Publication Search Results

ID: 159526
Type: article
Authors: Anderson-Teixeira, Kristina J.; Herrmann, Valentine; Banbury Morgan, Rebecca; Bond-Lamberty, Ben; Cook-Patton, Susan C.; Ferson, Abigail E.; Muller-Landau, Helene C.; Wang, Maria M. H.
Abstract: Forests are major components of the global carbon (C) cycle and thereby strongly influence atmospheric carbon dioxide (CO2) and climate. However, efforts to incorporate forests into climate models and CO2 accounting frameworks have been constrained by a lack of accessible, global-scale synthesis on how C cycling varies across forest types and stand ages. Here, we draw from the Global Forest Carbon Database, ForC, to provide a macroscopic overview of C cycling in the world's forests, giving special attention to stand age-related variation. Specifically, we use 11 923 ForC records for 34 C cycle variables from 865 geographic locations to characterize ensemble C budgets for four broad forest types-tropical broadleaf evergreen, temperate broadleaf, temperate conifer, and boreal. We calculate means and standard deviations for both mature and regrowth (age < 100 years) forests and quantify trends with stand age in regrowth forests for all variables with sufficient data. C cycling rates generally decreased from tropical to temperate to boreal in both mature and regrowth forests, whereas C stocks showed less directional variation. Mature forest net ecosystem production did not differ significantly among biomes. The majority of flux variables, together with most live biomass pools, increased significantly with the logarithm of stand age. As climate change accelerates, understanding and managing the carbon dynamics of forests is critical to forecasting, mitigation, and adaptation. This comprehensive and synthetic global overview of C stocks and fluxes across biomes and stand ages contributes to these efforts.

ID: 158908
Type: article
Authors: Banbury Morgan, Rebecca; Herrmann, Valentine; Kunert, Norbert; Bond-Lamberty, Ben; Muller-Landau, Helene C.; Anderson-Teixeira, Kristina J.
Abstract: Carbon (C) fixation, allocation, and metabolism by trees set the basis for energy and material flows in forest ecosystems and define their interactions with Earth's changing climate. However, while many studies have considered variation in productivity with latitude and climate, we lack a cohesive synthesis on how forest carbon fluxes vary globally with respect to climate and one another. Here, we draw upon 1,319 records from the Global Forest Carbon Database, representing all major forest types and the nine most significant autotrophic carbon fluxes, to comprehensively review how annual C cycling in mature, undisturbed forests varies with latitude and climate on a global scale. Across all flux variables analyzed, rates of C cycling decreased continuously with absolute latitude-a finding that confirms multiple previous studies and contradicts the idea that net primary productivity of temperate forests rivals that of tropical forests. C flux variables generally displayed similar trends across latitude and multiple climate variables, with no differences in allocation detected at this global scale. Temperature variables in general, and mean annual temperature or temperature seasonality in particular, were the best single predictors of C flux, explaining 19%-71% of variation in the C fluxes analyzed. The effects of temperature were modified by moisture availability, with C flux reduced under hot and dry conditions and sometimes under very high precipitation. Annual C fluxes increased with growing season length and were also influenced by growing season climate. These findings clarify how forest C flux varies with latitude and climate on a global scale. In an era when forests will play a critical yet uncertain role in shaping Earth's rapidly changing climate, our synthesis provides a foundation for understanding global patterns in forest C cycling.

