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{"Abstract":["Premise: Extreme events are an understudied aspect of ongoing\n anthropogenic climate change that could play a disproportionate role in\n the threat that rapid environmental shifts pose to natural populations.\n Methods: We exposed plants originating from seeds that were harvested\n before (ancestors) and after (descendants) multiple extreme heat events\n from six populations across the range of Mimulus cardinalis (Phyrmaceae)\n to a short‐term heat‐wave treatment in controlled growth chamber\n environments. We assessed physiological, performance, and functional\n responses (stomatal conductance, leaf temperature deficit, photosystem II\n efficiency, relative growth rate, specific leaf area, and leaf dry matter\n content) to the heat‐wave treatment, along with evolutionary responses\n (differences between ancestors and descendants) of M. cardinalis\n populations to the recent natural extreme heat event. Results: Plants in\n the heat‐wave treatment increased their overall performance, and the\n magnitude of increase was generally greatest among trailing‐edge\n populations. Despite limited overall trait differences between ancestors\n and descendants, there was some evidence of divergent evolutionary\n responses among regions to the natural extreme heat event. However, we did\n not find evidence of adaptive evolution that affected how M. cardinalis\n populations responded to the heat‐wave treatment. Conclusions: These\n results demonstrate that many M. cardinalis populations may reside in\n environments that are below their optimum average temperature, revealing\n potential resiliency to future warming. However, limited evolutionary\n responses in M. cardinalis to the recent extreme heat wave could still\n indicate potential for future vulnerability to extreme climate events of\n increased intensity, frequency, and duration."],"TechnicalInfo":["Readme file associated with the paper Albano et al., American Journal of\n Botany (accepted October 20, 2025, to be published in February, 2026).\n Title: Range-wide responses to an extreme heat event in Mimulus cardinalis\n In this paper, we perform a resurrection experiment, exposing Mimulus\n cardinalis to a heat-wave treatment in growth chamber environments. M.\n cardinalis individuals were sourced from six populations across its range\n (two leading-edge, two range-center, two trailing-edge) and within each\n population, seeds were harvested in 2010 (ancestors) and 2017\n (descendants) which were time periods selected before and after a natural\n multi-year heat-wave event in western North America. This design allows\n for investigation of physiological, performance, and functional trait\n responses to the heat-wave treatment for each population, along with\n investigation of evolutionary responses to the natural heat-wave event\n that could affect how plants respond to the heat-wave treatment. This\n experiment addressed two main objectives: (1) quantify responses in plant\n physiological, performance, and functional traits to a heat-wave treatment\n and determine if those responses varied among populations from across the\n range of M. cardinalis, and (2) characterize differences in response to a\n heat-wave treatment between 2010 ancestors and 2017 descendants,\n indicative of an evolutionary response to the recent heat and drought\n event experienced by natural M. cardinalis populations. The script to\n analyze the data required to address these objectives can be found in\n Albano_et_al_2026_AJB_Script.R, while the data itself can be found in\n Albano_et_al_2026_AJB_Data.csv, which contains the following columns: *\n Cohort: The category of year at which an individual was harvested.\n Ancestor (2010) or Descendant (2017) * Region: The region from which an\n individual was harvested, essentially a combination of two populations\n from each region. N (leading-edge), C (range-center), or S (trailing-edge)\n * Heat: The heat-wave treatment performed on each individual. Control or\n Heat wave * Cross_ID: The cross identifier used to separate individuals\n based on their parentage through the creation of a refresher generation\n prior to the initiation of the experiment * Time1: A unitless scaled\n measure of time of day, constructed by combining individual hour, minute,\n and second variables. * Time2: The Time1 variable converted to a factor\n variable (necessary for autocorrelation models) * Date: The date on which\n physiological traits (gsw, Tdiff, and PhiPS2) were measured for each\n individual. Format: MM/DD/YYYY * Population: The population from which an\n individual was harvested. N1 (leading-edge population #1), N2\n (leading-edge 2), C1 (range-center 1), C2 (range-center 2), S1\n (trailing-edge 1), or S2 (trailing-edge 2) * gsw: Stomatal conductance (of\n water vapor) measurement from one leaf of each individual plant. Units:\n mmol m^-2 s^-1 * gsw_Pred: Predicted stomatal conductance (of water vapor)\n measurement from each control individual if it was to be exposed to the\n heat-wave treatment, based solely on the physical effects of temperature\n increase. Units: mmol m^-2 s^-1 * Tdiff: Leaf temperature at the moment\n gsw was assessed minus air temperature in the growth chamber. Units: °C *\n PhiPS2: Unitless photosystem II efficiency (ΦPSII) for each individual\n plant * leaf_RGR: The relative growth rate of each individual plant, based\n on the number of leaves present prior to and after the experiment. Units:\n leaves leaves^-1 day^-1 * SLA: The specific leaf area of one leaf on each\n individual plant. Units: cm^2 g^-1 * LDMC: The leaf dry matter content of\n one leaf on each individual plant. Units: mg g^-1 *NA values in the\n leaf_RGR, SLA, and LDMC columns represent individuals that were too small\n and/or unhealthy for this data to be collected. \\**All heat-wave plants\n ("Heat wave" in the "Heat" column) are recorded as NA\n in the gsw_Pred column because the predicted stomatal conductance increase\n measurement only applies to "Control" plants"]} 

