biomass growth of individual trees as well as studies evaluating the dual effect of sapwood (water provision vs. respiratory costs) on tropical tree growth.

The importance of crown dimensions to improve tropical tree biomass estimates

Tropical forests play a vital role in the global carbon cycle, but the amount of carbon they contain and its spatial distribution remain uncertain. Recent studies suggest that once tree height is accounted for in biomass calculations, in addition to diameter and wood density, carbon stock estimates are reduced in many areas. However, it is possible that larger crown sizes might offset the reduction in biomass estimates in some forests where tree heights are lower because even comparatively short trees develop large, well-lit crowns in or above the forest canopy. While current allometric models and theory focus on diameter, wood density, and height, the influence of crown size and structure has not been well studied. To test the extent to which accounting for crown parameters can improve biomass estimates, we harvested and weighed 51 trees (11-169 cm diameter) in southwestern Amazonia where no direct biomass measurements have been made. The trees in our study had nearly half of total aboveground biomass in the branches (44% +/- 2% [mean +/- SE]), demonstrating the importance of accounting for tree crowns. Consistent with our predictions, key pantropical equations that include height, but do not account for crown dimensions, underestimated the sum total biomass of all 51 trees by 11% to 14%, primarily due to substantial underestimates of many of the largest trees. In our models, including crown radius greatly improves performance and reduces error, especially for the largest trees. In addition, over the full data set, crown radius explained more variation in aboveground biomass (10.5%) than height (6.0%). Crown form is also important: Trees with a monopodial architectural type are estimated to have 21-44% less mass than trees with other growth patterns. Our analysis suggests that accounting for crown allometry would substantially improve the accuracy of tropical estimates of tree biomass and its distribution in primary and degraded forests.

Winners and losers in the competition for space in tropical forest canopies

Trees compete for space in the canopy, but where and how individuals or their component parts win or lose is poorly understood. We developed a stochastic model of three-dimensional dynamics in canopies using a hierarchical Bayesian framework, and analysed 267,533 positive height changes from 1.25 m pixels using data from airborne LiDAR within 43 ha on the windward flank of Mauna Kea. Model selection indicates a strong resident's advantage, with 97.9% of positions in the canopy retained by their occupants over 2 years. The remaining 2.1% were lost to a neighbouring contender. Absolute height was a poor predictor of success, but short stature greatly raised the risk of being overtopped. Growth in the canopy was exponentially distributed with a scaling parameter of 0.518. These findings show how size and spatial proximity influence the outcome of competition for space, and provide a general framework for the analysis of canopy dynamics.