ID: 158553
Type: article
Authors: Davies, Stuart J.; Abiem, Iveren; Abu Salim, Kamariah; Aguilar, Salomon; Allen, David; Alonso, Alfonso; Anderson-Teixeira, Kristina; Andrade, Ana; Arellano, Gabriel; Ashton, Peter S.; Baker, Patrick J.; Baker, Matthew E.; Baltzer, Jennifer L.; Basset, Yves; Bissiengou, Pulcherie; Bohlman, Stephanie; Bourg, Norman A.; Brockelman, Warren Y.; Bunyavejchewin, Sarayudh; Burslem, David F. R. P.; Cao, Min; Cardenas, Dairon; Chang, Li-Wan; Chang-Yang, Chia-Hao; Chao, Kuo-Jung; Chao, Wei-Chun; Chapman, Hazel; Chen, Yu-Yun; Chisholm, Ryan A.; Chu, Chengjin; Chuyong, George; Clay, Keith; Comita, Liza S.; Condit, Richard; Cordell, Susan; Dattaraja, Handanakere S.; de Oliveira, Alexandre Adalardo; den Ouden, Jan; Detto, Matteo; Dick, Christopher; Du, Xiaojun; Duque, Alvaro; Ediriweera, Sisira; Ellis, Erle C.; Obiang, Nestor Laurier Engone; Esufali, Shameema; Ewango, Corneille E. N.; Fernando, Edwino S.; Filip, Jonah; Fischer, Gunter A.; Foster, Robin; Giambelluca, Thomas; Giardina, Christian; Gilbert, Gregory S.; Gonzalez-Akre, Erika; Gunatilleke, I. A. U. N.; Gunatilleke, C. V. S.; Hao, Zhanqing; Hau, Billy C. H.; He, Fangliang; Ni, Hongwei; Howe, Robert W.; Hubbell, Stephen P.; Huth, Andreas; Inman-Narahari, Faith; Itoh, Akira; Janik, David; Jansen, Patrick A.; Jiang, Mingxi; Johnson, Daniel J.; Jones, F. Andrew; Kanzaki, Mamoru; Kenfack, David; Kiratiprayoon, Somboon; Kral, Kamil; Krizel, Lauren; Lao, Suzanne; Larson, Andrew J.; Li, Yide; Li, Xiankun; Litton, Creighton M.; Liu, Yu; Liu, Shirong; Lum, Shawn K. Y.; Luskin, Matthew S.; Lutz, James A.; Hong Truong Luu; Ma, Keping; Makana, Jean-Remy; Malhi, Yadvinder; Martin, Adam; McCarthy, Caly; McMahon, Sean M.; McShea, William J.; Memiaghe, Herve; Mi, Xiangcheng; Mitre, David; Mohamad, Mohizah; Monks, Logan; Muller-Landau, Helene C.; Musili, Paul M.; Myers, Jonathan A.; Nathalang, Anuttara; Ngo, Kang Min; Norden, Natalia; Novotny, Vojtech; O'Brien, Michael J.; Orwig, David; Ostertag, Rebecca; Papathanassiou, Konstantinos; Parker, Geoffrey G.; Perez, Rolando; Perfecto, Ivette; Phillips, Richard P.; Pongpattananurak, Nantachai; Pretzsch, Hans; Ren, Haibo; Reynolds, Glen; Rodriguez, Lillian J.; Russo, Sabrina E.; Sack, Lawren; Sang, Weiguo; Shue, Jessica; Singh, Anudeep; Song, Guo-Zhang M.; Sukumar, Raman; Sun, I-Fang; Suresh, Hebbalalu S.; Swenson, Nathan G.; Tan, Sylvester; Thomas, Sean C.; Thomas, Duncan; Thompson, Jill; Turner, Benjamin L.; Uowolo, Amanda; Uriarte, Maria; Valencia, Renato; Vandermeer, John; Vicentini, Alberto; Visser, Marco; Vrska, Tomas; Wang, Xugao; Wang, Xihua; Weiblen, George D.; Whitfeld, Timothy J. S.; Wolf, Y.; Wright, S. Joseph; Xu, Han; Yao, Tze Leong; Yap, Sandra L.; Ye, Wanhui; Yu, Mingjian; Zhang, Minhua; Zhu, Daoguang; Zhu, Li; Zimmerman, Jess K.; Zuleta, Daniel
Abstract: ForestGEO is a network of scientists and long-term forest dynamics plots (FDPs) spanning the Earth's major forest types. ForestGEO's mission is to advance understanding of the diversity and dynamics of forests and to strengthen global capacity for forest science research. ForestGEO is unique among forest plot networks in its large-scale plot dimensions, censusing of all stems >= 1 cm in diameter, inclusion of tropical, temperate and boreal forests, and investigation of additional biotic (e.g., arthropods) and abiotic (e.g., soils) drivers, which together provide a holistic view of forest functioning. The 71 FDPs in 27 countries include approximately 7.33 million living trees and about 12,000 species, representing 20% of the world's known tree diversity. With >1300 published papers, ForestGEO researchers have made significant contributions in two fundamental areas: species coexistence and diversity, and ecosystem functioning. Specifically, defining the major biotic and abiotic controls on the distribution and coexistence of species and functional types and on variation in species' demography has led to improved understanding of how the multiple dimensions of forest diversity are structured across space and time and how this diversity relates to the processes controlling the role of forests in the Earth system. Nevertheless, knowledge gaps remain that impede our ability to predict how forest diversity and function will respond to climate change and other stressors. Meeting these global research challenges requires major advances in standardizing taxonomy of tropical species, resolving the main drivers of forest dynamics, and integrating plot-based ground and remote sensing observations to scale up estimates of forest diversity and function, coupled with improved predictive models. However, they cannot be met without greater financial commitment to sustain the long-term research of ForestGEO and other forest plot networks, greatly expanded scientific capacity across the world's forested nations, and increased collaboration and integration among research networks and disciplines addressing forest science.