Abstract PremiseThe adaptive significance of amphistomy (stomata on both upper and lower leaf surfaces) is unresolved. A widespread association between amphistomy and open, sunny habitats suggests the adaptive benefit of amphistomy may be greatest in these contexts, but this hypothesis has not been tested experimentally. Understanding amphistomy informs its potential as a target for crop improvement and paleoenvironment reconstruction. MethodsWe developed a method to quantify “amphistomy advantage” () as the log‐ratio of photosynthesis in an amphistomatous leaf to that of the same leaf but with gas exchange blocked through the upper surface (pseudohypostomy). Humidity modulated stomatal conductance and thus enabled comparing photosynthesis at the same total stomatal conductance. We estimated and leaf traits in six coastal (open, sunny) and six montane (closed, shaded) populations of the indigenous Hawaiian species ʻilima (Sida fallax). ResultsCoastal ʻilima leaves benefit 4.04 times more from amphistomy than montane leaves. Evidence was equivocal with respect to two hypotheses: (1) that coastal leaves benefit more because they are thicker and have lower CO₂conductance through the internal airspace and (2) that they benefit more because they have similar conductance on each surface, as opposed to most conductance being through the lower surface. ConclusionsThis is the first direct experimental evidence that amphistomy increases photosynthesis, consistent with the hypothesis that parallel pathways through upper and lower mesophyll increase CO₂supply to chloroplasts. The prevalence of amphistomatous leaves in open, sunny habitats can partially be explained by the increased benefit of amphistomy in “sun” leaves, but the mechanistic basis remains uncertain. 

Abstract PremiseExtreme events are an understudied aspect of ongoing anthropogenic climate change that could play a disproportionate role in the threat that rapid environmental shifts pose to natural populations. MethodsWe exposed plants originating from seeds that were harvested before (ancestors) and after (descendants) multiple extreme heat events from six populations across the range ofMimulus cardinalis(Phyrmaceae) to a short‐term heat‐wave treatment in controlled growth chamber environments. We assessed physiological, performance, and functional responses (stomatal conductance, leaf temperature deficit, photosystem II efficiency, relative growth rate, specific leaf area, and leaf dry matter content) to the heat‐wave treatment, along with evolutionary responses (differences between ancestors and descendants) ofM. cardinalispopulations to the recent natural extreme heat event. ResultsPlants in the heat‐wave treatment increased their overall performance, and the magnitude of increase was generally greatest among trailing‐edge populations. Despite limited overall trait differences between ancestors and descendants, there was some evidence of divergent evolutionary responses among regions to the natural extreme heat event. However, we did not find evidence of adaptive evolution that affected howM. cardinalispopulations responded to the heat‐wave treatment. ConclusionsThese results demonstrate that manyM. cardinalispopulations may reside in environments that are below their optimum average temperature, revealing potential resiliency to future warming. However, limited evolutionary responses inM. cardinalisto the recent extreme heat wave could still indicate potential for future vulnerability to extreme climate events of increased intensity, frequency, and duration. 

