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1. Coastal processes modify projections of some climate-driven stressors in the California Current System

   https://doi.org/10.5194/bg-18-2871-2021  

   Siedlecki, Samantha A.; Pilcher, Darren; Howard, Evan M.; Deutsch, Curtis; MacCready, Parker; Norton, Emily L.; Frenzel, Hartmut; Newton, Jan; Feely, Richard A.; Alin, Simone R.; et al (January 2021, Biogeosciences)

   Abstract. Global projections for ocean conditions in 2100 predict that the North Pacific will experience some of the largest changes. Coastal processes that drive variability in the region can alter these projected changes but are poorly resolved by global coarse-resolution models. We quantify the degree to which local processes modify biogeochemical changes in the eastern boundary California Current System (CCS) using multi-model regionally downscaled climate projections of multiple climate-associated stressors (temperature, O2, pH, saturation state (Ω), and CO2). The downscaled projections predict changes consistent with the directional change from the global projections for the same emissions scenario. However, the magnitude and spatial variability of projected changes are modified in the downscaled projections for carbon variables. Future changes in pCO2 and surface Ω are amplified, while changes in pH and upper 200 m Ω are dampened relative to the projected change in global models. Surface carbon variable changes are highly correlated to changes in dissolved inorganic carbon (DIC), pCO2 changes over the upper 200 m are correlated to total alkalinity (TA), and changes at the bottom are correlated to DIC and nutrient changes. The correlations in these latter two regions suggest that future changes in carbon variables are influenced by nutrient cycling, changes in benthic–pelagic coupling, and TA resolved by the downscaled projections. Within the CCS, differences in global and downscaled climate stressors are spatially variable, and the northern CCS experiences the most intense modification. These projected changes are consistent with the continued reduction in source water oxygen; increase in source water nutrients; and, combined with solubility-driven changes, altered future upwelled source waters in the CCS. The results presented here suggest that projections that resolve coastal processes are necessary for adequate representation of the magnitude of projected change in carbon stressors in the CCS. 

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2. Beyond Simple Trend Tests: Detecting Significant Changes in Design‐Flood Quantiles

   https://doi.org/10.1029/2023GL103438  

   Awasthi, C.; Archfield, S_A; Reich, B_J; Sankarasubramanian, A. (July 2023, Geophysical Research Letters)

   Abstract Changes in annual maximum flood (AMF), which are usually detected using simple trend tests (e.g., Mann‐Kendall test (MKT)), are expected to change design‐flood estimates. We propose an alternate framework to detect significant changes in design‐flood between two periods and evaluate it for synthetically generated AMF from the Log‐Pearson Type‐3 (LP3) distribution due to changes in moments associated with flood distribution. Synthetic experiments show MKT does not consider changes in all three moments of the LP3 distribution and incorrectly detects changes in design‐flood. We applied the framework on 31 river basins spread across the United States. Statistically significant changes in design‐flood quantiles were observed even without a significant trend in AMF and basins with statistically significant trend did not necessarily exhibit statistically significant changes in design‐flood. We recommend application of the framework for evaluating changes in design‐flood estimates considering changes in all the moments as opposed to simple trend tests. 

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3. Local biodiversity change reflects interactions among changing abundance, evenness, and richness

   https://doi.org/10.1002/ecy.3820  

   Blowes, Shane A.; Daskalova, Gergana N.; Dornelas, Maria; Engel, Thore; Gotelli, Nicholas J.; Magurran, Anne E.; Martins, Inês S.; McGill, Brian; McGlinn, Daniel J.; Sagouis, Alban; et al (December 2022, Ecology)

   Abstract Biodiversity metrics often integrate data on the presence and abundance of multiple species. Yet our understanding of covariation between changes to the numbers of individuals, the evenness of species relative abundances, and the total number of species remains limited. Using individual‐based rarefaction curves, we show how expected positive relationships among changes in abundance, evenness and richness arise, and how they can break down. We then examined interdependencies between changes in abundance, evenness and richness in more than 1100 assemblages sampled either through time or across space. As predicted, richness changes were greatest when abundance and evenness changed in the same direction, and countervailing changes in abundance and evenness acted to constrain the magnitude of changes in species richness. Site‐to‐site differences in abundance, evenness, and richness were often decoupled, and pairwise relationships between these components across assemblages were weak. In contrast, changes in species richness and relative abundance were strongly correlated for assemblages varying through time. Temporal changes in local biodiversity showed greater inertia and stronger relationships between the component changes when compared to site‐to‐site variation. Overall, local variation in assemblage diversity was rarely due to repeated passive samples from an approximately static species abundance distribution. Instead, changing species relative abundances often dominated local variation in diversity. Moreover, how changing relative abundances combined with changes to total abundance frequently determined the magnitude of richness changes. Embracing the interdependencies between changing abundance, evenness and richness can provide new information to better understand biodiversity change in the Anthropocene. 

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4. Testing Configuration Changes in Context to Prevent Production Failures

   Sun, Xudong; Cheng, Runxiang; Chen, Jianyan; Ang, Elaine; Legunsen, Owolabi; Xu, Tianyin (November 2020, In Proceedings of the 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI'20))

   null (Ed.)

   Large-scale cloud services deploy hundreds of configuration changes to production systems daily. At such velocity, con- figuration changes have inevitably become prevalent causes of production failures. Existing misconfiguration detection and configuration validation techniques only check configu- ration values. These techniques cannot detect common types of failure-inducing configuration changes, such as those that cause code to fail or those that violate hidden constraints. We present ctests, a new type of tests for detecting failure- inducing configuration changes to prevent production failures. The idea behind ctests is simple—connecting production sys- tem configurations to software tests so that configuration changes can be tested in the context of code affected by the changes. So, ctests can detect configuration changes that ex- pose dormant software bugs and diverse misconfigurations. We show how to generate ctests by transforming the many existing tests in mature systems. The key challenge that we address is the automated identification of test logic and oracles that can be reused in ctests. We generated thousands of ctests from the existing tests in five cloud systems. Our results show that ctests are effective in detecting failure-inducing configuration changes before deployment. We evaluate ctests on real-world failure-inducing configura- tion changes, injected misconfigurations, and deployed con- figuration files from public Docker images. Ctests effectively detect real-world failure-inducing configuration changes and misconfigurations in the deployed files. 

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5. How Do Code Changes Evolve in Different Platforms? A Mining-Based Investigation

   https://doi.org/10.1109/ICSME.2019.00033  

   Viggiato, Markos; Oliveira, Johnatan; Figueiredo, Eduardo; Jamshidi, Pooyan; Kastner, Christian (September 2019, Proceedings of the 35th International Conference on Software Maintenance and Evolution (ICSME))

   Software developed in different platforms has different characteristics and needs. More specifically, code changes are differently performed in the mobile platform compared to non-mobile platforms (e.g., desktop and Web platforms). Prior works have investigated the differences in specific platforms. However, we still lack a deeper understanding of how code changes evolve across different software platforms. In this paper, we present a study aiming at investigating the frequency of changes and how source code changes, build changes and test changes co-evolve in mobile and non-mobile platforms. We developed linear regression models to explain which factors influence the frequency of changes in different platforms and applied the Apriori algorithm to find types of changes that frequently occur together. Our findings show that non-mobile repositories have a higher number of commits per month compared to mobile and our regression models suggest that being mobile significantly impacts on the number of commits in a negative direction when controlling for confound factors, such as code size. We also found that developers do not usually change source code files together with build files or test files. We argue that our results can provide valuable information for developers on how changes are performed in different platforms so that practices adopted in successful software systems can be followed. 

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