ID: 158537
Type: article
Authors: Kunert, Norbert; Zailaa, Joseph; Herrmann, Valentine; Muller-Landau, Helene C.; Wright, S. Joseph; Perez, Rolando; McMahon, Sean M.; Condit, Richard C.; Hubbell, Steven P.; Sack, Lawren; Davies, Stuart J.; Anderson-Teixeira, Kristina J.
Abstract: The effects of climate change on tropical forests will depend on how diverse tropical tree species respond to drought. Current distributions of evergreen and deciduous tree species across local and regional moisture gradients reflect their ability to tolerate drought stress, and might be explained by functional traits. We measured leaf water potential at turgor loss (i.e. 'wilting point'; pi(tlp)), wood density (WD) and leaf mass per area (LMA) on 50 of the most abundant tree species in central Panama. We then tested their ability to explain distributions of evergreen and deciduous species within a 50 ha plot on Barro Colorado Island and across a 70 km rainfall gradient spanning the Isthmus of Panama. Among evergreen trees, species with lower pi(tlp) were associated with drier habitats, with pi(tlp) explaining 28% and 32% of habitat association on local and regional scales, respectively, greatly exceeding the predictive power of WD and LMA. In contrast, pi(tlp) did not predict habitat associations among deciduous species. Across spatial scales, pi(tlp) is a useful indicator of habitat preference for tropical tree species that retain their leaves during periods of water stress, and holds the potential to predict vegetation responses to climate change.

ID: 157929
Type: article
Authors: Muller-Landau, Helene C.; Cushman, K. C.; Arroyo, Eva E.; Cano, Isabel Martinez; Anderson-Teixeira, Kristina J.; Backiel, Bogumila
Abstract: Tropical forests vary widely in biomass carbon (C) stocks and fluxes even after controlling for forest age. A mechanistic understanding of this variation is critical to accurately predicting responses to global change. We review empirical studies of spatial variation in tropical forest biomass, productivity and woody residence time, focusing on mature forests. Woody productivity and biomass decrease from wet to dry forests and with elevation. Within lowland forests, productivity and biomass increase with temperature in wet forests, but decrease with temperature where water becomes limiting. Woody productivity increases with soil fertility, whereas residence time decreases, and biomass responses are variable, consistent with an overall unimodal relationship. Areas with higher disturbance rates and intensities have lower woody residence time and biomass. These environmental gradients all involve both direct effects of changing environments on forest C fluxes and shifts in functional composition - including changing abundances of lianas - that substantially mitigate or exacerbate direct effects. Biogeographic realms differ significantly and importantly in productivity and biomass, even after controlling for climate and biogeochemistry, further demonstrating the importance of plant species composition. Capturing these patterns in global vegetation models requires better mechanistic representation of water and nutrient limitation, plant compositional shifts and tree mortality.

