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We present a representation of nitrogen and phosphorus cycling in the Functionally Assembled Terrestrial Ecosystem Simulator, a demographic vegetation model within the Energy Exascale Earth System land model. This representation is modular, and designed to allow testing of multiple hypothetical approaches for carbon-nutrient coupling in plants. Novel model hypotheses introduced in this work include, (a) the controls on plant acquisition of aqueous mineralized nutrients in the soil and (b) fairly straight forward methods of allocating nutrients to specific plant organs and their losses through live plant turnover as well as litter fluxes generated through plant mortality. This combines the new with pre-existing hypotheses (such as nitrogen fixation and soil decomposition) into a system that can accommodate plant-soil dynamics for a large number of size- and functional-type-resolved plant cohorts within a time-since-disturbance-resolved ecosystem. Root uptake of nutrients is governed by fine root biomass, and plants vary in their fine root biomass allocation in order to balance carbon and nutrient limitations to growth. We test the sensitivity of the model to a wide range of parameter variations and structural representations, and in the context of observations at Barro Colorado Island, Panama. A key model prediction is that plants in the high-light-availability canopy positions allocate more carbon to fine roots than plants in low-light understory environments, given the widely different carbon versus nutrient constraints of these two niches within a given ecosystem. This model provides a basis for exploring carbon-nutrient coupling with vegetation demography within Earth system models.

While tropical cyclone regimes are shifting with climate change, the mechanisms underpinning the resistance (ability to withstand disturbance-induced change) and resilience (capacity to return to pre-disturbance reference) of tropical forest litterfall to cyclones remain largely unexplored pantropically. Single-site studies in Australia and Hawaii suggest that litterfall on low-phosphorus (P) soils is more resistant and less resilient to cyclones. We conducted a meta-analysis to investigate the pantropical importance of total soil P in mediating forest litterfall resistance and resilience to 22 tropical cyclones. We evaluated cyclone-induced and post-cyclone litterfall mass (g/m2 /day), and P and nitrogen (N) fluxes (mg/m2 /day) and concentrations (mg/g), all indicators of ecosystem function and essential for nutrient cycling. Across 73 case studies in Australia, Guadeloupe, Hawaii, Mexico, Puerto Rico, and Taiwan, total litterfall mass flux increased from ~2.5 ± 0.3 to 22.5 ± 3 g/m2 /day due to cyclones, with large variation among studies. Litterfall P and N fluxes post-cyclone represented ~5% and 10% of the average annual fluxes, respectively. Post-cyclone leaf litterfall N and P concentrations were 21.6 ± 1.2% and 58.6 ± 2.3% higher than pre-cyclone means. Mixed-effects models determined that soil P negatively moderated the pantropical litterfall resistance to cyclones, with a 100 mg P/kg increase in soil P corresponding to a 32% to 38% decrease in resistance. Based on 33% of the resistance case studies, total litterfall mass flux reached pre-disturbance levels within one-year post-disturbance. A GAMM indicated that soil P, gale wind duration and time post-cyclone jointly moderate the short-term resilience of total litterfall, with the nature of the relationship between resilience and soil P contingent on time and wind duration. Across pantropical forests observed to date, our results indicate that litterfall resistance and resilience in the face of intensifying cyclones will be partially determined by total soil P.

Scientific communities are increasingly publishing data to evaluate, accredit, and build on published research. However, guidelines for curating data for publication are sparse for model-related research, limiting the usability of archived simulation data. In particular, there are no established guidelines for archiving data related to terrestrial models that simulate land processes and their coupled interactions with climate. Terrestrial modelers have a unique set of challenges when publishing data due to the diversity of scientific domains, research questions, and the types and scales of simulations. Researchers in the U.S. Department of Energy’s (DOE) projects use a variety of multiscale models to advance robust predictions of terrestrial and subsurface ecosystem processes. Here, we synthesize archiving needs for data associated with different DOE models, and provide guidelines for publishing terrestrial model data components following FAIR (Findable, Accessible, Interoperable, Reusable) principles. The guidelines recommend archiving model inputs and testing data used in final simulation runs along with associated codes, workflow scripts, and metadata in public repositories. Researchers should consider archiving model outputs if they are within the storage limits of the repository. We also provide considerations for how to bundle files into different data publications with citable digital object identifiers. Finally, we identify repository features and tools that would enable storage and reuse of model data. Given the diversity of DOE terrestrial models, these guidelines are transferable to other model types and will enable efficient reuse of simulation data for purposes such as model intercomparisons, initialization, benchmarking, synthesis, and comparisons with field observations.

