It is well established that species richness of primary producers and primary consumers can enhance efficiency of resource uptake and biomass production of respective trophic levels. At the level of ...secondary consumers (predators), however, conclusions about the functional role of biodiversity have been mixed. We take advantage of a recent surge of published experiments (totaling 46 since 2005) to both evaluate general effects of predator richness on aggregate prey suppression (topâdown control) and explore sources of variability among experiments. Our results show that, across experiments, predator richness enhances prey suppression relative to the average single predator species (mean richness effect), but not the bestâperforming species. Mean richness effects in predator experiments were stronger than those for primary producers and detritivores, suggesting that relationships between richness and function may increase with trophic height in food webs. The strength of mean predator richness effects increased with the spatial and temporal scale of experiments, and the taxonomic distinctness (TD, used as a proxy of phylogenetic diversity) of species present. This latter result suggests that TD captures important aspects of functional differentiation among predators and that measures of biodiversity that go beyond species richness may help to better predict the effects of predator species loss.
Resource pulses are infrequent, large-magnitude, and short-duration events of increased resource availability. They include a diverse set of extreme events in a wide range of ecosystems, but ...identifying general patterns among the diversity of pulsed resource phenomena in nature remains an important challenge. Here we present a meta-analysis of resource pulse–consumer interactions that addresses four key questions: (1) Which characteristics of pulsed resources best predict their effects on consumers? (2) Which characteristics of consumers best predict their responses to resource pulses? (3) How do the effects of resource pulses differ in different ecosystems? (4) What are the indirect effects of resource pulses in communities? To investigate these questions, we built a data set of diverse pulsed resource–consumer interactions from around the world, developed metrics to compare the effects of resource pulses across disparate systems, and conducted multilevel regression analyses to examine the manner in which variation in the characteristics of resource pulse–consumer interactions affects important aspects of consumer responses. Resource pulse magnitude, resource trophic level, resource pulse duration, ecosystem type and subtype, consumer response mechanisms, and consumer body mass were found to be key explanatory factors predicting the magnitude, duration, and timing of consumer responses. Larger consumers showed more persistent responses to resource pulses, and reproductive responses were more persistent than aggregative responses. Aquatic systems showed shorter temporal lags between peaks of resource availability and consumer response compared to terrestrial systems, and temporal lags were also shorter for smaller consumers compared to larger consumers. The magnitude of consumer responses relative to their resource pulses was generally smaller for the direct consumers of primary resource pulses, compared to consumers at greater trophic distances from the initial resource pulse. In specific systems, this data set showed both attenuating and amplifying indirect effects. We consider the mechanistic processes behind these patterns and their implications for the ecology of resource pulses.
Marine taxa are threatened by anthropogenic impacts, but knowledge of their extinction vulnerabilities is limited. The fossil record provides rich information on past extinctions that can help ...predict biotic responses. We show that over 23 million years, taxonomic membership and geographic range size consistently explain a large proportion of extinction risk variation in six major taxonomic groups. We assess intrinsic risk—extinction risk predicted by paleontologically calibrated models—for modern genera in these groups. Mapping the geographic distribution of these genera identifies coastal biogeographic provinces where fauna with high intrinsic risk are strongly affected by human activity or climate change. Such regions are disproportionately in the tropics, raising the possibility that these ecosystems may be particularly vulnerable to future extinctions. Intrinsic risk provides a prehuman baseline for considering current threats to marine biodiversity.
Many scientific domains gather sufficient labels to train machine algorithms through human-in-the-loop techniques provided by the Zooniverse.org citizen science platform. As the range of projects, ...task types and data rates increase, acceleration of model training is of paramount concern to focus volunteer effort where most needed. The application of Transfer Learning (TL) between Zooniverse projects holds promise as a solution. However, understanding the effectiveness of TL approaches that pretrain on large-scale generic image sets vs. images with similar characteristics possibly from similar tasks is an open challenge. We apply a generative segmentation model on two Zooniverse project-based data sets: (1) to identify fat droplets in liver cells (FatChecker; FC) and (2) the identification of kelp beds in satellite images (Floating Forests; FF) through transfer learning from the first project. We compare and contrast its performance with a TL model based on the COCO image set, and subsequently with baseline counterparts. We find that both the FC and COCO TL models perform better than the baseline cases when using >75% of the original training sample size. The COCO-based TL model generally performs better than the FC-based one, likely due to its generalized features. Our investigations provide important insights into usage of TL approaches on multi-domain data hosted across different Zooniverse projects, enabling future projects to accelerate task completion.
Large-scale research endeavors can be hindered by logistical constraints limiting the amount of available data. For example, global ecological questions require a global dataset, and traditional ...sampling protocols are often too inefficient for a small research team to collect an adequate amount of data. Citizen science offers an alternative by crowdsourcing data collection. Despite growing popularity, the community has been slow to embrace it largely due to concerns about quality of data collected by citizen scientists. Using the citizen science project Floating Forests (http://floatingforests.org), we show that consensus classifications made by citizen scientists produce data that is of comparable quality to expert generated classifications. Floating Forests is a web-based project in which citizen scientists view satellite photographs of coastlines and trace the borders of kelp patches. Since launch in 2014, over 7,000 citizen scientists have classified over 750,000 images of kelp forests largely in California and Tasmania. Images are classified by 15 users. We generated consensus classifications by overlaying all citizen classifications and assessed accuracy by comparing to expert classifications. Matthews correlation coefficient (MCC) was calculated for each threshold (1-15), and the threshold with the highest MCC was considered optimal. We showed that optimal user threshold was 4.2 with an MCC of 0.400 (0.023 SE) for Landsats 5 and 7, and a MCC of 0.639 (0.246 SE) for Landsat 8. These results suggest that citizen science data derived from consensus classifications are of comparable accuracy to expert classifications. Citizen science projects should implement methods such as consensus classification in conjunction with a quantitative comparison to expert generated classifications to avoid concerns about data quality.
In coastal areas around the world, the dominant primary producers are benthic macrophytes, including seagrasses and macroalgae, that provide habitat structure and food for diverse and abundant ...populations and communities, and drive ecosystem processes. Seagrass meadows and macroalgal forests are economically central to coastal human communities, particularly in the developing world, contributing to fisheries yield, storm protection, blue carbon storage, and important cultural values. These services are threatened worldwide by human activities, with substantial areas of seagrass and kelp forests lost over the last half-century. Tracking status and trends in marine macrophyte cover and quality is an emerging priority for ocean and coastal management, but doing so has been challenged by limited coordination across the numerous efforts to monitor macrophytes, which vary widely in goals, methodologies, scales, capacity, governance approaches, and data availability. Here, we present a consensus assessment and recommendations on the current state of and opportunities for advancing global marine macrophyte observations, integrating contributions from a community of researchers with broad geographic and disciplinary expertise. The time is ripe to harmonize marine macrophyte observations by building on existing networks and identifying a core set of common metrics and approaches in sampling design, field measurements, taxonomy, governance, capacity building, and data management. A global macrophyte observation community would then be facilitated by ensuring rigorous documentation, archiving and open-access sharing of protocols and resources at all stages of workflow, from field surveys to data management, and provision of open-access data. Realizing these recommendations will produce more effective, efficient, and responsive observing, a more accurate global picture of change in macrophyte systems, and stronger international capacity for sustaining observations.
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