ID: 157939
Type: article
Authors: Araujo, Raquel Fernandes; Chambers, Jeffrey Q.; Souza Celes, Carlos Henrique; Muller-Landau, Helene C.; Ferreira dos Santos, Ana Paula; Emmert, Fabiano; Ribeiro, Gabriel H. P. M.; Gimenez, Bruno Oliva; Lima, Adriano J. N.; Campos, Moacir A. A.; Higuchi, Niro
Abstract: Tree growth and survival differ strongly between canopy trees (those directly exposed to overhead light), and understory trees. However, the structural complexity of many tropical forests makes it difficult to determine canopy positions. The integration of remote sensing and ground-based data enables this determination and measurements of how canopy and understory trees differ in structure and dynamics. Here we analyzed 2 cm resolution RGB imagery collected by a Remotely Piloted Aircraft System (RPAS), also known as drone, together with two decades of bi-annual tree censuses for 2 ha of old growth forest in the Central Amazon. We delineated all crowns visible in the imagery and linked each crown to a tagged stem through field work. Canopy trees constituted 40% of the 1244 inventoried trees with diameter at breast height (DBH) > 10 cm, and accounted for similar to 70% of aboveground carbon stocks and wood productivity. The probability of being in the canopy increased logistically with tree diameter, passing through 50% at 23.5 cm DBH. Diameter growth was on average twice as large in canopy trees as in understory trees. Growth rates were unrelated to diameter in canopy trees and positively related to diameter in understory trees, consistent with the idea that light availability increases with diameter in the understory but not the canopy. The whole stand size distribution was best fit by a Weibull distribution, whereas the separate size distributions of understory trees or canopy trees > 25 cm DBH were equally well fit by exponential and Weibull distributions, consistent with mechanistic forest models. The identification and field mapping of crowns seen in a high resolution orthomosaic revealed new patterns in the structure and dynamics of trees of canopy vs. understory at this site, demonstrating the value of traditional tree censuses with drone remote sensing.

ID: 156603
Type: article
Authors: Gora, Evan M.; Burchfield, Jeffrey C.; Muller‐Landau, Helene C.; Bitzer, Phillip M.; Yanoviak, Stephen P.

ID: 155500
Type: article
Authors: Gora, Evan M.; Muller‐Landau, Helene C.; Burchfield, Jeffrey C.; Bitzer, Phillip M.; Hubbell, Stephen P.; Yanoviak, Stephen P.
Abstract: Tree death due to lightning influences tropical forest carbon cycling and tree community dynamics. However, the distribution of lightning damage among trees in forests remains poorly understood. We developed models to predict direct and secondary lightning damage to trees based on tree size, crown exposure, and local forest structure. We parameterized these models using data on the locations of lightning strikes and censuses of tree damage in strike zones, combined with drone-based maps of tree crowns and censuses of all trees within a 50-ha forest dynamics plot on Barro Colorado Island, Panama. The likelihood of a direct strike to a tree increased with larger exposed crown area and higher relative canopy position (emergent > canopy >>> subcanopy), whereas the likelihood of secondary lightning damage increased with tree diameter and proximity to neighboring trees. The predicted frequency of lightning damage in this mature forest was greater for tree species with larger average diameters. These patterns suggest that lightning influences forest structure and the global carbon budget by nonrandomly damaging large trees. Moreover, these models provide a framework for investigating the ecological and evolutionary consequences of lightning disturbance in tropical forests. Synthesis: Our findings indicate that the distribution of lightning damage is stochastic at large spatial grain and relatively deterministic at smaller spatial grain (<15 m). Lightning is more likely to directly strike taller trees with large crowns and secondarily damage large neighboring trees that are closest to the directly struck tree. The results provide a framework for understanding how lightning can affect forest structure, forest dynamics, and carbon cycling. The resulting lightning risk model will facilitate informed investigations into the effects of lightning in tropical forests.

