Ecology

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05 November 2021

Whales’ gigantic appetites, climate fears — the week in infographics

Nature highlights three key infographics from the week in science and research.

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Climate scientists are scepticalThe momentous COP26 climate summit now under way in Glasgow, UK, represents one final opportunity for the governments of the world to craft a plan to meet their most ambitious goals for curbing climate change. Pledges are already flowing in, but the meeting has another week to run and much is still to be decided. Ahead of the summit, Nature conducted an anonymous survey of the 233 living authors of a climate-science report published in August by the Intergovernmental Panel on Climate Change, and received responses from 92 scientists — about 40% of the group. Their answers suggest strong scepticism that governments will markedly slow the pace of global warming, despite political promises made by international leaders as part of the landmark 2015 Paris climate agreement. Six in ten of the respondents, for example, said that they expect the world to warm by at least 3 °C by the end of the century, compared with conditions before the Industrial Revolution. That is far beyond the Paris agreement’s goal to limit warming to 1.5–2 °C.

Source: Nature analysis

Africa’s clinical trialsA shocking lack of COVID-19 vaccines in Africa, and the cost of existing treatments, means the continent really needs affordable, readily available COVID-19 drugs. These could reduce COVID-19 symptoms, lower the burden of disease on health-care systems and reduce deaths. The pandemic has given clinical research in Africa a boost: the Pan African Clinical Trials Registry recorded more clinical trials in 2020 than in 2019, and the number for 2021 is also on track to exceed 2019. But trials of COVID-19 drugs are still lacking in Africa, where they face infrastructure and recruitment challenges. One solution could be to establish a body to coordinate treatment trials on the continent.

Source: https://pactr.samrc.ac.za

The gluttony of whalesHow much do baleen whales, the largest known animals that have ever lived, eat? Three times as much as previously thought, report researchers who used cameras to study seven species of baleen whale. Writing in Nature, the researchers also suggest a feeding cycle involving iron and whale poo that could explain how such gluttony is possible. When whales eat iron-rich prey such as krill, they use the prey’s protein to make blubber — and defecate the iron-rich remains. Whale faeces might then provide a source of iron for microscopic marine algae called phytoplankton, and drive blooms of a type of plankton called diatoms. Diatoms, in turn, can move iron along the food chain when they are eaten by krill, which also excrete iron. Whales can further aid iron availability by mixing ocean waters through their vigorous tail movements.

doi: https://doi.org/10.1038/d41586-021-03066-5

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One of the striking features of the Anthropocene is a rapid degradation of natural ecosystems1,2, and an alarming decline of many species, which ultimately may lead to extinctions3,4,5. Whereas conserving ecosystem functions is increasingly recognised as a vital need for humans6,7,8, the interspecific interactions underpinning these functions are poorly understood9,10. However, conserving such interactions can be particularly important when taxa providing high-value ecosystem services are involved10,11.Ground beetles (Coleoptera: Carabidae) have been long known for their benefits in agroecosystems12,13. They play an important role in suppressing pests14, but several carabid species also consume seeds of herbaceous plants, making them a valuable asset for weed control as well15.Fungi are also of vital significance in most of the world’s terrestrial ecosystems16. Mycorrhizal fungi improve nutrient uptake by a large range of plant species through intimate and specialised associations17, other fungi play a crucial role in decomposition18, and yet others are pathogens of both crops and pests in agroecosystems19. Fungal parasitism is one of the crucial agents of evolution20.Fungi and carabids often co-occur, and they can potentially interact in many ways. The soil environment carabids often inhabit is a reservoir of fungal propagules where the beetles can feed on spores, hyphae or fruiting bodies21. They may also be responsible for dispersal of spores of certain fungi22. Several parasitic or entomopathogenic fungi are in an obligatory relationship with their beetle hosts23, therefore, the population decline of a ground beetle species could potentially lead to overlooked extinction cascades24. However, our knowledge of the fungal-carabid interactions is still limited concerning the frequency of these interactions and on how their exact nature affect the parties involved. Indeed, we do not even have a catalogue of the carabid-fungi interactions, and they have not yet been organized into a comprehensive database. Such a database would be of particular importance from an integrated pest management point of view because both fungi and carabids can deliver ecosystem services, but how their interactions, and potential synergies or antagonisms, influence the delivery of these services is poorly understood.In order to have a detailed overview of the interactions between Carabidae and the fungal kingdom, we collated a database containing previously reported associations between these taxa. Carabid and fungal species involved in the interaction, the type of the interaction (e. g. parasitic, pathogenic, mutualistic, or trophic interactions), the location (country) the interaction was reported from, and the publication source combined with detailed notes to each questionable entry comprised one record. Publications available in printed formats only were either digitized and data were extracted using semi-automatic text-mining processes, or they were manually screened. We aimed at possible completeness, using a wide range of databases and search engines and several languages to cover most of the published literature.Both ground beetle and fungal names were validated and their higher taxonomical classifications were also extracted. When it was possible, historical localities were converted to their current country names. The full bibliographical details were also stored in the database.The database covers a time-period from 1793 to 2020, spans over all geographic sub-regions defined by the United Nations (“UNSD — Methodology”, unstats.un.org. Retrieved 2020–10–11) with recorded associations from 129 countries. Our effort yielded 3,378 unique associations in 5,564 records between 1,776 carabid and 676 fungal species. Although rapidly developing molecular methods have largely facilitated the mapping of complex interaction networks in ecological studies25,26,27, due to the historic nature of our dataset, most of the records rely on traditional taxonomical identification. Yet, 16 records were based purely on metabarcoding studies; comments linked to these associations clearly identify them.Whilst we found relatively few pathogenic interactions, a great diversity between ectoparasitic Laboulbeniales fungi and carabids was revealed (Fig. 1). Soft bodied, cave-dwelling members of the Trechinae subfamily were particularly prone to these parasitic infections. Little information was available on mutualistic relationships but the presence of Yarrowia yeast reported from the gut of several carabid species28 is probably beneficial for both parties. The data show two distinct peaks in publications registering new associations, in the early 19th century and in the late 20th century (Fig. 2a) but the steady increase in the cumulative number of associations (Fig. 2b) suggests that further research is required to fully resolve this association network. Although we believe that most of the data published so far were collected, data submission will remain open to researchers wishing to contribute.Fig. 1The number of unique associations between Carabidae subfamilies and fungal classes. Side bar plots show the number of species in each subfamily/class recorded in our dataset.Full size imageFig. 2The number of recorded unique associations over time. Changes in the number of new records (a) and in the cumulative number (b) per year. Dark green lines indicate smoothed trends.Full size image More