Tropical forests take up more carbon (C) from the atmosphere per annum by photosynthesis than any other type of vegetation. Phosphorus (P) limitations to C uptake are paramount for tropical and subtropical forests around the globe. Yet the generality of photosynthesis-P relationships underlying these limitations are in question, and hence are not represented well in terrestrial biosphere models. Here we demonstrate the dependence of photosynthesis and underlying processes on both leaf N and P concentrations. The regulation of photosynthetic capacity by P was similar across four continents. Implementing P constraints in the ORCHIDEE-CNP model, gross photosynthesis was reduced by 36% across the tropics and subtropics relative to traditional N constraints and unlimiting leaf P. Our results provide a quantitative relationship for the P dependence for photosynthesis for the front-end of global terrestrial C models that is consistent with canopy leaf measurements.

Plants invest a considerable amount of leaf nitrogen in the photosynthetic enzyme ribulose-1,5-bisphosphate carboxylase-oxygenase (RuBisCO), forming a strong coupling of nitrogen and photosynthetic capacity. Variability in the nitrogen-photosynthesis relationship indicates different nitrogen use strategies of plants (i.e., the fraction nitrogen allocated to RuBisCO; fLNR), however, the reason for this remains unclear as widely different nitrogen use strategies are adopted in photosynthesis models. Here, we use a comprehensive database of in situ observations, a remote sensing product of leaf chlorophyll and ancillary climate and soil data, to examine the global distribution in fLNR using a random forest model. We find global fLNR is 18.2 ± 6.2%, with its variation largely driven by negative dependence on leaf mass per area and positive dependence on leaf phosphorus. Some climate and soil factors (i.e., light, atmospheric dryness, soil pH, and sand) have considerable positive influences on fLNR regionally. This study provides insight into the nitrogen-photosynthesis relationship of plants globally and an improved understanding of the global distribution of photosynthetic potential.

Leaf-level gas exchange data support the mechanistic understanding of plant fluxes of carbon and water. These fluxes inform our understanding of ecosystem function, are an important constraint on parameterization of terrestrial biosphere models, are necessary to understand the response of plants to global environmental change, and are integral to efforts to improve crop production. Collection of these data using gas analyzers can be both technically challenging and time consuming, and individual studies generally focus on a small range of species, restricted time periods, or limited geographic regions. The high value of these data is exemplified by the many publications that reuse and synthesize gas exchange data, however the lack of metadata and data reporting conventions make full and efficient use of these data difficult. Here we propose a reporting format for leaf-level gas exchange data and metadata to provide guidance to data contributors on how to store data in repositories to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format specifies data table variable naming and unit conventions, as well as metadata characterizing experimental conditions and protocols. For common data types that were the focus of this initial version of the reporting format, i.e., survey measurements, dark respiration, carbon dioxide and light response curves, and parameters derived from those measurements, we took a further step of defining required additional data and metadata that would maximize the potential reuse of those data types. To aid data contributors and the development of data ingest tools by data repositories we provided a translation table comparing the outputs of common gas exchange instruments. Extensive consultation with data collectors, data users, instrument manufacturers, and data scientists was undertaken in order to ensure that the reporting format met community needs. The reporting format presented here is intended to form a foundation for future development that will incorporate additional data types and variables as gas exchange systems and measurement approaches advance in the future. The reporting format is published in the U.S. Department of Energy's ESS-DIVE data repository, with documentation and future development efforts being maintained in a version control system.