ID: 155905
Type: article
Authors: Koven, Charles D.; Knox, Ryan G.; Fisher, Rosie A.; Chambers, Jeffrey Q.; Christoffersen, Bradley O.; Davies, Stuart J.; Detto, Matteo; Dietze, Michael C.; Faybishenko, Boris; Holm, Jennifer; Huang, Maoyi; Kovenock, Marlies; Kueppers, Lara M.; Lemieux, Gregory; Massoud, Elias; McDowell, Nathan G.; Muller-Landau, Helene C.; Needham, Jessica F.; Norby, Richard J.; Powell, Thomas; Rogers, Alistair; Serbin, Shawn P.; Shuman, Jacquelyn K.; Swann, Abigail L. S.; Varadharajan, Charuleka; Walker, Anthony P.; Wright, S. Joseph; Xu, Chonggang
Abstract: Plant functional traits determine vegetation responses to environmental variation, but variation in trait values is large, even within a single site. Likewise, uncertainty in how these traits map to Earth system feedbacks is large. We use a vegetation demographic model (VDM), the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to explore parameter sensitivity of model predictions, and comparison to observations, at a tropical forest site: Barro Colorado Island in Panama. We define a single 12-dimensional distribution of plant trait variation, derived primarily from observations in Panama, and define plant functional types (PFTs) as random draws from this distribution. We compare several model ensembles, where individual ensemble members vary only in the plant traits that define PFTs, and separate ensembles differ from each other based on either model structural assumptions or non-trait, ecosystem-level parameters, which include (a) the number of competing PFTs present in any simulation and (b) parameters that govern disturbance and height-based light competition. While single-PFT simulations are roughly consistent with observations of productivity at Barro Colorado Island, increasing the number of competing PFTs strongly shifts model predictions towards higher productivity and biomass forests. Different ecosystem variables show greater sensitivity than others to the number of competing PFTs, with the predictions that are most dominated by large trees, such as biomass, being the most sensitive. Changing disturbance and height-sorting parameters, i.e., the rules of competitive trait filtering, shifts regimes of dominance or coexistence between early- and late-successional PFTs in the model. Increases to the extent or severity of disturbance, or to the degree of determinism in height-based light competition, all act to shift the community towards early-successional PFTs. In turn, these shifts in competitive outcomes alter predictions of ecosystem states and fluxes, with more early-successional-dominated forests having lower biomass. It is thus crucial to differentiate between plant traits, which are under competitive pressure in VDMs, from those model parameters that are not and to better understand the relationships between these two types of model parameters to quantify sources of uncertainty in VDMs.

ID: 156602
Type: article
Authors: Martínez Cano, Isabel; Shevliakova, Elena; Malyshev, Sergey; Wright, S. J.; Detto, Matteo; Pacala, Stephen W.; Muller‐Landau, Helene C.

