Mencuccini M., Manzoni S., Christoffersen B. (2019) Modelling water fluxes in plants: from tissues to biosphere. New Phytologist. : 0-0.LinkDoi: 10.1111/nph.15681
Models of plant water fluxes have evolved from studies focussed on understanding the detailed structure and functioning of specific components of the soil–plant–atmosphere (SPA) continuum to architectures often incorporated inside eco-hydrological and terrestrial biosphere (TB) model schemes. We review here the historical evolution of this field, examine the basic structure of a simplified individual-based model of plant water transport, highlight selected applications for specific ecological problems and conclude by examining outstanding issues requiring further improvements in modelling vegetation water fluxes. We particularly emphasise issues related to the scaling from tissue-level traits to individual-based predictions of water transport, the representation of nonlinear and hysteretic behaviour in soil–xylem hydraulics and the need to incorporate knowledge of hydraulics within broader frameworks of plant ecological strategies and their consequences for predicting community demography and dynamics. © 2019 The Authors. New Phytologist © 2019 New Phytologist Trust
B. Eller, C., de V. Barros, F., R.L. Bittencourt, P., Rowland, L., Mencuccini, M., S. Oliveira, R. (2018) Xylem hydraulic safety and construction costs determine tropical tree growth. Plant Cell and Environment. 41: 548-562.LinkDoi: 10.1111/pce.13106
Bruelheide H., Dengler J., Purschke O., Lenoir J., Jiménez-Alfaro B., Hennekens S.M., Botta-Dukát Z., Chytrý M., Field R., Jansen F., Kattge J., Pillar V.D., Schrodt F., Mahecha M.D., Peet R.K., Sandel B., van Bodegom P., Altman J., Alvarez-Dávila E., Arfin Khan M.A.S., Attorre F., Aubin I., Baraloto C., Barroso J.G., Bauters M., Bergmeier E., Biurrun I., Bjorkman A.D., Blonder B., Čarni A., Cayuela L., Černý T., Cornelissen J.H.C., Craven D., Dainese M., Derroire G., De Sanctis M., Díaz S., Doležal J., Farfan-Rios W., Feldpausch T.R., Fenton N.J., Garnier E., Guerin G.R., Gutiérrez A.G., Haider S., Hattab T., Henry G., Hérault B., Higuchi P., Hölzel N., Homeier J., Jentsch A., Jürgens N., Kącki Z., Karger D.N., Kessler M., Kleyer M., Knollová I., Korolyuk A.Y., Kühn I., Laughlin D.C., Lens F., Loos J., Louault F., Lyubenova M.I., Malhi Y., Marcenò C., Mencuccini M., Müller J.V., Munzinger J., Myers-Smith I.H., Neill D.A., Niinemets Ü., Orwin K.H., Ozinga W.A., Penuelas J., Pérez-Haase A., Petřík P., Phillips O.L., Pärtel M., Reich P.B., Römermann C., Rodrigues A.V., Sabatini F.M., Sardans J., Schmidt M., Seidler G., Silva Espejo J.E., Silveira M., Smyth A., Sporbert M., Svenning J.-C., Tang Z., Thomas R., Tsiripidis I., Vassilev K., Violle C., Virtanen R., Weiher E., Welk E., Wesche K., Winter M., Wirth C., Jandt U. (2018) Global trait–environment relationships of plant communities. Nature Ecology and Evolution. 2: 1906-1917.LinkDoi: 10.1038/s41559-018-0699-8
Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait–environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions. © 2018, The Author(s), under exclusive licence to Springer Nature Limited.
Eller C.B., Rowland L., Oliveira R.S., Bittencourt P.R.L., Barros F.V., Da Costa A.C.L., Meir P., Friend A.D., Mencuccini M., Sitch S., Cox P. (2018) Modelling tropical forest responses to drought and El Niño with a stomatal optimization model based on xylem hydraulics. Philosophical Transactions of the Royal Society B: Biological Sciences. 373: 0-0.LinkDoi: 10.1098/rstb.2017.0315
The current generation of dynamic global vegetation models (DGVMs) lacks a mechanistic representation of vegetation responses to soil drought, impairing their ability to accurately predict Earth system responses to future climate scenarios and climatic anomalies, such as El Niño events. We propose a simple numerical approach to model plant responses to drought coupling stomatal optimality theory and plant hydraulics that can be used in dynamic global vegetation models (DGVMs). The model is validated against stand-scale forest transpiration (E) observations from a long-term soil drought experiment and used to predict the response of three Amazonian forest sites to climatic anomalies during the twentieth century. We show that our stomatal optimization model produces realistic stomatal responses to environmental conditions and can accurately simulate how tropical forest E responds to seasonal, and even long-term soil drought. Our model predicts a stronger cumulative effect of climatic anomalies in Amazon forest sites exposed to soil drought during El Niño years than can be captured by alternative empirical drought representation schemes. The contrasting responses between our model and empirical drought factors highlight the utility of hydraulically-based stomatal optimization models to represent vegetation responses to drought and climatic anomalies in DGVMs. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’. © 2018 The Authors.
