Biology subjects

Stinziano, J. R.

Publications and source records attributed to Stinziano, J. R..

8 recordsLinked to original sources

bioRxiv2026

Quantitative horizon scanning identifies high-priority wood-boring beetle pests for regulatory review in Canada

Invasive wood-boring beetles are a significant threat to forests, imposing high economic and environmental costs. With their high global biodiversity, it is difficult to assess all wood-boring beetles potential to invade a particular region. Horizon scanning can create short-lists of high priority pests for risk assessment by National Plant Protection Organizations; however, it is often resource-intensive, creating potential blind spots due to resource constraints. Here, we use a multi-layered horizon scan, including self-organizing maps and climate suitability modelling combined with rapid risk assessment, to produce a short-list of wood-boring beetles for regulatory review in Canada. This method relies on open-source data and could be applicable to any country. From an initial list of 10,824 species with available georeferenced observations, our method yielded a short-list of 24 species. The method led to the regulation of two additional wood-boring beetles in Canada, demonstrating its real-world applicability in accelerating the regulation of quarantine pests. Several already-regulated species were also identified, suggesting consistency with existing risk identification and assessment procedures. The limitations on the method are the availability of biologically meaningful species occurrence data, relevance of climate norms for species establishment, and availability of data for rapid risk assessment.

ecology↗

bioRxiv2024

Beyond a diagnostic tool: Validating standardized Mahalanobis distance as a species distribution model for invasive alien species in North America

Species distribution models (SDMs) are useful tools for predicting where new invasive species can establish within a country, supporting both preparatory and response activities. National Plant Protection Organizations use SDMs to inform risk assessment and surveillance activities for emerging plant pests. However, SDMs face multiple and difficult statistical challenges, including multi-collinearity of input variables, correlation structures in climate variables that vary through time and space, limited species observation data, and they often lack formal tests of model performance. We have implemented a previously-reported extrapolation-detection tool as an SDM, rather than a diagnostic tool of SDMs. This method characterizes the observed multivariate climate envelope by using Mahalanobis distance to take advantage of the correlation between climate variables, and identifies areas where the climatic conditions are outside the range of the observed climate envelope. Model outputs include climate suitability maps, and most-important covariate analyses to identify the environmental drivers of the results while assisting in variable reduction. We performed a formal test to assess the ability of the SDM to identify areas invaded by invasive plant pests in North America. Using a list of 23 species from the Canadian Food Inspection Agencys regulated plant pest list, we demonstrate that this method achieves a high level of accuracy (> 85%) for determining climate suitability for North American plant pest invasions, especially when combined with most-important covariate-guided variable reduction. This suggests that the model is suitable for identifying areas of North America that are susceptible to future invasions. We show that many of the errors occur at the edge of climate suitable areas, where we would expect greater uncertainty in model predictions due to potential over-constraining and geospatial averaging. We present additional analyses to support recommendations on the use and limitations of this SDM in a regulatory context.

ecology↗

bioRxiv2020

Future-proofing code: Principles of coding for plant ecophysiology with {photosynthesis} as a case study

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: 1) standardized nomenclature, 2) consistency in style, 3) increased modularity/extensibility for easier editing and understanding, 4) code scalability for application to large datasets, 5) documented contingencies for code maintenance, 6) documentation to facilitate user understanding; 7) extensive tutorials, and 8) unit testing. 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.

plant biology↗

bioRxiv2020

Racing against stomatal attenuation: rapid CO2 response curves more reliably estimate photosynthetic capacity than steady state curves in a low conductance species

A/Ci curves are an important gas-exchange-based approach to understanding the regulation of photosynthesis, describing the response of net CO2 assimilation (A) to leaf internal concentration of CO2 (Ci). Low stomatal conductance species pose a challenge to the measurement of A/Ci curves by reducing the signal-to-noise ratio of gas exchange measures. Additionally, the stomatal attenuation effect of elevated ambient CO2 leads to further reduction of conductance and may lead to erroneous interpretation of high Ci responses of A. Rapid A/Ci response (RACiR) curves offer a potential practice to develop A/Ci curves faster than the stomatal closure response to elevated CO2. We used the moderately low conductance Citrus to compare traditional steady state (SS) A/Ci curves with RACiR curves. SS curves failed more often than RACiR curves. Overall parameter estimates were the same between SS and RACiR curves. When low stomatal conductance values were removed, triose-phosphate utilization (TPU) limitation estimates increased. Overall RACiR stomatal conductance values began and remained higher than SS values. Based on the comparable resulting parameter estimates, higher likelihood of success and reduced measurement time, we propose RACiR as a valuable tool to measure A/Ci responses in low conductance species.

plant biology↗

bioRxiv2020

Robust estimates of cuticle conductance on stomatous leaf surfaces during the light induction of photosynthesis

