Cross-sector communication, collaboration and knowledge exchange are still significant challenges for practical adoption of the One Health paradigm. To address these needs the “One Health Surveillance Codex” (OHS Codex) was established to provide a framework for the One Health community to continuously share practical solutions (e.g. tools, technical resources, guidance documents and experiences) applicable for national and international stakeholders from different One Health Surveillance sectors. Currently, the OHS Codex provides a number of resources that support the adoption of the OH paradigm in areas linked to the harmonization and interpretation of surveillance data. The OHS Codex framework comprises four high-level “action” principles, which respectively support collaboration, knowledge exchange, data interoperability, and dissemination. These principles match well with priority areas identified in the “Tripartite Guide to Addressing Zoonotic Diseases in Countries” published by WHO, FAO and OIE. Within each of the four principles, the OHS Codex provides a collection of useful resources as well as pointers to success stories for the application of these resources. As the OHS Codex is designed as an open community framework, it will continuously evolve and adapt to the needs of the OH community in the future.

The regulation of resource allocation in biological systems observed today is the cumulative result of natural selection in ancestral and recent environments. To what extent are observed resource allocation patterns in different photosynthetic types optimally adapted to current conditions, and to what extent do they reflect ancestral environments? Here, we explore these questions for C3, C4, and C3–C4 intermediate plants of the model genus Flaveria. We developed a detailed mathematical model of carbon fixation, which accounts for various environmental parameters and for energy and nitrogen partitioning across photosynthetic components. This allows us to assess environment-dependent plant physiology and performance as a function of resource allocation patterns. Models of C4 plants optimized for conditions experienced by evolutionary ancestors perform better than models accounting for experimental growth conditions, indicating low phenotypic plasticity. Supporting this interpretation, the model predicts that C4 species need to re-allocate more nitrogen between photosynthetic components than C3 species to adapt to new environments. We thus hypothesize that observed resource distribution patterns in C4 plants still reflect optimality in ancestral environments, allowing the quantitative inference of these environments from today’s plants. Our work allows us to quantify environmental effects on photosynthetic resource allocation and performance in the light of evolutionary history.

Summary-The regulation of resource allocation in biological systems observed today is the cumulative result of natural selection in ancestral and recent environments. To what extent are observed resource allocation patterns in different photosynthetic types optimally adapted to current conditions, and to what extend do they reflect ancestral environments? Here, we explore these questions for C3, C4, and C3-C4 intermediate plants of the model genus Flaveria.-We developed a detailed mathematical model of carbon fixation, which accounts for various environmental parameters and for energy and nitrogen partitioning across photosynthetic components. This allows us to assess environment-dependent plant physiology and performance as a function of resource allocation patterns.-To achieve maximal CO2 fixation rates under growth conditions differing from those experienced during their evolution, C4 species need to re-allocate significantly more nitrogen between photosynthetic components than their C3 relatives. As this is linked to a limited phenotypic plasticity, observed resource distributions in C4 plants still reflect optimality in ancestral environments, allowing their quantitative inference.-Our work allows us to quantify environmental effects on resource allocation and performance of photosynthetic organisms. This understanding paves the way for interpreting present photosynthetic physiology in the light of evolutionary history.

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