Galante M.V., Pinard M.A., Mencuccini M. (2018) Estimating Carbon Avoided from the Implementation of Reduced-Impact Logging in Sabah, Malaysia. International Forestry Review. 20: 58-78.LinkDoi: 10.1505/146554818822824192
The objective of this study was to investigate the design and application of a carbon baseline for commercial timber harvest activities involving conventional timber harvest activities (CNV), relative to reduced-impact logging (RIL) in Sabah, Malaysia. As only RIL is eligible to be practiced in production forests, a baseline of CNV was estimated from the literature. The principle of net present value was applied to the post-harvest accumulation of carbon stocks after RIL to model a conservative 'crediting' baseline. Two areas representing opposite ends of a range of anthropogenic disturbance were sampled, with an old growth lower montane forest, and a lowland severely logged-over dipterocarp forest investigated before-, and two- and three-years after harvest, respectively. Areas impacted by CNV were estimated to contain 12-39% of pre-harvest carbon stock, relative to 57-63% under RIL and estimated to accumulate carbon in the range of 0.68-1.25 tC ha-1 yr1, averaging 14-55 years for recovery; in-line with body of knowledge. While the main limitation was our inability measure CNV directly, a balance of understanding is required for the development of a 'best estimate' using the literature. © 2018 Commonwealth Forestry Association. All rights reserved.
Ledo, A., Paul, K.I., Burslem, D.F.R.P., Ewel, J.J., Barton, C., Battaglia, M., Brooksbank, K., Carter, J., Eid, T.H., England, J.R., Fitzgerald, A., Jonson, J., Mencuccini, M., Montagu, K.D., Montero, G., Mugasha, W.A., Pinkard, E., Roxburgh, S., Ryan, C.M., Ruiz-Peinado, R., Sochacki, S., Specht, A., Wildy, D., Wirth, C., Zerihun, A., Chave, J. (2018) Tree size and climatic water deficit control root to shoot ratio in individual trees globally. New Phytologist. 217: 8-11.LinkDoi: 10.1111/nph.14863
Leslie, A.D., Mencuccini, M., Perks, M.P. (2018) Preliminary growth functions for Eucalyptus gunnii in the UK. Biomass and Bioenergy. 108: 464-469.LinkDoi: 10.1016/j.biombioe.2017.10.037
Mcdowell N., Allen C.D., Anderson-Teixeira K., Brando P., Brienen R., Chambers J., Christoffersen B., Davies S., Doughty C., Duque A., Espirito-Santo F., Fisher R., Fontes C.G., Galbraith D., Goodsman D., Grossiord C., Hartmann H., Holm J., Johnson D.J., Kassim A.R., Keller M., Koven C., Kueppers L., Kumagai T., Malhi Y., Mcmahon S.M., Mencuccini M., Meir P., Moorcroft P., Muller-Landau H.C., Phillips O.L., Powell T., Sierra C.A., Sperry J., Warren J., Xu C., Xu X. (2018) Drivers and mechanisms of tree mortality in moist tropical forests. New Phytologist. : 0-0.LinkDoi: 10.1111/nph.15027
Tree mortality rates appear to be increasing in moist tropical forests (MTFs) with significant carbon cycle consequences. Here, we review the state of knowledge regarding MTF tree mortality, create a conceptual framework with testable hypotheses regarding the drivers, mechanisms and interactions that may underlie increasing MTF mortality rates, and identify the next steps for improved understanding and reduced prediction. Increasing mortality rates are associated with rising temperature and vapor pressure deficit, liana abundance, drought, wind events, fire and, possibly, CO2 fertilization-induced increases in stand thinning or acceleration of trees reaching larger, more vulnerable heights. The majority of these mortality drivers may kill trees in part through carbon starvation and hydraulic failure. The relative importance of each driver is unknown. High species diversity may buffer MTFs against large-scale mortality events, but recent and expected trends in mortality drivers give reason for concern regarding increasing mortality within MTFs. Models of tropical tree mortality are advancing the representation of hydraulics, carbon and demography, but require more empirical knowledge regarding the most common drivers and their subsequent mechanisms. We outline critical datasets and model developments required to test hypotheses regarding the underlying causes of increasing MTF mortality rates, and improve prediction of future mortality under climate change. © 2018 New Phytologist Trust.