ID: 152409
Type: article
Authors: Rutishauser, Ervan; Wright, S. Joseph; Condit, Richard; Hubbell, Stephen P.; Davies, Stuart J.; Muller-Landau, Helene C.
Abstract: Tropical forest responses to climate and atmospheric change are critical to the future of the global carbon budget. Recent studies have reported increases in estimated above-ground biomass (EAGB) stocks, productivity, and mortality in old-growth tropical forests. These increases could reflect a shift in forest functioning due to global change and/or long-lasting recovery from past disturbance. We introduce a novel approach to disentangle the relative contributions of these mechanisms by decomposing changes in whole-plot biomass fluxes into contributions from changes in the distribution of gap-successional stages and changes in fluxes for a given stage. Using 30 years of forest dynamic data at Barro Colorado Island (BCI), Panama, we investigated temporal variation in EAGB fluxes as a function of initial EAGB in 10x10m quadrats. Productivity and mortality fluxes both increased strongly with initial quadrat EAGB. The distribution of EAGB (and thus initial EAGB) across quadrats hardly varied over 30 years (and 7 censuses). EAGB fluxes as a function of initial EAGB varied strongly and significantly among census intervals, with notably higher productivity in 1985-1990 associated with recovery from the 1982-83 El Niño event. Variation in whole-plot fluxes among census intervals was explained overwhelmingly by variation in fluxes as a function of initial EAGB, with essentially no contribution from changes in initial EAGB distributions. The high observed temporal variation in productivity and mortality suggests that this forest is very sensitive to climate variability. There was no consistent long-term trend in productivity, mortality, or biomass in this forest over 30 years, although the temporal variability in productivity and mortality was so strong that it could well mask a substantial trend. Accurate prediction of future tropical forest carbon budgets will require accounting for disturbance-recovery dynamics and understanding temporal variability in productivity and mortality.

ID: 152754
Type: article
Authors: Yanoviak, Stephen P.; Gora, Evan M.; Bitzer, Phillip M.; Burchfield, Jeffrey C.; Muller-Landau, Helene C.; Detto, Matteo; Paton, Steven; Hubbell, Stephen P.
Abstract: The mortality rates of large trees are critical to determining carbon stocks in tropical forests, but the mechanisms of tropical tree mortality remain poorly understood. Lightning strikes thousands of tropical trees every day, but is commonly assumed to be a minor agent of tree mortality in most tropical forests. We use the first systematic quantification of lightning-caused mortality to show that lightning is a major cause of death for the largest trees in an old-growth lowland forest in Panama. A novel lightning strike location system together with field surveys of strike sites revealed that, on average, each strike directly kills 3.5 trees (>10 cm diameter)and damages 11.4 more. Given lightning frequencydata from the Earth Networks Total Lightning Networkand historical total tree mortality rates for this site, we conclude that lightning accounts for 40.5% of the mortality of large trees (>60 cm diameter) in the short termand likely contributes to an additional 9.0% of large tree deaths over the long term. Any changes in cloud-to-ground lightning frequency due to climatic change will alter tree mortality rates; projected 25-50% increases in lightning frequency would increase large tree mortality rates in this forest by 9-18%. The results of this study indicate that lightning plays a criticaland previously underestimated role in tropical forest dynamics and carbon cycling.

ID: 151797
Type: article
Authors: Broekman, Maarten J. E.; Muller-Landau, Helene C.; Visser, Marco D.; Jongejans, Eelke; Wright, S. Joseph; de Kroon, Hans
Abstract: Many empirical studies motivated by an interest in stable coexistence have quantified negative density dependence, negative frequency dependence, or negative plant-soil feedback, but the links between these empirical results and ecological theory are not straightforward. Here, we relate these analyses to theoretical conditions for stabilisation and stable coexistence in classical competition models. By stabilisation, we mean an excess of intraspecific competition relative to interspecific competition that inherently slows or even prevents competitive exclusion. We show that most, though not all, tests demonstrating negative density dependence, negative frequency dependence, and negative plant-soil feedback constitute sufficient conditions for stabilisation of two-species interactions if applied to data for per capita population growth rates of pairs of species, but none are necessary or sufficient conditions for stable coexistence of two species. Potential inferences are even more limited when communities involve more than two species, and when performance is measured at a single life stage or vital rate. We then discuss two approaches that enable stronger tests for stable coexistence-invasibility experiments and model parameterisation. The model parameterisation approach can be applied to typical density-dependence, frequency-dependence, and plant-soil feedback data sets, and generally enables better links with mechanisms and greater insights, as demonstrated by recent studies.