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Design of species assemblages with contrasting species and functional diversitiesWe designed eight assemblages of native and perennial plants differing in terms of species richness (three levels), functional diversity of the traits involved in plant–arthropod interactions (two levels) and species identity (two sets of species). We combined these first two factors to define four categories of plant assemblages for further study:

Low functional diversity and medium species richness (14 species), LFMS;

High functional diversity and low species richness (9 species), HFLS;

High functional diversity and medium species richness (14 species), HFMS;

High functional diversity and high species richness (29 species), HFHS.

For each of these four categories, we designed two assemblages with different species identities, as described in the Supplementary information, resulting in eight plant assemblages in total. Functional characterization was based on a rough classification of plant species into functional groups (Supplementary Table S1), according to the mains traits involved in plant–species interactions easily accessible from databases: (1) flower resources, i.e. floral and extrafloral nectar or pollen, (2) accessibility of the resource, depending on flower shape, (3) availability of the resource, i.e. the flowering period and (4) flowering height.We generated the seed mixtures from commercial seeds, using ecotypes of local origin wherever possible (northern part of the Parisian basin, France). All applicable international, national, and institutional guidelines relevant for the use of plants were followed.Experimental designThe experiment was conducted between 2013 and 2017 in a 6.5-ha field at Grignon, France (N 48.837, E 1.956), on a deep loamy clay soil, in which soil depth decreased along a gradient from north to south. The field was divided in three blocks running from north to south to take this soil heterogeneity into account.Each assemblage was sown on a 6 × 44 m2 strip, with three replicates (Supplementary Fig. S2), with each assemblage represented once per block. A control treatment, sown with the same crop species as the rest of the field, was also included in the experimental design, resulting in nine experimental treatments in total. From the autumn of 2013 to the 2017 harvest, a winter barley–maize–faba bean–oilseed rape rotation was grown in the field. Crops were managed without insecticide treatment, but with a mean of 0.75 fungicide and 1.25 herbicide treatments per year. The observations were made in faba bean in 2016 and in oilseed rape in 2017.Botanical assessments and functional characterization of the plant communitiesBotanical assessments were conducted in April and June, in 2016 and 2017. In each treatment, the vegetation was assessed in 3 × 15 m2 plots at a position representative of the whole strip, generally in the center of the strip, to prevent edge effects. The percentage of the ground covered by each sown or spontaneously growing plant species was estimated by eye, by the same observer in each case. We noted the phenological development stage of each species in each treatment on an 11-point scale, to ensure an accurate assessment of flowering phenology. In the control plots (sown with the crop species only), we took into account the resources provided by weed species.The functional characterization of plant communities was based on the plant traits assumed to be involved in plant–parasitoid interactions6 (Supplementary Table S3). These traits were related to (1) the provision of trophic resources (presence of floral and extrafloral nectar, qualitative estimation of floral nectar), (2) the temporal availability of the resource (date of flowering onset and duration of flowering), (3) flower attractiveness (flower or inflorescence diameter, color, UV reflectance pattern), (4) nectar accessibility (flower opening diameter, corolla height, nectar depth and nectar tube diameter) and (5) the provision of physical habitats (leaf distribution, vegetative and flowering height). We measured most of these traits, particularly all those relating to flower morphology, phenology and nectar provision (see more detailed methods in the Supplementary information). Only a few were retrieved from previous publications and online databases: flower color and UV reflectance pattern, leaf distribution, vegetative and flower height.These traits were used (1) to determine the accessibility of nectar to each parasitoid (see below) and (2) to calculate the functional diversity of the plant assemblages. We calculated functional dispersion as the abundance-weighted mean distance of individual species from the centroid of all species in the trait space50 and Rao quadratic entropy51. Since these two parameters were highly correlated (Supplementary information), we considered only functional dispersion a measurement of functional diversity. The traits associated with the provision, availability and accessibility of nectar resources were measured for all the dicotyledonous species sown and for all spontaneous species occurring in the plant communities and flowering during parasitoid activity. Overall, considering the traits we measured and those retrieved