Predators control pests and increase yield across crop types and climates: a meta-analysis.

Pesticides have well-documented negative consequences to control crop pests, and natural predators are alternatives and can provide an ecosystem service as biological control agents. However, there remains considerable uncertainty regarding whether such biological control can be a widely applicable solution, especially given ongoing climatic variation and climate change. Here, we performed a meta-analysis focused on field studies with natural predators to explore broadly whether and how predators might control pests and in turn increase yield. We also contrasted across studies pest suppression by a single and multiple predators and how climate influence biological control. Predators reduced pest populations by 73% on average, and increased crop yield by 25% on average. Surprisingly, the impact of predators did not depend on whether there were many or a single predator species. Precipitation seasonality was a key climatic influence on biological control: as seasonality increased, the impact of predators on pest populations increased. Taken together, the positive contribution of predators in controlling pests and increasing yield, and the consistency of such responses in the face of precipitation variability, suggest that biocontrol has the potential to be an important part of pest management and increasing food supplies as the planet precipitation patterns become increasingly variable.

ZooTraits: An R shiny app for exploring animal trait data for ecological and evolutionary research.

Animal trait data are scattered across several datasets, making it challenging to compile and compare trait information across different groups. For plants, the TRY database has been an unwavering success for those ecologists interested in addressing how plant traits influence a wide variety of processes and patterns, but the same is not true for most animal taxonomic groups. Here, we introduce ZooTraits, a Shiny app designed to help users explore and obtain animal trait data for research in ecology and evolution. ZooTraits was developed to tackle the challenge of finding in a single site information of multiple trait datasets and facilitating access to traits by providing an easy-to-use, open-source platform. This app combines datasets centralized in the Open Trait Network, raw data from the AnimalTraits database, and trait information for animals compiled by Gonçalves-Souza et al. (2023, Ecology and Evolution 13, e10016). Importantly, the ZooTraits app can be accessed freely and provides a user-friendly interface through three functionalities that will allow users to easily visualize, compare, download, and upload trait data across the animal tree of life-ExploreTrait, FeedTrait, and GetTrait. By using ExploreTrait and GetTrait, users can explore, compare, and extract 3954 trait records from 23,394 species centralized in the Open Traits Network, and trait data for ~2000 species from the AnimalTraits database. The app summarizes trait information for numerous taxonomic groups within the Animal Kingdom, encompassing data from diverse aquatic and terrestrial ecosystems and various geographic regions worldwide. Moreover, ZooTraits enables researchers to upload trait information, serving as a hub for a continually expanding global trait database. By promoting the centralization of trait datasets and offering a platform for data sharing, ZooTraits is facilitating advancements in trait-based ecological and evolutionary studies. We hope that other trait databases will evolve to mirror the approach we have outlined here.

Bringing light onto the Raunkiæran shortfall: A comprehensive review of traits used in functional animal ecology.

Trait-based approaches elucidate the mechanisms underlying biodiversity response to, or effects on, the environment. Nevertheless, the Raunkiæran shortfall-the dearth of knowledge on species traits and their functionality-presents a challenge in the application of these approaches. We conducted a systematic review to investigate the trends and gaps in trait-based animal ecology in terms of taxonomic resolution, trait selection, ecosystem type, and geographical region. In addition, we suggest a set of crucial steps to guide trait selection and aid future research to conduct within and cross-taxon comparisons. We identified 1655 articles using virtually all animal groups published from 1999 to 2020. Studies were concentrated in vertebrates, terrestrial habitats, the Palearctic realm, and mostly investigated trophic and habitat dimensions. Additionally, they focused on response traits (79.4%) and largely ignored intraspecific variation (94.6%). Almost 36% of the data sets did not provide the rationale behind the selection of morphological traits. The main limitations of trait-based animal ecology were the use of trait averages and a rare inclusion of intraspecific variability. Nearly one-fifth of the studies based only on response traits conclude that trait diversity impacts ecosystem processes or services without justifying the connection between them or measuring them. We propose a guide for standardizing trait collection that includes the following: (i) determining the type of trait and the mechanism linking the trait to the environment, ecosystem, or the correlation between the environment, trait, and ecosystem, (ii) using a "periodic table of niches" to select the appropriate niche dimension to support a mechanistic trait selection, and (iii) selecting the relevant traits for each retained niche dimension. By addressing these gaps, trait-based animal ecology can become more predictive. This implies that future research will likely focus on collaborating to understand how environmental changes impact animals and their capacity to provide ecosystem services and goods.