Meir P., Mencuccini M., Binks O., Da Costa A.L., Ferreira L., Rowland L. (2018) Short-term effects of drought on tropical forest do not fully predict impacts of repeated or long-term drought: Gas exchange versus growth. Philosophical Transactions of the Royal Society B: Biological Sciences. 373: 0-0.LinkDoi: 10.1098/rstb.2017.0311
Are short-term responses by tropical rainforest to drought (e.g. during El Niño) sufficient to predict changes over the long-term, or from repeated drought? Using the world’s only long-term (16-year) drought experiment in tropical forest we examine predictability from short-term measurements (1 – 2 years). Transpiration was maximized in droughted forest: it consumed all available throughfall throughout the 16 years of study. Leaf photosynthetic capacity ðVcmax Þ was maintained, but only when averaged across tree size groups. Annual transpiration in droughted forest was less than in control, with initial reductions (at high biomass) imposed by foliar stomatal control. Tree mortality increased after year three, leading to an overall biomass loss of 40%; over the long-term, the main constraint on transpiration was thus imposed by the associated reduction in sapwood area. Altered tree mortality risk may prove predictable from soil and plant hydraulics, but additional monitoring is needed to test whether future biomass will stabilize or collapse. Allocation of assimilate differed over time: stem growth and reproductive output declined in the short-term, but following mortality-related changes in resource availability, both showed long-term resilience, with partial or full recovery. Understanding and simulation of these phenomena and related trade-offs in allocation will advance more effectively through greater use of optimization and probabilistic modelling approaches. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’. © 2018 The Authors.
Poyatos R., Sus O., Badiella L., Mencuccini M., Martínez-Vilalta J. (2018) Gap-filling a spatially explicit plant trait database: Comparing imputation methods and different levels of environmental information. Biogeosciences. 15: 2601-2617.LinkDoi: 10.5194/bg-15-2601-2018
The ubiquity of missing data in plant trait databases may hinder trait-based analyses of ecological patterns and processes. Spatially explicit datasets with information on intraspecific trait variability are rare but offer great promise in improving our understanding of functional biogeography. At the same time, they offer specific challenges in terms of data imputation. Here we compare statistical imputation approaches, using varying levels of environmental information, for five plant traits (leaf biomass to sapwood area ratio, leaf nitrogen content, maximum tree height, leaf mass per area and wood density) in a spatially explicit plant trait dataset of temperate and Mediterranean tree species (Ecological and Forest Inventory of Catalonia, IEFC, dataset for Catalonia, north-east Iberian Peninsula, 31 900 km2). We simulated gaps at different missingness levels (10-80 %) in a complete trait matrix, and we used overall trait means, species means, k nearest neighbours (kNN), ordinary and regression kriging, and multivariate imputation using chained equations (MICE) to impute missing trait values. We assessed these methods in terms of their accuracy and of their ability to preserve trait distributions, multi-trait correlation structure and bivariate trait relationships. The relatively good performance of mean and species mean imputations in terms of accuracy masked a poor representation of trait distributions and multivariate trait structure. Species identity improved MICE imputations for all traits, whereas forest structure and topography improved imputations for some traits. No method performed best consistently for the five studied traits, but, considering all traits and performance metrics, MICE informed by relevant ecological variables gave the best results. However, at higher missingness (> 30 %), species mean imputations and regression kriging tended to outperform MICE for some traits. MICE informed by relevant ecological variables allowed us to fill the gaps in the IEFC incomplete dataset (5495 plots) and quantify imputation uncertainty. Resulting spatial patterns of the studied traits in Catalan forests were broadly similar when using species means, regression kriging or the best-performing MICE application, but some important discrepancies were observed at the local level. Our results highlight the need to assess imputation quality beyond just imputation accuracy and show that including environmental information in statistical imputation approaches yields more plausible imputations in spatially explicit plant trait datasets. © 2018 Author(s).
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