Mechanistic photosynthesis models are at the heart of terrestrial biosphere models (TBMs) simulating the daily, monthly, annual and decadal rhythms of carbon assimilation (A). These models are founded on robust mathematical hypotheses that describe how A responds to changes in light and atmospheric CO2 concentration. Two predominant photosynthesis models are in common usage: Farquhar (FvCB) and Collatz (CBGB). However, a detailed quantitative comparison of these two models has never been undertaken. In this study, we unify the FvCB and CBGB models to a common parameter set and use novel multi-hypothesis methods (that account for both hypothesis and parameter variability) for process-level sensitivity analysis. These models represent three key biological processes: carboxylation, electron transport, triose phosphate use (TPU) and an additional model process: limiting-rate selection. Each of the four processes comprises 1-3 alternative hypotheses giving 12 possible individual models with a total of 14 parameters. To broaden inference, TBM simulations were run and novel, high-resolution photosynthesis measurements were made. We show that parameters associated with carboxylation are the most influential parameters but also reveal the surprising and marked dominance of the limiting-rate selection process (accounting for 57% of the variation in A vs. 22% for carboxylation). The limiting-rate selection assumption proposed by CBGB smooths the transition between limiting rates and always reduces A below the minimum of all potentially limiting rates, by up to 25%, effectively imposing a fourth limitation on A. Evaluation of the CBGB smoothing function in three TBMs demonstrated a reduction in global A by 4%-10%, equivalent to 50%-160% of current annual fossil fuel emissions. This analysis reveals a surprising and previously unquantified influence of a process that has been integral to many TBMs for decades, highlighting the value of multi-hypothesis methods.

Leaf respiration in the dark (Rdark) and light (Rday) is poorly characterized in diverse tropical ecosystems, and little to no information exists on the degree of light suppression in common tree species within the Amazon basin, and their dependences upon plant functional traits and position within the canopy. We quantified Rdark and apparent Rday using the Kok method and measured key leaf traits in 26 tree individuals of different species distributed in three different canopy positions: canopy, lower canopy, and understory. To explore the relationships between the leaf traits we used the standardized major axis (SMA). We found that canopy trees had significantly higher rates of Rdark and Rday than trees in the understory. The difference between Rdark and Rday (the light suppression of respiration) was greatest in the understory (68 ± 9%, 95% CI) and lower canopy (49 ± 9%, 95% CI) when compared to the canopy (37 ± 10%, 95% CI). We also found that Rday was significantly and strongly correlated with Rdark (p < 0.001) for all the canopy positions. Also, leaf mass per area (LMA) and leaf Phosphorus concentration (P) had a significant relationship with Rdark (p < 0.001; p = 0.003), respectively. In addition, a significant relationship was found for LMA in the canopy and lower canopy positions (p = 0.009; p = 0.048) while P was only significant in the canopy (p = 0.044). Finally, no significant relationship was found between Rdark and nitrogen, sugars, and starch. Our results highlight the importance of including representation of the light suppression of leaf respiration in terrestrial biosphere models and also of accounting for vertical gradients within forest canopies and connections with functional traits.

