Precipitation mediates sap flux sensitivity to evaporative demand in the neotropics

Transpiration in humid tropical forests modulates the global water cycle and is a key driver of climate regulation. Yet, our understanding of how tropical trees regulate sap flux in response to climate variability remains elusive. With a progressively warming climate, atmospheric evaporative demand [i.e., vapor pressure deficit (VPD)] will be increasingly important for plant functioning, becoming the major control of plant water use in the twenty-first century. Using measurements in 34 tree species at seven sites across a precipitation gradient in the neotropics, we determined how the maximum sap flux velocity (vmax) and the VPD threshold at which vmax is reached (VPDmax) vary with precipitation regime [mean annual precipitation (MAP); seasonal drought intensity (PDRY)] and two functional traits related to foliar and wood economics spectra [leaf mass per area (LMA); wood specific gravity (WSG)]. We show that, even though vmax is highly variable within sites, it follows a negative trend in response to increasing MAP and PDRY across sites. LMA and WSG exerted little effect on vmax and VPDmax, suggesting that these widely used functional traits provide limited explanatory power of dynamic plant responses to environmental variation within hyper-diverse forests. This study demonstrates that long-term precipitation plays an important role in the sap flux response of humid tropical forests to VPD. Our findings suggest that under higher evaporative demand, trees growing in wetter environments in humid tropical regions may be subjected to reduced water exchange with the atmosphere relative to trees growing in drier climates

Drivers and mechanisms of tree mortality in moist tropical forests

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

Global transpiration data from sap flow measurements: the SAPFLUXNET database

Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land–atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80 % of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50 % of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56 % of the datasets. Many datasets contain data for species that make up 90 % or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes. SAPFLUXNET version 0.1.5 is freely available from the Zenodo repository (https://doi.org/10.5281/zenodo.3971689; Poyatos et al., 2020a). The “sapfluxnetr” R package – designed to access, visualize, and process SAPFLUXNET data – is available from CRAN.EEA Santa CruzFil: Poyatos, Rafael. Universitat Autònoma de Barcelona. Bellaterra (Cerdanyola del Vallès); EspañaFil: Poyatos, Rafael. CREAF. Bellaterra (Cerdanyola del Vallès); EspañaFil: Granda, Víctor. Universitat Autònoma de Barcelona. Bellaterra (Cerdanyola del Vallès); EspañaFil: Granda, Víctor. Joint Research Unit CREAF-CTFC. Bellaterra; EspañaFil: Flo, Víctor. Universitat Autònoma de Barcelona. Bellaterra (Cerdanyola del Vallès); EspañaFil: Adams, Mark A. Swinburne University of Technology. Faculty of Science Engineering and Technology; Australia.Fil: Adams, Mark A. University of Sydney. School of Life and Environmental Sciences; Australia.Fil: Adorján, Balázs. University of Debrecen. Faculty of Science and Technology. Department of Botany; HungríaFil: Aguadé, David. Universitat Autònoma de Barcelona. Bellaterra (Cerdanyola del Vallès); EspañaFil: Aidar, Marcos P. M. Institute of Botany. Plant Physiology and Biochemistry; BrasilFil: Allen, Scott. University of Nevada. Department of Natural Resources and Environmental Science; Estados UnidosFil: Alvarado-Barrientos, M. Susana. Instituto de Ecología A.C. Red Ecología Funcional; México.Fil: Anderson-Teixeira, Kristina J. Center for Tropical Forest Science-Forest Global Earth Observatory, Smithsonian Tropical Research Institute; PanamáFil: Anderson-Teixeira, Kristina J. Conservation Ecology Center. Smithsonian Conservation Biology Institute; Estados UnidosFil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Martínez-Vilalta, Jordi. CREAF. Bellaterra (Cerdanyola del Vallès); EspañaFil: Martínez-Vilalta, Jordi. Universitat Autònoma de Barcelona. Bellaterra (Cerdanyola del Vallès); Españ

Implementing GitHub Actions Continuous Integration to Reduce Error Rates in Ecological Data Collection

Accurate field data are essential to understanding ecological systems and forecasting their responses to global change. Yet, data collection errors are common, and data analysis often lags far enough behind its collection that many errors can no longer be corrected, nor can anomalous observations be revisited. Needed is a system in which data quality assurance and control (QA/QC), along with the production of basic data summaries, can be automated immediately following data collection. Here, we implement and test a system to satisfy these needs. For two annual tree mortality censuses and a dendrometer band survey at two forest research sites, we used GitHub Actions continuous integration (CI) to automate data QA/QC and run routine data wrangling scripts to produce cleaned datasets ready for analysis. This system automation had numerous benefits, including (1) the production of near real-time information on data collection status and errors requiring correction, resulting in final datasets free of detectable errors, (2) an apparent learning effect among field technicians, wherein original error rates in field data collection declined significantly following implementation of the system, and (3) an assurance of computational reproducibility—that is, robustness of the system to changes in code, data and software. By implementing CI, researchers can ensure that datasets are free of any errors for which a test can be coded. The result is dramatically improved data quality, increased skill among field technicians, and reduced need for expert oversight. Furthermore, we view CI implementation as a first step towards a data collection and analysis pipeline that is also more responsive to rapidly changing ecological dynamics, making it better suited to study ecological systems in the current era of rapid environmental change

