A prominent signal of the Anthropocene is the extinction and population reduction of the megabiota—the largest animals and plants on the planet. However, we lack a predictive framework for the sensitivity of megabiota during times of rapid global change and how they impact the functioning of ecosystems and the biosphere. Here, we extend metabolic scaling theory and use global simulation models to demonstrate that (i) megabiota are more prone to extinction due to human land use, hunting, and climate change; (ii) loss of megabiota has a negative impact on ecosystem metabolism and functioning; and (iii) their reduction has and will continue to significantly decrease biosphere functioning. Global simulations show that continued loss of large animals alone could lead to a 44%, 18% and 92% reduction in terrestrial heterotrophic biomass, metabolism, and fertility respectively. Our findings suggest that policies that emphasize the promotion of large trees and animals will have disproportionate impact on biodiversity, ecosystem processes, and climate mitigation.

Three perspectives were taken to explain decision-making within team sports (information processing, recognition primed decision-making, and ecological dynamics perspectives), resulting in conceptual tension and practical confusion. The aim of this paper was to interrogate empirical evidence to (1) understand the process of decision-making within team sports and (2) capture the characteristics of decision-making expertise in a team sport context. Nine electronic databases (SPORTDiscus, PsycINFO, PsycArticles, PsycTests, PubMed, SAGE journals online, Web of Knowledge, Academic Search Complete, and Web of Science) were searched until the final return in March 2021. Fifty-three articles satisfied the inclusion criteria, were analysed thematically, and synthesised using a narrative approach. Findings indicate that the relative absence or presence of mental representation within the decision-making process depends on factors, including complexity, typicality, time available, and contextual priors available in the game situation. We recommend that future research integrate concepts and methodologies prevalent within each perspective to better understand decision-making within team sports before providing implications for practitioners.

The leaf economic spectrum (LES) describes a set of universal trade-offs between leaf mass per area (LMA), leaf nitrogen (N), leaf phosphorus (P) and leaf photosynthesis that influence patterns of primary productivity and nutrient cycling. Many questions regarding vegetation-climate feedbacks can be addressed with a better understanding of LES traits and their controls. Remote sensing offers enormous potential for generating large-scale LES trait data. Yet so far, canopy studies have been limited to imaging spectrometers onboard aircraft, which are rare, expensive to deploy and lack fine-scale resolution. In this study, we measured VNIR (visible-near infrared (400–1050 nm)) reflectance of individual sun and shade leaves in 7 one-ha tropical forest plots located along a 1200–2000 mm precipitation gradient in West Africa. We collected hyperspectral imaging data from 3 of the 7 plots, using an octocopter-based unmanned aerial vehicle (UAV), mounted with a hyperspectral mapping system (450–950 nm, 9 nm FWHM). Using partial least squares regression (PLSR), we found that the spectra of individual sun leaves demonstrated significant (p < 0.01) correlations with LMA and leaf chemical traits: r² = 0.42 (LMA), r² = 0.43 (N), r² = 0.21 (P), r² = 0.20 (leaf potassium (K)), r² = 0.23 (leaf calcium (Ca)) and r² = 0.14 (leaf magnesium (Mg)). Shade leaf spectra displayed stronger relationships with all leaf traits. At the airborne level, four of the six leaf traits demonstrated weak (p < 0.10) correlations with the UAV-collected spectra of 58 tree crowns: r² = 0.25 (LMA), r² = 0.22 (N), r² = 0.22 (P), and r² = 0.25 (Ca). From the airborne imaging data, we used LMA, N and P values to map the LES across the three plots, revealing precipitation and substrate as co-dominant drivers of trait distributions and relationships. Positive N-P correlations and LMA-P anticorrelations followed typical LES theory, but we found no classic trade-offs between LMA and N. Overall, this study demonstrates the application of UAVs to generating LES information and advancing the study and monitoring tropical forest functional diversity.

The Late Quaternary extinctions of megafauna (defined as animal species > 44.5 kg) reduced the dispersal of seeds and nutrients, and likely also microbes and parasites. Here we use body‐mass based scaling and range maps for extinct and extant mammal species to show that these extinctions led to an almost seven‐fold reduction in the movement of gut‐transported microbes, such as Escherichia coli (3.3–0.5 km ² d ⁻¹ ). Similarly, the extinctions led to a seven‐fold reduction in the mean home ranges of vector‐borne pathogens (7.8–1.1 km ² ). To understand the impact of this, we created an individual‐based model where an order of magnitude decrease in home range increased maximum aggregated microbial mutations 4‐fold after 20 000 yr. We hypothesize that pathogen speciation and hence endemism increased with isolation, as global dispersal distances decreased through a mechanism similar to the theory of island biogeography. To investigate if such an effect could be found, we analysed where 145 zoonotic diseases have emerged in human populations and found quantitative estimates of reduced dispersal of ectoparasites and fecal pathogens significantly improved our ability to predict the locations of outbreaks (increasing variance explained by 8%). There are limitations to this analysis which we discuss in detail, but if further studies support these results, they broadly suggest that reduced pathogen dispersal following megafauna extinctions may have increased the emergence of zoonotic pathogens moving into human populations.

Sodium (Na) plays a critical role in the functioning of terrestrial ecosystems. In Na‐poor regions, plant consumers may experience Na deficiency and adapt by seeking supplementary Na resources. This can markedly impact animal behavior, space‐use, and co‐existence, with concomitant impacts on ecosystems. Many studies have noted that Na‐seeking behaviors, such as soil consumption from mineral licks, are predominately observed for larger‐bodied herbivores. However, the mechanisms that drive interspecific variation in Na deficiency and mineral lick use remain poorly understood. Here, we examine whether allometric scaling of Na requirements can explain variation in mineral lick use by herbivorous and omnivorous mammals. We 1) collated data from published literature to derive an allometric scaling of Na requirements in mammals, 2) compared predicted Na requirements to estimated Na intake of mammal communities in three globally distant sites: the Peruvian Amazon, Kalahari Desert, and Malaysian Borneo and 3) examined the relationship between predicted Na deficiency and mineral lick use utilizing camera‐trap and mammal abundance data at each site. We found that minimum daily Na maintenance requirements in mammals scaled allometrically at a higher factor (BM ^{0.91 (CI: 0.80–1.0)} ) than that of food and water Na intake (BM ^0.71–0.79 ), indicating that larger species may be more susceptible to Na limitation. This aligned with a positive association between mineral lick use and body mass (BM), as well as Na deficiency, by species at all sites, and increased artificial salt and mineral lick consumption by larger‐bodied mammals in the Kalahari. Our results suggest that larger herbivores may be more sensitive to anthropogenic impacts to Na availability, which may alter their functional roles in ecosystems, particularly in Na‐poor regions. Further research is needed to explore the consequences of changing Na availability on animals and ecosystems, as well as advance our understanding of Na physiology in mammals.