ID: 150595
Type: article
Authors: Gora, Evan M.; Kneale, Riley C.; Larjavaara, Markku; Muller-Landau, Helene C.
Abstract: Woody debris (WD) stocks and fluxes are important components of forest carbon budgets and yet remain understudied, particularly in tropical forests. Here we present the most comprehensive assessment of WD stocks and fluxes yet conducted in a tropical forest, including one of the first tropical estimates of suspended WD. We rely on data collected over 8 years in an old-growth moist tropical forest in Panama to quantify spatiotemporal variability and estimate minimum sample sizes for different components. Downed WD constituted the majority of total WD mass (78%), standing WD contributed a substantial minority (21%), and suspended WD was the smallest component (1%). However, when considering sections of downed WD that are elevated above the soil, the majority of WD inputs and approximately 50% of WD stocks were disconnected from the forest floor. Branchfall and liana wood accounted for 17 and 2% of downed WD, respectively. Residence times averaged 1.9 years for standing coarse WD (CWD; > 20 cm diameter) and 3.6 years for downed CWD. WD stocks and inputs were highly spatially variable, such that the sampling efforts necessary to estimate true values within 10% with 95% confidence were > 130 km of transects for downed CWD and > 550 ha area for standing CWD. The vast majority of studies involve much lower sampling efforts, suggesting that considerably more data are required to precisely quantify tropical forest WD pools and fluxes. The demonstrated importance of elevated WD in our study indicates a need to understand how elevation above the ground alters decomposition rates and incorporate this understanding into models of forest carbon cycling.

ID: 150601
Type: article
Authors: Martínez Cano, Isabel; Muller-Landau, Helene C.; Wright, S. Joseph; Bohlman, Stephanie A.; Pacala, Stephen W.
Abstract: Tree allometric relationships are widely employed for estimating forest biomass and production and are basic building blocks of dynamic vegetation models. In tropical forests, allometric relationships are often modeled by fitting scale-invariant power functions to pooled data from multiple species, an approach that fails to capture changes in scaling during ontogeny and physical limits to maximum tree size and that ignores interspecific differences in allometry. Here, we analyzed allometric relationships of tree height (9884 individuals) and crown area (2425) with trunk diameter for 162 species from the Barro Colorado Nature Monument, Panama. We fit nonlinear, hierarchical models informed by species traits – wood density, mean sapling growth, or sapling mortality – and assessed the performance of three alternative functional forms: the scale-invariant power function and the saturating Weibull and generalized Michaelis–Menten (gMM) functions. The relationship of tree height with trunk diameter was best fit by a saturating gMM model in which variation in allometric parameters was related to interspecific differences in sapling growth rates, a measure of regeneration light demand. Light-demanding species attained taller heights at comparatively smaller diameters as juveniles and had shorter asymptotic heights at larger diameters as adults. The relationship of crown area with trunk diameter was best fit by a power function model incorporating a weak positive relationship between crown area and species-specific wood density. The use of saturating functional forms and the incorporation of functional traits in tree allometric models is a promising approach for improving estimates of forest biomass and productivity. Our results provide an improved basis for parameterizing tropical plant functional types in vegetation models.