from databases, the trait matrix was complete for more than 95% of the species, accounting for 99.6% of total plant cover.Assessment of the levels of parasitism on five herbivorous pests of faba bean and oilseed rapeIn the adjacent crop, 5 and 20 m from the wildflower strip, we measured the level of parasitism in one herbivorous pest of faba bean (2016) and four herbivorous pests of oilseed rape (2017). We chose a distance close to the strip (5 m) to prevent confounding effects with the other adjacent strips, knowing that their effect is the strongest in the first few meters from the strip52. A further distance was also chosen (20 m) to determine whether the strips promoted biological control at field level, while taking into account the spatial constraint of the distance between strips (50 m between opposing strips).All the protocols are detailed in the Supplementary information. Parasitism was assessed in Bruchus rufimanus larvae after the visual examination of faba bean seeds after harvest. For oilseed rape, we collected and reared Ceutorhynchus pallidactylus and Psylliodes chrysocephala larvae until the adult stage or parasitoid emergence. In Brassicogethes aeneus larvae, parasitism was assessed by observing the eggs of Tersilochus heterocerus in the host larvae in oilseed rape flowers. Finally, after oilseed rape harvest, we retrieved cocoons of Dasineura brassicae from the soil, which we dissected, recording the number of cocoons occupied by parasitoids.Measurement of parasitoid traitsWe carried out morphological measurements on parasitoids (Supplementary Table S4), to determine their degree of access to the nectar provided by plants, as a function of the size of their mouthparts and head, which limit corolla penetration, using an approach analogous to that of van Rijn and Wäckers16. Parasitoid individuals, preserved in 70% ethanol, were obtained (1) from our rearing experiments (for Bruchus rufimanus, Psylliodes chrysocephala and Ceutorhynchus pallidactylus), (2) from the dissection of cocoons for Dasineura brassicae or (3) by field sampling in the flower strips with a sweep net in April 2017 to collect Tersilochus heterocerus, parasitoids of Brassicogethes aeneus identified with53. For each parasitoid species or morphospecies, we measured, on at least 10 individuals, proboscis length, proboscis width (at mid-length)54 and the maximum dorsal head width, including the eyes. Observations were carried out under a binocular microscope (Leica M80, 60 ×) linked to a video camera (Moticam 10, Motic), and measurements were made with ImageJ v1.50i digital image analysis software (National Institute of Health, Bethesda, http://imagej.nih.gov/ij).Nectar resources for parasitoidsWe estimated the amount of nectar provided by the plants by summing, for each flower strip corresponding to a treatment, the percent cover of plants providing available and accessible nectar, as assessed in vegetation surveys. Separate estimates were obtained for each parasitoid species or morphospecies.Plant species producing floral or extrafloral nectar were first selected on the basis of the observations detailed in the botanical assessment section. Nectar was considered to be available when it was produced during the period of parasitoid activity (Supplementary Table S4), by selecting species at the flowering stage or producing extrafloral nectar based on the phenological observations carried out during the botanical assessments. Nectar accessibility depended on morphological matching between plants and insects. Extrafloral nectar, which is not enclosed in a perianth, but produced on bracts or stipules, was considered to be accessible. We determined the accessibility of floral nectar with a mechanistic trait-based approach (Supplementary Information), by adapting the geometric model proposed by van Rijn and Wäckers16. A decision tree was built (Fig. 2) to take into account the three constraints limiting nectar accessibility: (1) ability of the insect to penetrate the flower, which is dependent on head size and flower opening, (2) ability to reach the nectar, which depends on proboscis length, nectar depth and corolla height, and (3) proboscis width and nectar tube diameter in the presence of nectar.Statistical analysesWe investigated the effects of the different plant assemblages on the rates of parasitism for the five herbivorous species, at 5 and 20 m from the flower strip, considered separately as individual response variables. We first tested the effect of each assemblage (nine treatments as factors) on parasitism rates. We used generalized linear mixed models in the lme package55, with a binomial error distribution. The models included plot (n = 9 flower strips × 3 replicates = 27), strip (1–3) or block (1–3) as a random effect. All models were run three times with each random effect variable, and the model giving the lowest AIC was retained. Strips consistently yielded the lowest AIC. This factor was therefore introduced as a random effect variable for all statistical analyses. The significance of the fixed effects was evaluated by type II analyses of deviance with Wald chi-squared tests from the Anova function from the car package56. If a significant effect (p value  More

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