Tropical forests absorb large amounts of atmospheric CO2 through photosynthesis, but high surface temperatures suppress this absorption while promoting isoprene emissions. While mechanistic isoprene emission models predict a tight coupling to photosynthetic electron transport (ETR) as a function of temperature, direct field observations of this phenomenon are lacking in the tropics and are necessary to assess the impact of a warming climate on global isoprene emissions. Here we demonstrate that in the early successional species Vismia guianensis in the central Amazon, ETR rates increased with temperature in concert with isoprene emissions, even as stomatal conductance (gs ) and net photosynthetic carbon fixation (Pn ) declined. We observed the highest temperatures of continually increasing isoprene emissions yet reported (50°C). While Pn showed an optimum value of 32.6 ± 0.4°C, isoprene emissions, ETR, and the oxidation state of PSII reaction centers (qL ) increased with leaf temperature with strong linear correlations for ETR (ƿ = 0.98) and qL (ƿ = 0.99) with leaf isoprene emissions. In contrast, other photoprotective mechanisms, such as non-photochemical quenching, were not activated at elevated temperatures. Inhibition of isoprenoid biosynthesis repressed Pn at high temperatures through a mechanism that was independent of stomatal closure. While extreme warming will decrease gs and Pn in tropical species, our observations support a thermal tolerance mechanism where the maintenance of high photosynthetic capacity under extreme warming is assisted by the simultaneous stimulation of ETR and metabolic pathways that consume the direct products of ETR including photorespiration and the biosynthesis of thermoprotective isoprenoids. Our results confirm that models which link isoprene emissions to the rate of ETR hold true in tropical species and provide necessary "ground-truthing" for simulations of the large predicted increases in tropical isoprene emissions with climate warming.

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 singlePFT 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.

Global terrestrial models currently predict that the Amazon rainforest will continue to act as a carbon sink in the future, primarily owing to the rising atmospheric carbon dioxide (CO2) concentration. Soil phosphorus impoverishment in parts of the Amazon basin largely controls its functioning, but the role of phosphorus availability has not been considered in global model ensembles—for example, during the Fifth Climate Model Intercomparison Project. Here we simulate the planned free-air CO2 enrichment experiment AmazonFACE with an ensemble of 14 terrestrial ecosystem models. We show that phosphorus availability reduces the projected CO2-induced biomass carbon growth by about 50% to 79 ± 63 g C m−2 yr−1 over 15 years compared to estimates from carbon and carbon–nitrogen models. Our results suggest that the resilience of the region to climate change may be much less than previously assumed. Variation in the biomass carbon response among the phosphorus-enabled models is considerable, ranging from 5 to 140 g C m−2 yr−1, owing to the contrasting plant phosphorus use and acquisition strategies considered among the models. The Amazon forest response thus depends on the interactions and relative contributions of the phosphorus acquisition and use strategies across individuals, and to what extent these processes can be upregulated under elevated CO2.

Increasing atmospheric CO2 stimulates photosynthesis which can increase net primary production (NPP), but at longer timescales may not necessarily increase plant biomass. Here we analyse the four decade-long CO2-enrichment experiments in woody ecosystems that measured total NPP and biomass. CO2 enrichment increased biomass increment by 1.05 ± 0.26 kg C m-2 over a full decade, a 29.1 ± 11.7% stimulation of biomass gain in these early-secondary-succession temperate ecosystems. This response is predictable by combining the CO2 response of NPP (0.16 ± 0.03 kg C m-2 y-1) and the CO2-independent, linear slope between biomass increment and cumulative NPP (0.55 ± 0.17). An ensemble of terrestrial ecosystem models fail to predict both terms correctly. Allocation to wood was a driver of across-site, and across-model, response variability and together with CO2-independence of biomass retention highlights the value of understanding drivers of wood allocation under ambient conditions to correctly interpret and predict CO2 responses.

Vegetation plays an important role in regulating global carbon cycles and is a key component of the Earth system models (ESMs) that aim to project Earth's future climate. In the last decade, the vegetation component within ESMs has witnessed great progress from simple "big-leaf" approaches to demographically structured approaches, which have a better representation of plant size, canopy structure, and disturbances. These demographically structured vegetation models typically have a large number of input parameters, and sensitivity analysis is needed to quantify the impact of each parameter on the model outputs for a better understanding of model behavior. In this study, we conducted a comprehensive sensitivity analysis to diagnose the Community Land Model coupled to the Functionally Assembled Terrestrial Simulator, or CLM4.5(FATES). Specifically, we quantified the first- and second-order sensitivities of the model parameters to outputs that represent simulated growth and mortality as well as carbon fluxes and stocks for a tropical site with an extent of 1×1°. While the photosynthetic capacity parameter (Vc;max25) is found to be important for simulated carbon stocks and fluxes, we also show the importance of carbon storage and allometry parameters, which determine survival and growth strategies within the model. The parameter sensitivity changes with different sizes of trees and climate conditions. The results of this study highlight the importance of understanding the dynamics of the next generation of demographically enabled vegetation models within ESMs to improve model parameterization and structure for better model fidelity.