Spatial covariance of herbivorous and predatory guilds of forest canopy arthropods along a latitudinal gradient

In arthropod community ecology, species richness studies tend to be prioritised over those investigating patterns of abundance. Consequently, the biotic and abiotic drivers of arboreal arthropod abundance are still relatively poorly known. In this cross-continental study, we employ a theoretical framework in order to examine patterns of covariance among herbivorous and predatory arthropod guilds. Leaf-chewing and leaf-mining herbivores, and predatory ants and spiders, were censused on > 1000 trees in nine 0.1 ha forest plots. After controlling for tree size and season, we found no negative pairwise correlations between guild abundances per plot, suggestive of weak signals of both inter-guild competition and top-down regulation of herbivores by predators. Inter-guild interaction strengths did not vary with mean annual temperature, thus opposing the hypothesis that biotic interactions intensify towards the equator. We find evidence for the bottom-up limitation of arthropod abundances via resources and abiotic factors, rather than for competition and predation.publishedVersio

allodb: An R package for biomass estimation at globally distributed extratropical forest plots

Allometric equations for calculation of tree above-ground biomass (AGB) form the basis for estimates of forest carbon storage and exchange with the atmosphere. While standard models exist to calculate forest biomass across the tropics, we lack a standardized tool for computing AGB across boreal and temperate regions that comprise the global extratropics. Here we present an integrated R package, allodb, containing systematically selected published allometric equations and proposed functions to compute AGB. The data component of the package is based on 701 woody species identified at 24 large Forest Global Earth Observatory (ForestGEO) forest dynamics plots representing a wide diversity of extratropical forests. A total of 570 parsed allometric equations to estimate individual tree biomass were retrieved, checked and combined using a weighting function designed to ensure optimal equation selection over the full tree size range with smooth transitions across equations. The equation dataset can be customized with built-in functions that subset the original dataset and add new equations. Although equations were curated based on a limited set of forest communities and number of species, this resource is appropriate for large portions of the global extratropics and can easily be expanded to cover novel forest types

Global transpiration data from sap flow measurements: the SAPFLUXNET database

Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land?atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80 % of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50 % of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets,while on-site soil water content is available for 56 % of the datasets. Many datasets contain data for species that make up 90 % or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes.Fil: Poyatos, Rafael. Universitat Autònoma de Barcelona; EspañaFil: Granda, Víctor. Universitat Autònoma de Barcelona; EspañaFil: Flo, Víctor. Universitat Autònoma de Barcelona; EspañaFil: Adams, Mark A.. Swinburne University of Technology; Australia. University of Sydney; AustraliaFil: Adorján, Balázs. University of Debrecen; HungríaFil: Aguadé, David. Universitat Autònoma de Barcelona; EspañaFil: Aidar, Marcos P. M.. Institute of Botany; BrasilFil: Allen, Scott. University of Nevada; Estados UnidosFil: Alvarado Barrientos, M. Susana. Instituto de Ecología A.C.; MéxicoFil: Anderson Teixeira, Kristina J.. Smithsonian Tropical Research Institute; PanamáFil: Aparecido, Luiza Maria. Arizona State University; Estados Unidos. Texas A&M University; Estados UnidosFil: Arain, M. Altaf. McMaster University; CanadáFil: Aranda, Ismael. National Institute for Agricultural and Food Research and Technology; EspañaFil: Asbjornsen, Heidi. University of New Hampshire; Estados UnidosFil: Robert Baxter. Durham University; Reino UnidoFil: Beamesderfer, Eric. McMaster University; Canadá. Northern Arizona University; Estados UnidosFil: Carter Berry, Z.. Chapman University; Estados UnidosFil: Berveiller, Daniel. Université Paris Saclay; Francia. Centre National de la Recherche Scientifique; FranciaFil: Blakely, Bethany. University of Illinois at Urbana-Champaign; Estados UnidosFil: Boggs, Johnny. United States Forest Service; Estados UnidosFil: Gil Bohrer. Ohio State University; Estados UnidosFil: Bolstad, Paul V.. University of Minnesota; Estados UnidosFil: Bonal, Damien. Université de Lorraine; FranciaFil: Bracho, Rosvel. University of Florida; Estados UnidosFil: Brito, Patricia. Universidad de La Laguna; EspañaFil: Brodeur, Jason. McMaster University; CanadáFil: Casanoves, Fernando. Centro Agronómico Tropical de Investigación y Enseñanza; Costa RicaFil: Chave, Jérôme. Université Paul Sabatier; FranciaFil: Chen, Hui. Xiamen University; ChinaFil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia de Santa Cruz. Universidad Tecnológica Nacional. Facultad Regional Santa Cruz. Centro de Investigaciones y Transferencia de Santa Cruz. Universidad Nacional de la Patagonia Austral. Centro de Investigaciones y Transferencia de Santa Cruz; Argentin