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Transfer efficiency is the proportion of energy passed between nodes in food webs. It is an emergent, unitless property that is difficult to measure, and responds dynamically to environmental and ecosystem changes. Because the consequences of changes in transfer efficiency compound through ecosystems, slight variations can have large effects on food availability for top predators. Here, we review the processes controlling transfer efficiency, approaches to estimate it, and known variations across ocean biomes. Both process-level analysis and observed macroscale variations suggest that ecosystem-scale transfer efficiency is highly variable, impacted by fishing, and will decline with climate change. It is important that we more fully resolve the processes controlling transfer efficiency in models to effectively anticipate changes in marine ecosystems and fisheries resources.

Open science skills are increasingly important for a career in ecology and evolutionary biology (EEB) as efforts to make data and analyses publicly available continue to become more commonplace. While learning core concepts in EEB, students are also expected to gain skills in conducting open science to prepare for future careers. Core open science skills like programming, data sharing, and practices that promote reproducibility can be taught to undergraduate students alongside core concepts in EEB. Yet, these skills are not always taught in biology undergraduate programs, and a major challenge in developing open science skills and learning EEB concepts simultaneously is the high cognitive load associated with learning multiple disparate concepts at the same time. One solution is to provide students with easily digestible, scaffolded, pre‐formatted code in the form of vignettes and interactive tutorials. Here, we present six open source teaching tutorials for undergraduate students in EEB. These tutorials teach fundamental ecological concepts, data literacy, programming (using R software), and analysis skills using publicly available datasets while introducing students to open science concepts and tools. Spanning a variety of EEB topics and skill levels, these tutorials serve as examples and resources for educators to integrate open science tools, programming, and data literacy into teaching EEB at the undergraduate level. [ABSTRACT FROM AUTHOR]

The effect of climate warming on community composition is expected to be contingent on competitive outcomes, yet approaches to projecting ecological outcomes often rely on measures of density‐independent performance across temperatures. Recent theory suggests that the temperature response of competitive ability differs in shape from that of population growth rate. Here, we test this hypothesis empirically and find thermal performance curves of competitive ability in aquatic microorganisms to be systematically left‐shifted and flatter compared to those of exponential growth rate. The minimum resource requirement for growth, R*—an inverse indicator of competitive ability—changes with temperature following a U‐shaped pattern in all four species tested, contrasting from their left‐skewed density‐independent growth rate thermal performance curves. Our results provide new evidence that exploitative competitive success is highest at temperatures that are sub‐optimal for growth, suggesting performance estimates of density‐independent variables might underpredict performance in cooler competitive environments. [ABSTRACT FROM AUTHOR]

Thermal variability is a key driver of ecological processes, affecting organisms and populations across multiple temporal scales. Despite the ubiquity of variation, biologists lack a quantitative synthesis of the observed ecological consequences of thermal variability across a wide range of taxa, phenotypic traits and experimental designs. Here, we conduct a meta-analysis to investigate how properties of organisms, their experienced thermal regime and whether thermal variability is experienced in either the past (prior to an assay) or present (during the assay) affect performance relative to the performance of organisms experiencing constant thermal environments. Our results-which draw upon 1712 effect sizes from 75 studies-indicate that the effects of thermal variability are not unidirectional and become more negative as mean temperature and fluctuation range increase. Exposure to variation in the past decreases performance to a greater extent than variation experienced in the present and increases the costs to performance more than diminishing benefits across a broad set of empirical studies. Further, we identify life-history attributes that predictably modify the ecological response to variation. Our findings demonstrate that effects of thermal variability on performance are context-dependent, yet negative outcomes may be heightened in warmer, more variable climates.

Understanding and predicting responses of ectothermic animals to temperature are essential for decision-making and management. The thermal performance curve (TPC), which quantifies the thermal sensitivity of traits such as metabolism, growth and feeding rates in laboratory conditions, is often used to predict responses of wild populations. However, central assumptions of this approach are that TPCs are relatively static between populations and that curves measured under stable temperature conditions can predict performance under variable conditions. We test these assumptions using two latitudinally matched populations of the ecosystem engineer Mytilus trossulus that differ in their experienced temperature variability regime. We acclimated each population in a range of constant or fluctuating temperatures for six weeks and measured a series of both short term (feeding rate, byssal thread production) and long-term (growth, survival) metrics to test the hypothesis that performance in fluctuating temperatures can be predicted from constant temperatures. We find that this was not true for any metric, and that there were important interactions with the population of origin. Our results emphasize that responses to fluctuating conditions are still poorly understood and suggest caution must be taken in the use of TPCs generated under constant temperature conditions for the prediction of wild population responses.

Variability in the environment defines the structure and dynamics of all living systems, from organisms to ecosystems. Species have evolved traits and strategies that allow them to detect, exploit and predict the changing environment. These traits allow organisms to maintain steady internal conditions required for physiological functioning through feedback mechanisms that allow internal conditions to remain at or near a set-point despite a fluctuating environment. In addition to feedback, many organisms have evolved feedforward processes, which allow them to adjust in anticipation of an expected future state of the environment. Here we provide a framework describing how feedback and feedforward mechanisms operating within organisms can generate effects across scales of organization, and how they allow living systems to persist in fluctuating environments. Daily, seasonal and multi-year cycles provide cues that organisms use to anticipate changes in physiologically relevant environmental conditions. Using feedforward mechanisms, organisms can exploit correlations in environmental variables to prepare for anticipated future changes. Strategies to obtain, store and act on information about the conditional nature of future events are advantageous and are evidenced in widespread phenotypes such as circadian clocks, social behaviour, diapause and migrations. Humans are altering the ways in which the environment fluctuates, causing correlations between environmental variables to become decoupled, decreasing the reliability of cues. Human-induced environmental change is also altering sensory environments and the ability of organisms to detect cues. Recognizing that living systems combine feedback and feedforward processes is essential to understanding their responses to current and future regimes of environmental fluctuations. This article is part of the theme issue 'Integrative research perspectives on marine conservation'.

Competition for limiting resources is among the most fundamental ecological interactions and has long been considered a key driver of species coexistence and biodiversity. Species' minimum resource requirements, their R *s, are key traits that link individual physiological demands to the outcome of competition. However, a major question remains unanswered-to what extent are species' competitive traits able to evolve in response to resource limitation? To address this knowledge gap, we performed an evolution experiment in which we exposed Chlamydomonas reinhardtii for approximately 285 generations to seven environments in chemostats that differed in resource supply ratios (including nitrogen, phosphorus and light limitation) and salt stress. We then grew the ancestors and descendants in a common garden and quantified their competitive abilities for essential resources. We investigated constraints on trait evolution by testing whether changes in resource requirements for different resources were correlated. Competitive abilities for phosphorus improved in all populations, while competitive abilities for nitrogen and light increased in some populations and decreased in others. In contrast to the common assumption that there are trade-offs between competitive abilities for different resources, we found that improvements in competitive ability for a resource came at no detectable cost. Instead, improvements in competitive ability for multiple resources were either positively correlated or not significantly correlated. Using resource competition theory, we then demonstrated that rapid adaptation in competitive traits altered the predicted outcomes of competition. These results highlight the need to incorporate contemporary evolutionary change into predictions of competitive community dynamics over environmental gradients. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.