O_LICuticle conductance (gcw) can bias calculations of intercellular CO2 concentration inside the leaf (Ci) when stomatal conductance (gsw) is small. C_LIO_LIWe examined how the light induction of photosynthesis impacts calculations by directly measuring Ci along with standard gas exchange in sunflower and tobacco leaves. C_LIO_LIWhen photosynthesis was induced from dark to saturating light (1200 mol m-2 s-1 PAR) the calculated Ci was significantly larger than measured Ci and the difference decreased as gsw increased. This difference could lead to over-estimation of rubisco deactivation by limited CO2 supply during early induction of photosynthesis. However, only small differences in Ci were observed during the induction from shade (50 mol m-2 s-1 PAR) because gsw was sufficiently large. The induction from dark also allowed robust estimations of gcw when combined with direct Ci measurements. These gcw estimates succeeded in correcting the calculation, suggesting that the cuticle was the major source of error. C_LIO_LIDespite a technical restriction to amphi-stomatous leaves, the presented technique has a potential to provide insights into the cuticle conductance on intact stomatous leaf surfaces. C_LI

plant biology↗

bioRxiv2020

Minimum conductance in leaves-cuticle, leaky stomata, or water vapor saturation?

O_LIMinimum conductance (gw,min) in leaves is important for water relations in land plants. Yet, its regulation is unclear due to measurement constraints. C_LIO_LICuticle conductance to water vapor (gcw) was estimated from the difference between calculated and direct measurement of CO2 concentration in the leaf airspace (Ci) of amphi-stomatous tobacco and sunflower. We estimated gcw in a series of light and dark experiments, and partitioned gw,min into cuticle and stomatal components. Some leaves were detached to simulate severe drought through desiccation conditions where gw,min is generally determined. C_LIO_LIBetween light and dark experiments each gcw was in close agreement, and successfully corrected the discrepancies of calculations from direct measurements. In the dark, either stomatal or cuticle conductance dominated the gw,min, suggesting either of them can control the minimum water loss. In the detached leaves, gcw could not be estimated likely due to unsaturation in the leaf airspace, and gw,min was progressively underestimated. C_LIO_LIBesides cuticle, leaf water status is a potential pitfall of the standard gas exchange model. Our technique is useful to study the minimal gas exchange as well as to refine the model. C_LI

plant biology↗

bioRxiv2020

Where in the leaf is intercellular CO2 (Ci)? Considerations and recommendations for assessing gaseous diffusion in leaves

The assumptions that water vapor exchange occurs exclusively through stomata, that the intercellular airspace is fully saturated with water vapor, and that CO2 gradients are negligible between stomata and the intercellular airspace have enabled significant advancements in photosynthetic gas exchange research for nearly 60 years via calculation of intercellular CO2 (Ci). However, available evidence suggests that these assumptions may be overused. Here we review the literature surrounding evidence for and against the assumptions made by Moss & Rawlins (1963). We reinterpret data from the literature by propagating different rates of cuticular water loss, CO2 gradients, and unsaturation through the data. We find that in general, when cuticle conductance is less than 1% of stomatal conductance, the assumption that water vapor exchange occurs exclusively through stomata has a marginal effect on gas exchange calculations, but this is not true when cuticle conductance exceeds 5% of stomatal conductance. Our analyses further suggest that CO2 and water vapor gradients have stronger impacts at higher stomatal conductance, while cuticle conductance has a greater impact at lower stomatal conductance. Therefore, we recommend directly measuring Ci whenever possible, measuring apoplastic water potentials to estimate humidity inside the leaf, and exercising caution when interpreting data under conditions of high temperature and/or low stomatal conductance, and when a species is known to have high cuticular conductance. HighlightLeaf water vapor and CO2 exchange have been successfully used to model photosynthetic biochemistry. We review critical assumptions in these models and make recommendations about which need to be re-assessed.

plant biology↗

bioRxiv2020

A derivation error exists in the current implementation of the Johnson et al. (1942) modified Arrhenius function that affects leaf carbon balance models

O_LIUnderstanding biological temperature responses is crucial to predicting global carbon fluxes. The current approach to modelling temperature responses of photosynthetic capacity in large scale modelling efforts uses a modified Arrhenius equation. C_LIO_LIWe rederived the modified Arrhenius equation from the source publication from 1942 and uncovered a missing term that was dropped by 2002. We compare fitted temperature response parameters between the correct and incorrect derivation of the modified Arrhenius equation. C_LIO_LIWe find that most parameters are minimally affected, though activation energy is impacted quite substantially. We then scaled the impact of these small errors to whole plant carbon balance and found that the impact of the rederivation of the modified Arrhenius equation on modelled daily carbon gain causes a meaningful deviation of ~18% day-1. C_LIO_LIThis suggests that the error in the derivation of the modified Arrhenius equation has impacted the accuracy of predictions of carbon fluxes at larger scales since >40% of Earth System Models contain the erroneous derivation. We recommend that the derivation error be corrected in modelling efforts moving forward. C_LI

plant biology↗