History's legacy: Why future progress in ecology demands a view of the past.

History has profoundly affected the composition, distribution, and abundances of species in contemporary ecosystems. A full understanding of how ecosystems work and change must therefore take history into account. We offer four well-studied examples illustrating how a knowledge of history has strengthened interpretations of modern systems: the development of molluscan antipredatory defenses in relation to shell-breaking predators; the North Pacific kelp ecosystem with sea otters, smaller predators, sea urchins, and large herbivores; estuarine ecosystems affected by the decline in oysters and other suspension feeders; and the legacy of extinct large herbivores and frugivores in tropical American forests. Many current ecological problems would greatly benefit from a historical perspective. We highlight four of these: soil depletion and tree stunting in forests related to the disappearance of large consumers; the spread of anoxic dead zones in the ocean, which we argue could be mitigated by restoring predator and suspension-feeding guilds; ocean acidification, which would be alleviated by more nutrient recycling by consumers in the aerobic ecosystem; and the relation between species diversity and keystone predators, a foundational concept that is complicated by simplified trophic relationships in modern ecosystems.

Global and national trends, gaps, and opportunities in documenting and monitoring species distributions.

Conserving and managing biodiversity in the face of ongoing global change requires sufficient evidence to assess status and trends of species distributions. Here, we propose novel indicators of biodiversity data coverage and sampling effectiveness and analyze national trajectories in closing spatiotemporal knowledge gaps for terrestrial vertebrates (1950 to 2019). Despite a rapid rise in data coverage, particularly in the last 2 decades, strong geographic and taxonomic biases persist. For some taxa and regions, a tremendous growth in records failed to directly translate into newfound knowledge due to a sharp decline in sampling effectiveness. However, we found that a nation's coverage was stronger for species for which it holds greater stewardship. As countries under the post-2020 Global Biodiversity Framework renew their commitments to an improved, rigorous biodiversity knowledge base, our findings highlight opportunities for international collaboration to close critical information gaps.

Emergence of scientific understanding in real-time ecological research practice.

Scientific understanding as a subject of inquiry has become widely discussed in philosophy of science and is often addressed through case studies from history of science. Even though these historical reconstructions engage with details of scientific practice, they usually provide only limited information about the gradual formation of understanding in ongoing processes of model and theory construction. Based on a qualitative ethnographic study of an ecological research project, this article shifts attention from understanding in the context of historical case studies to evidence of current case studies. By taking de Regt's (Understanding scientific understanding. Oxford University Press, New York, 2017) contextual theory of scientific understanding into the field, it confirms core tenets of the contextual theory (e.g. the crucial role of visualization and visualizability) suggesting a normative character with respect to scientific activities. However, the case study also shows the limitations of de Regt's latest version of this theory as an attempt to explain the development of understanding in current practice. This article provides a model representing the emergence of scientific understanding that exposes main features of scientific understanding such as its gradual formation, its relation to skills and imagination, and its capacity for knowledge selectivity. The ethnographic evidence presented here supports the claim that something unique can be learned by looking into ongoing research practices that can't be gained by studying historical case studies.

Standard guidelines for the publication of telomere qPCR results in evolutionary ecology.

Telomere length has been used as a proxy of fitness, aging and lifespan in vertebrates. In the last decade, dozens of articles reporting on telomere dynamics in the fields of ecology and evolution have been published for a wide range of taxa. With this growing interest, it is necessary to ensure the accuracy and reproducibility of telomere length measurement techniques. Real-time quantitative PCR (qPCR) is routinely applied to measure relative telomere length. However, this technique is highly sensitive to several methodological variables and the optimization of qPCR telomere assays remains highly variable between studies. Therefore, standardized guidelines are required to enable the optimization of robust protocols, and to help in judging the validity of the presented results. This review provides an overview of preanalytical and analytical factors that can lead to qPCR inconsistencies and biases, including: (a) sample type, collection and storage; (b) DNA extraction, storage and quality; (c) qPCR primers, laboratory reagents, and assay conditions; and (d) data analysis. We propose a minimum level of information for publication of qPCR telomere assays in evolutionary ecology considering the methodological pitfalls and sources of error. This review highlights the complexity of the optimization and validation of qPCR for telomere measurement per se, demonstrating the importance of transparency and clarity of reporting methodological details required for reliable, reproducible and comparable qPCR telomere assays. We encourage efforts to implement standardized protocols that ensure the rigour and quality of telomere dynamics studies.