Evaluating the response of the land carbon sink to the anomalies in temperature and drought imposed by El Niño events provides insights into the present-day carbon cycle and its climate-driven variability. It is also a necessary step to build confidence in terrestrial ecosystems models' response to the warming and drying stresses expected in the future over many continents, and particularly in the tropics. Here we present an in-depth analysis of the response of the terrestrial carbon cycle to the 2015/2016 El Niño that imposed extreme warming and dry conditions in the tropics and other sensitive regions. First, we provide a synthesis of the spatio-temporal evolution of anomalies in net land-atmosphere CO2 fluxes estimated by two in situ measurements based on atmospheric inversions and 16 land-surface models (LSMs) from TRENDYv6. Simulated changes in ecosystem productivity, decomposition rates and fire emissions are also investigated. Inversions and LSMs generally agree on the decrease and subsequent recovery of the land sink in response to the onset, peak and demise of El Niño conditions and point to the decreased strength of the land carbon sink: by 0.4-0.7 PgC yr-1 (inversions) and by 1.0 PgC yr-1 (LSMs) during 2015/2016. LSM simulations indicate that a decrease in productivity, rather than increase in respiration, dominated the net biome productivity anomalies in response to ENSO throughout the tropics, mainly associated with prolonged drought conditions.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'.

The maximum photosynthetic carboxylation rate (Vcmax ) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global Vcmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr-1 , 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated through to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated (r = 0.85-0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand Vcmax variation in the field, particularly in northern latitudes.

Peatlands harbour more than one-third of terrestrial carbon leading to the argument that the bryophytes, as major components of peatland ecosystems, store more organic carbon in soils than any other collective plant taxa. Plants of the genus Sphagnum are important components of peatland ecosystems and are potentially vulnerable to changing climatic conditions. However, the response of Sphagnum to rising temperatures, elevated CO2 and shifts in local hydrology have yet to be fully characterized. In this review, we examine Sphagnum biology and ecology and explore the role of this group of keystone species and its associated microbiome in carbon and nitrogen cycling using literature review and model simulations. Several issues are highlighted including the consequences of a variable environment on plant-microbiome interactions, uncertainty associated with CO2 diffusion resistances and the relationship between fixed N and that partitioned to the photosynthetic apparatus. We note that the Sphagnum fallax genome is currently being sequenced and outline potential applications of population-level genomics and corresponding plant photosynthesis and microbial metabolic modelling techniques. We highlight Sphagnum as a model organism to explore ecosystem response to a changing climate and to define the role that Sphagnum can play at the intersection of physiology, genetics and functional genomics.

The purpose of the present study was to determine the reliability of a 5km run test on a motorized treadmill. Over three consecutive weeks, 12 well-trained runners completed three 5km time trials on a treadmill following a standardized warm-up. Runners were partially-blinded to their running speed and distance covered. Total time to complete the run was recorded for analysis of reliability. The highest intraclass correlation coefficient between trials for 5km time trial (TT) time was 0.99 (90% confidence intervals [CI]; 0.96-1.00, "very high"), which occurred between trials 2 and 3. The lowest typical error of measurement (expressed as a coefficient of variation percentage [CV%] and as an absolute value in seconds) also occurred between trials 2 and 3, and was 1.0% and 10.9 seconds, respectively. The testing protocol performed on a motorized treadmill in the current study is reproducible in well-trained runners following a single trial, making it a reliable method for monitoring running performance.