ID: 150610
Type: article
Authors: Muller-Landau, Helene C.; Visser, Marco D.
Abstract: Lianas and other climbing plants are structural parasites of trees, generally reducing host tree survival, growth, and reproduction, yet their influences on the outcome of competition among tree species have remained largely unexplored. We propose that there are three distinct components to liana–tree interactions: prevalence, defined as the proportion of infested trees; load, defined as the mean liana cover on infested trees; and tolerance, defined as the effect of a given level of infestation on tree population growth rates. We introduce a new metric that integrates these components, the liana burden, defined as the total effect of lianas on per capita population growth rates given current prevalence, load, and tolerance. Using these metrics, we quantify variation among 33 co-occurring tropical tree species in liana–tree interactions and its relation with shade-tolerance. The focal tree species vary strongly in liana prevalence, load, tolerance, and burden. Interspecific variation in tolerance is the largest contributor to interspecific variation in burden. Species rankings of per capita population growth rates under current liana infestation levels differ somewhat from rankings under liana-free conditions, and differ strongly from rankings under uniformly high liana infestation. Thus, lianas alter competitive hierarchies to benefit tree species that are relatively tolerant of and/or resistant to lianas. Among the focal tree species, shade-tolerance is positively correlated with liana tolerance and prevalence, but largely unrelated to load and burden, meaning shade-tolerance does not predict which species are competitively disadvantaged by lianas. We describe a variety of mechanisms by which lianas may potentially increase or decrease niche differences among tree species, including interactions with spatial and temporal environmental niche partitioning, and potential differences among tree species in relative vulnerability to different liana species. Synthesis. Lianas, like other natural enemies, can in principle alter competitive hierarchies and niche structure of co-occurring tree species, and our analyses suggest such influences are substantial in our focal tropical tree community and likely many other tree communities as well. Quantifying these effects requires a more comprehensive approach including analyses and modelling of dynamics of liana–tree interactions and their variation with tree and liana species identities.

ID: 152067
Type: article
Authors: Park, John Y.; Muller-Landau, Helene C.; Lichstein, Jeremy W.; Rifai, Sami W.; Dandois, Jonathan P.; Bohlman, Stephanie A.
Abstract: Tropical forests exhibit complex but poorly understood patterns of leaf phenology. Understanding species- and individual-level phenological patterns in tropical forests requires datasets covering large numbers of trees, which can be provided by Unmanned Aerial Vehicles (UAVs). In this paper, we test a workflow combining high-resolution RGB images (7 cm/pixel) acquired from UAVs with a machine learning algorithm to monitor tree and species leaf phenology in a tropical forest in Panama. We acquired images for 34 flight dates over a 12-month period. Crown boundaries were digitized in images and linked with forest inventory data to identify species. We evaluated predictions of leaf cover from different models that included up to 14 image features extracted for each crown on each date. The models were trained and tested with visual estimates of leaf cover from 2422 images from 85 crowns belonging to eight species spanning a range of phenological patterns. The best-performing model included both standard color metrics, as well as texture metrics that quantify within-crown variation, with r2 of 0.84 and mean absolute error (MAE) of 7.8% in 10-fold cross-validation. In contrast, the model based only on the widely-used Green Chromatic Coordinate (GCC) index performed relatively poorly (r2 = 0.52, MAE = 13.6%). These results highlight the utility of texture features for image analysis of tropical forest canopies, where illumination changes may diminish the utility of color indices, such as GCC. The algorithm successfully predicted both individual-tree and species patterns, with mean r2 of 0.82 and 0.89 and mean MAE of 8.1% and 6.0% for individual- and species-level analyses, respectively. Our study is the first to develop and test methods for landscape-scale UAV monitoring of individual trees and species in diverse tropical forests. Our analyses revealed undescribed patterns of high intraspecific variation and complex leaf cover changes for some species.

ID: 150247
Type: article
Authors: Wright, S. Joseph; Calderón, Osvaldo; Muller-Landau, Helene C.
Abstract: Phenology models developed for temperate and boreal plants predict a single, population-level first flowering date for each year. These models cannot accommodate species that flower multiple times each year in humid tropical forests nor flowering data with census-interval rather than daily temporal resolution. Here, we present a new model framework able to predict the timing of multiple annual flowering events from census data. We extend a recent model, which predicted tropical flowering probabilities as discrete events occurring on census dates, by integrating predicted flowering probabilities over all dates between censuses. We evaluate our model against 29 years of daily climate and weekly flowering records for Hybanthus prunifolius (Violaceae) and Handroanthus guayacan (Bignoniaceae) from Barro Colorado Island, Panama. Previous experiments demonstrate that both species flower shortly after a heavy, dry-season rain interrupts an extended dry period. Our model captures this sequence of rainfall events. Best-fit model parameters are consistent with previous experimental results. This match suggests the new model framework will provide novel insights for other humid tropical forest species.