Systematic approach to evaluating environmental and ecological technologies for wastewater treatment.

Evaluating the performance of wastewater treatment represents a challenging and complex task as it usually involves engineering, environmental and economic (3E) factors. In this study, we developed an 3E triangle model to evaluate the performance of environmental technologies (i.e., anaerobic-anoxic-oxic reactors, oxidation ditches, and membrane bioreactors) and ecological technologies (i.e., stabilization ponds, constructed wetlands, and slow-rate systems) for wastewater treatment. A total of 17 key performance indicators, such as energy consumption, pollutant removal, global warming potential and wastewater treatment fees, were considered in the 3E triangle model. The results indicated that, in terms of engineering performance, both the membrane bioreactors and constructed wetlands were stable, effective and reliable during their operating periods. When the environmental impacts of wastewater treatment technologies were compared via a life cycle assessment, the ecological technologies showed superior performance, in terms of environmental impacts, especially for the global warming potential and eutrophication potential. In general, environmental technologies exhibited higher treatment fees and unit construction costs because of their large power consumption and equipment costs. In contrast, ecological technologies had higher unit land use due to their large area requirements and low treatment capacity. In overall, both the membrane bioreactors and constructed wetlands showed excellent overall performance in the 3E triangle model. Wastewater treatment plant are typical case studies for addressing the interactions of water and energy elements. Reducing energy consumption is a hotspot for the research field of membrane bioreactors, while constructed wetlands are continually improved and optimized to have broad applications for rural wastewater treatment.

Best practice guidelines for studies of parasite community ecology.

In recent decades, parasite community ecology has produced hundreds of studies on an ever-growing number of host species, and developed into an active sub-discipline of parasitology. However, this growth has been characterized by a lack of standards in the practices used by researchers, with many common approaches being flawed, unjustified or misleading. Here, in the hope of promoting advances in the study of parasite community ecology, I identify some of the most common errors or weaknesses in past studies, and propose ten simple rules for best practice in the field. They cover issues including, among others, taxonomic resolution, proper and justifiable analytical methods, higher-level replication, controlling for sampling effort or species richness, accounting for spatial distances, using experimental approaches, and placing raw data in the public domain. While knowledge of parasite communities has expanded in breadth, with more and more host species being studied, true progress has been very limited with respect to our understanding of fundamental general processes shaping these communities. It is hoped that the guidelines presented here can direct researchers away from the entrenched use of certain approaches flawed in design, analysis or interpretation, by offering a more rigorous and standardized set of practices, and, hopefully, a way forward.

Review and recommendations on criteria to evaluate the relevance of pesticide interaction data for ecological risk assessments.

Mixing pesticides with different modes of action can provide a wider spectrum of control with fewer applications compared to using single active ingredients and is essential for comprehensive management of pest resistance. Mixture studies with pesticides are performed to assess compatibility, combined efficacy, and potential for toxicological interactions that damage crops. The purpose of this paper is to review and recommend previously published scientific criteria for evaluating the quality, relevance and interpretability of data on toxicological interactions and to demonstrate a methodology for applying them objectively to mixtures studies used in ecological risk assessment. The recommended criteria reflect the consensus of the literature on interaction analysis from decades of research in pharmacology and toxicology and are broadly applicable to mixtures of drugs, pesticides, industrial chemicals and food additives. They are useful for researchers who design and analyze interaction studies, for risk assessors who use interaction data in risk assessments, and for those who make risk management decisions pertaining to pesticides. This paper describes our methodology for assessing data on the combined activity of pesticides and then discusses how to interpret such data in the context of an ecological risk assessment. Examples have been drawn primarily from studies with herbicides and nontarget plants, and several example analyses have been included that can inform whether mixture data are sufficiently reliable and relevant for use in regulatory decision making.