Detailed modeling of the combustion of real transportation fuels and the atmospheric reactions involving their emissions is prohibitively expensive, due to the large size and stiffness of the chemical kinetic models. Adaptive preconditioning is a method used to reduce the cost of integrating large kinetic models by forming a preconditioner based on a semi-analytical Jacobian matrix, paired with sparse linear algebra procedures. In this study, we extend this preconditioning method to a more-general mole-based state vector formulation applicable to generic reactor types and combinations. We tested the scheme using constant-pressure and constant-volume ideal-gas reactor simulations, showing speedup in performance from a factor of 3 up to nearly 4000 times for chemical kinetic models with 10 to 7171 species, in comparison with typical dense solvers. The method also improves performance by a factor of 1.06 to 21.1, for models larger than 200 species, in comparison with a fully exact, analytical Jacobian used as the preconditioner. Overall, this method improves performance by up to three orders of magnitude for large kinetic models, and offers benefits for models with as few as 10 species. [ABSTRACT FROM AUTHOR]

Access to higher education continues to expand in the United States. And, as opportunity has continued to increase, so too has the amount of diversity present throughout higher education. These trends, combined with the fundamental principles connected to the purpose of higher education, work to create culturally relevant and responsive practice. Focused on educational practice designed to meet the needs of a continuously diversifying student population, this chapter examines student programming and curricula as a means to promote student success and learning.

Dewey (1916) described the attainment of education as a necessary tool for the establishment and sustainability of progress. Education, attending to the good of the public, is designed to instill knowledge in the constituencies it serves (Kezar 2005). Further, Woods (2004) described the design of education, its services and responsibilities, as an enterprise that promotes ethical, active engagement and respect for everyone. However, disconnects between theory and practice exist as education in the United States functions to empower some while marginalizing and oppressing others. This chapter, through a critical lens, will juxtapose ideals of equality and equity to discuss how integrating criticality and identity development into educational praxis will assist in creating inclusive, equitable practice prepared to meet the needs of learners from low socioeconomic backgrounds.

Summary: Terrestrial biosphere models (TBMs) include the representation of vertical gradients in leaf traits associated with modeling photosynthesis, respiration, and stomatal conductance. However, model assumptions associated with these gradients have not been tested in complex tropical forest canopies.We compared TBM representation of the vertical gradients of key leaf traits with measurements made in a tropical forest in Panama and then quantified the impact of the observed gradients on simulated canopy‐scale CO2 and water fluxes.Comparison between observed and TBM trait gradients showed divergence that impacted canopy‐scale simulations of water vapor and CO2 exchange. Notably, the ratio between the dark respiration rate and the maximum carboxylation rate was lower near the ground than at the top‐of‐canopy, leaf‐level water‐use efficiency was markedly higher at the top‐of‐canopy, and the decrease in maximum carboxylation rate from the top‐of‐canopy to the ground was less than TBM assumptions.The representation of the gradients of leaf traits in TBMs is typically derived from measurements made within‐individual plants, or, for some traits, assumed constant due to a lack of experimental data. Our work shows that these assumptions are not representative of the trait gradients observed in species‐rich, complex tropical forests. [ABSTRACT FROM AUTHOR]

The concept of sacrifice was formerly a key variable in theorizing about religion and society. Secularization theory and conceptual models equating sacrifice with cost have reduced its usage and apparent relevance, although it continues to be of interest in anthropology and religious studies. Research on sacrifice has been neglected in the social sciences, especially in studies of religiosity and families. Seventy-seven religious adolescents in 55 religious Jewish, Christian, Muslim, and Mormon families in New England and northern California were interviewed about whether they felt they had been asked to make sacrifices for their faith as they were growing up. This article discusses how contemporary religious youth view the sacrifices they make for religious reasons. Adolescents reported sacrifices in five domains: societal expectations, popular culture, comforts and pleasures, time and activities, and peer relations. Youth gave the following reasons for being willing to make sacrifices: connecting to a higher meaning or purpose, connecting to God, connecting to the faith tradition or community, fulfilling expectations, feeling affective benefits, and avoiding problems.