How widespread use of generative AI for images and video can affect the environment and the science of ecology.

Generative artificial intelligence (AI) models will have broad impacts on society including the scientific enterprise; ecology and environmental science will be no exception. Here, we discuss the potential opportunities and risks of advanced generative AI for visual material (images and video) for the science of ecology and the environment itself. There are clearly opportunities for positive impacts, related to improved communication, for example; we also see possibilities for ecological research to benefit from generative AI (e.g., image gap filling, biodiversity surveys, and improved citizen science). However, there are also risks, threatening to undermine the credibility of our science, mostly related to actions of bad actors, for example in terms of spreading fake information or committing fraud. Risks need to be mitigated at the level of government regulatory measures, but we also highlight what can be done right now, including discussing issues with the next generation of ecologists and transforming towards radically open science workflows.

Ten simple rules for increased lab resilience.

When running a lab we do not think about calamities, since they are rare events for which we cannot plan while we are busy with the day-to-day management and intellectual challenges of a research lab. No lab team can be prepared for something like a pandemic such as COVID-19, which has led to shuttered labs around the globe. But many other types of crises can also arise that labs may have to weather during their lifetime. What can researchers do to make a lab more resilient in the face of such exterior forces? What systems or behaviors could we adjust in 'normal' times that promote lab success, and increase the chances that the lab will stay on its trajectory? We offer 10 rules, based on our current experiences as a lab group adapting to crisis.

Rate of environmental change across scales in ecology.

The rate of change (RoC) of environmental drivers matters: biotic and abiotic components respond differently when faced with a fast or slow change in their environment. This phenomenon occurs across spatial scales and thus levels of ecological organization. We investigated the RoC of environmental drivers in the ecological literature and examined publication trends across ecological levels, including prevalent types of evidence and drivers. Research interest in environmental driver RoC has increased over time (particularly in the last decade), however, the amount of research and type of studies were not equally distributed across levels of organization and different subfields of ecology use temporal terminology (e.g. 'abrupt' and 'gradual') differently, making it difficult to compare studies. At the level of individual organisms, evidence indicates that responses and underlying mechanisms are different when environmental driver treatments are applied at different rates, thus we propose including a time dimension into reaction norms. There is much less experimental evidence at higher levels of ecological organization (i.e. population, community, ecosystem), although theoretical work at the population level indicates the importance of RoC for evolutionary responses. We identified very few studies at the community and ecosystem levels, although existing evidence indicates that driver RoC is important at these scales and potentially could be particularly important for some processes, such as community stability and cascade effects. We recommend shifting from a categorical (e.g. abrupt versus gradual) to a quantitative and continuous (e.g. °C/h) RoC framework and explicit reporting of RoC parameters, including magnitude, duration and start and end points to ease cross-scale synthesis and alleviate ambiguity. Understanding how driver RoC affects individuals, populations, communities and ecosystems, and furthermore how these effects can feed back between levels is critical to making improved predictions about ecological responses to global change drivers. The application of a unified quantitative RoC framework for ecological studies investigating environmental driver RoC will both allow cross-scale synthesis to be accomplished more easily and has the potential for the generation of novel hypotheses.

Myristate and the ecology of AM fungi: significance, opportunities, applications and challenges.

A recent study by Sugiura and coworkers reported the non-symbiotic growth and spore production of an arbuscular mycorrhizal (AM) fungus, Rhizophagus irregularis, when the fungus received an external supply of certain fatty acids, myristates (C:14). This discovery follows the insight that AM fungi receive fatty acids from their hosts when in symbiosis. If this result holds up and can be repeated under nonsterile conditions and with a broader range of fungi, it has numerous consequences for our understanding of AM fungal ecology, from the level of the fungus, at the plant community level, and to functional consequences in ecosystems. In addition, myristate may open up several avenues from a more applied perspective, including improved fungal culture and supplementation of AM fungi or inoculum in the field. We here map these potential opportunities, and additionally offer thoughts on potential risks of this potentially new technology. Lastly, we discuss the specific research challenges that need to be overcome to come to an understanding of the potential role of myristate in AM ecology.

Arbuscular Mycorrhizal Fungi Alter the Community Structure of Ammonia Oxidizers at High Fertility via Competition for Soil NH4.

Nitrification represents a central process in the cycling of nitrogen (N) which in high-fertility habitats can occasionally be undesirable. Here, we explore how arbuscular mycorrhiza (AM) impacts nitrification when N availability is not limiting to plant growth. We wanted to test which of the mechanisms that have been proposed in the literature best describes how AM influences nitrification. We manipulated the growth settings of Plantago lanceolata so that we could control the mycorrhizal state of our plants. AM induced no changes in the potential nitrification rates or the estimates of ammonium oxidizing (AO) bacteria. However, we could observe a moderate shift in the community of ammonia-oxidizers, which matched the shift we saw when comparing hyphosphere to rhizosphere soil samples and mirrored well changes in the availability of ammonium in soil. We interpret our results as support that it is competition for N that drives the interaction between AM and AO. Our experiment sheds light on an understudied interaction which is pertinent to typical management practices in agricultural systems.

Application of the microbial community coalescence concept to riverine networks.

Flows of water, soil, litter, and anthropogenic materials in and around rivers lead to the mixing of their resident microbial communities and subsequently to a resultant community distinct from its precursors. Consideration of these events through a new conceptual lens, namely, community coalescence, could provide a means of integrating physical, environmental, and ecological mechanisms to predict microbial community assembly patterns better in these habitats. Here, we review field studies of microbial communities in riverine habitats where environmental mixing regularly occurs, interpret some of these studies within the community coalescence framework and posit novel hypotheses and insights that may be gained in riverine microbial ecology through the application of this concept. Particularly in the face of a changing climate and rivers under increasing anthropogenic pressures, knowledge about the factors governing microbial community assembly is essential to forecast and/or respond to changes in ecosystem function. Additionally, there is the potential for microbial ecology studies in rivers to become a driver of theory development: riverine systems are ideal for coalescence studies because regular and predictable environmental mixing occurs. Data appropriate for testing community coalescence theory could be collected with minimal alteration to existing study designs.

Microbial Ecology: Community Coalescence Stirs Things Up.

When methane-producing microbial communities are mixed experimentally, the resulting community is dominated by the community with the greatest resource-use efficiency. These results suggest a degree of community cohesion, or the maintenance of that initial community in the mix.