Abstract Photosynthesis is co-limited by multiple factors depending on the plant and its environment. These include biochemical rate limitations, internal and external water potentials, temperature, irradiance and carbon dioxide ( CO2). Amphistomatous leaves have stomata on both abaxial and adaxial leaf surfaces. This feature is considered an adaptation to alleviate CO2 diffusion limitations in productive environments as the diffusion path length from stomate to chloroplast is effectively halved in amphistomatous leaves. Plants may also reduce CO2 limitations through other aspects of optimal stomatal anatomy: stomatal density, distribution, patterning and size. Some studies have demonstrated that stomata are overdispersed compared to a random distribution on a single leaf surface; however, despite their prevalence in nature and near ubiquity among crop species, much less is known about stomatal anatomy in amphistomatous leaves, especially the coordination between leaf surfaces. Here, we use novel spatial statistics based on simulations and photosynthesis modelling to test hypotheses about how amphistomatous plants may optimize CO2 diffusion in the model angiosperm Arabidopsis thaliana grown in different light environments. We find that (i) stomata are overdispersed, but not ideally dispersed, on both leaf surfaces across all light treatments; (ii) the patterning of stomata on abaxial and adaxial leaf surfaces is independent and (iii) the theoretical improvements to photosynthesis from abaxial–adaxial stomatal coordination are miniscule (≪1%) across the range of feasible parameter space. However, we also find that (iv) stomatal size is correlated with the mesophyll volume that it supplies with CO2, suggesting that plants may optimize CO2 diffusion limitations through alternative pathways other than ideal, uniform stomatal spacing. We discuss the developmental, physical and evolutionary constraints that may prohibit plants from reaching this theoretical adaptive peak of uniform stomatal spacing and inter-surface stomatal coordination. These findings contribute to our understanding of variation in the anatomy of amphistomatous leaves. 

Summary A prevailing hypothesis posits that achieving higher maximum rates of leaf carbon gain and water loss is constrained by geometry and/or selection to limit the allocation of epidermal area to stomata (f_S). Under this ‘stomatal‐area minimization hypothesis’, higherg_s,maxis associated with greater numbers of smaller stomata because this trait combination increasesg_s,maxwith minimal increase inf_S, leading to relative conservation off_Ssemi‐independent ofg_s,maxdue to coordination in stomatal size, density, and pore depth. An alternative hypothesis is that the evolution of higherg_s,maxcan be enabled by a greater epidermal area allocated to stomata, leading to positive covariation betweenf_Sandg_s,max; we call this the ‘stomatal‐area adaptation hypothesis’. Under this hypothesis, the interspecific scaling betweeng_s,max, stomatal density, and stomatal size is a by‐product of selection on a moving optimalg_s,max.We integrated biophysical and evolutionary quantitative genetic modeling with phylogenetic comparative analyses of a global data set of stomatal density and size from 2408 vascular forest species. The models present specific assumptions of both hypotheses and deduce predictions that can be evaluated with our empirical analyses of forest plants.There are three main results. First, neither the stomatal‐area minimization nor adaptation hypothesis is sufficient to be supported. Second, estimates of interspecific scaling from common regression methods cannot reliably distinguish between hypotheses when stomatal size is bounded. Third, we reconcile both hypotheses with the data by including an additional assumption that stomatal size is bounded by a wide range and under selection; we refer to this synthetic hypothesis as the ‘stomatal adaptation + bounded size’ hypothesis.This study advances our understanding of scaling between stomatal size and density by mathematically describing specific assumptions of competing hypotheses, demonstrating that existing hypotheses are inconsistent with observations, and reconciling these hypotheses with phylogenetic comparative analyses by postulating a synthetic model of selection ong_s,max,f_S, and stomatal size. 

Abstract Plant ecophysiology is founded on a rich body of physical and chemical theory, but it is challenging to connect theory with data in unambiguous, analytically rigorous and reproducible ways. Custom scripts written in computer programming languages (coding) enable plant ecophysiologists to model plant processes and fit models to data reproducibly using advanced statistical techniques. Since many ecophysiologists lack formal programming education, we have yet to adopt a unified set of coding principles and standards that could make coding easier to learn, use and modify. We identify eight principles to help in plant ecophysiologists without much programming experience to write resilient code: (i) standardized nomenclature, (ii) consistency in style, (iii) increased modularity/extensibility for easier editing and understanding, (iv) code scalability for application to large data sets, (v) documented contingencies for code maintenance, (vi) documentation to facilitate user understanding; (vii) extensive tutorials and (viii) unit testing and benchmarking. We illustrate these principles using a new R package, {photosynthesis}, which provides a set of analytical and simulation tools for plant ecophysiology. Our goal with these principles is to advance scientific discovery in plant ecophysiology by making it easier to use code for simulation and data analysis, reproduce results and rapidly incorporate new biological understanding and analytical tools.