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The experiment underlying the study provides a diversity gradient of 1–60 plant species, established in assemblages randomly chosen from a pool of species typical of Arrhenatheretum grasslands. Recently sown on fertile arable soil and maintained by weeding, this experiment is a highly artificial system that fails to meet the definition of semi-natural grasslands7. Four years after establishment, a management intensity gradient of one to four annual cuts and three fertilization levels was established in subplots randomly assigned to the 1–60-species plots. Data presented in this study were collected in the following year.Intensive management was thus imposed on plant species typical of Arrhenaterethum meadows, a plant community characterized by two annual cuts8. The potential effect size of increased management intensity is thus underestimated by applying the management to a plant community not adapted to it. More importantly, it is unlikely that the species-richness of high-diversity plots could be maintained under increased management intensity over longer periods. In fact, 22% of these subplots managed at very high intensity had to be excluded for missing or insufficient yield after only two years, indicating that their species did not persist under high defoliation frequency and fertilizer levels, even when competitors were excluded by weeding.While the discussion hardly addresses this crucial trade-off between management intensity and plant diversity, Schaub et al.6 do indicate that repeated resowing is likely to be necessary to maintain high diversity under increased management intensities. In contrast to permanent grasslands, whose species composition is shaped by site conditions and management, species selection in (re-)sown grasslands is a conscious choice. To be advantageous, mixtures have to show larger yields than the most productive monoculture, so-called transgressive overyielding. Transgressive overyielding is one of the reasons why mixtures, especially grass-clover mixtures, are frequently used in sown grasslands. A European-scale experiment demonstrated that four-species mixtures showed transgressive overyielding at a wide range of sites under intensive agricultural management9,10. Although Schaub et al.6 generally quantify the diversity effects in comparison to monocultures, they argue that grasslands with the high-diversity characteristic of semi-natural grasslands have benefits not only over monocultures but over low-diversity grasslands, such as the 1–8 species standard mixtures shown in Fig. 6 of their paper. However, their results fail to demonstrate that their high-diversity plots show any transgressive overyielding even over monocultures, not to speak of low-diversity mixtures. As species assemblages of the experiment are randomly drawn from the species pool, monocultures and low-diversity mixtures cannot be expected to include the most productive species or species combinations and thus cannot be used to assess transgressive overyielding. When transgressive overyielding was quantified for one- to eight-species plots of the same experiment under extensive management in 2003, it decreased with species number. While two-species mixtures showed a mean transgressive overyielding of 5%, eight-species mixtures were only 70% as productive as the corresponding best monoculture, on average11.Accordingly, the experimental design fails to capture the real trade-offs faced by grassland managers, either in permanent or in sown grassland. It cannot answer if high levels of diversity and the associated biodiversity benefits can be maintained under intensive management for a longer period than just a few years. Neither can it show a productivity benefit of high-diversity grassland assemblages compared to species-poor mixtures, or even monocultures, when in practice the sown species are deliberately chosen rather than randomly drawn from a species pool. While the underlying biodiversity experiment has made valuable contributions to our fundamental understanding of plant diversity effects on ecosystem functioning, it thus cannot be used to derive direct management recommendations for managed grassland. More

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Site descriptionWe define “kelp forest” as rocky-reef habitat within the 5–20 m depth range that supports dense stands of giant kelp, Macrocystis pyrifera. For this study, we considered the Santa Barbara Channel (SBC) to include the mainland region between Point Conception (−120.476° longitude, 34.455° latitude) and Point Mugu (−119.065° longitude, 34.079° latitude), as well the northern and southern sides of the four northern Channel Islands (Fig. 1). Although the SBC is a subset of the Southern California Bight, its strong west-east gradient in cold to warm temperature means the study system includes many of the kelp-forest species throughout California31. This means the SBC kelp-forest food web is a large “metaweb”, characterizing kelp forest meta-communities, rather than a site-specific web. In other words, the system includes cold water and warm water species that might not necessarily co-occur at a single site. However, there are site-specific food webs embedded in the metaweb at particular locations where a subset of species occur.Data sourcesOur goal was to assemble the food web using both published and novel empirical observations. To this end, we first used published data sets and species’ range boundaries to create free-living species lists. The initial list of fishes, algae, and free-living invertebrates was assembled from the Channel Islands National Park Kelp Forest Monitoring program (CINP KFM, annual reports available at https://irma.nps.gov/DataStore/SavedSearch/Profile/1508, accessed March 6, 2017, or visit https://www.nps.gov/im/medn/kelp-forest-communities.htm to contact David Kushner or Joshua Sprague) and the SBC Long Term Ecological Research program’s ongoing kelp-forest community timeseries (SBC LTER, https://sbclter.msi.ucsb.edu/data/catalog/, accessed March 12, 2017). We added to these lists using primary literature, technical reports (e.g., NOAA, USFW), direct observations, expert opinion, crowd-sourced observations (e.g., eBird.org), guidebooks, and grey literature. We sampled the local kelp forest zooplankton and the algae-associated small-invertebrate community, because these organisms were not well represented in surveys (see below).We created initial lists of parasite species using published literature and host-parasite databases. A systematic review was conducted to collect parasite records for each free-living species. We searched the Natural History Museum (NHM) of London host-parasite database (https://www.nhm.ac.uk/research-curation/scientific-resources/taxonomy-systematics/host-parasites/database/search.jsp), the FishPest database32, WoRMs (http://www.marinespecies.org/aphia.php?p = search), BIOSIS citation index (http://webofscience.com), and Google Scholar™(https://scholar.google.com/) (Genus + species + parasit*, expanded to Genus + parasit* if no records were found). For each host species, we recorded the number of records found in BIOSIS and NHM as an estimate of study effort. Although parasites are often reported at the host and parasite species level, we were often able to infer parasite and host life stages based on knowledge about life cycles. We added to these lists by sampling local fish and invertebrates, with a focus on hosts that were common in the system and not well-studied (see below). As for any food-web study, we were most interested in including common or important parasites, rather than rarities.Published diet observations (including in grey literature), direct observations, and inference were used to determine trophic links (see below).Free-living species sampling methodsCertain groups of free-living species were under-represented in published survey data, so we conducted sampling to assess species diversity in the following areas.Zooplankton towsWe conducted vertical zooplankton tows within kelp forests at two island locations (on the same date) and two mainland locations (repeated tows, four dates at one site, three of those dates at a second site, including one nighttime sampling date), for eight site by date samples30. While the vessel was at anchor within a kelp forest, a 30 cm diameter, 200 micron plankton net was dropped to the bottom and pulled to the surface at a rate of 0.33 m per second. Care was taken not to scrape the net against kelp plants. The collection jar attached to the net was kept vertical with a small lead weight to ensure that the net did not collect organisms on the way down to the bottom. The depth and time of collection were recorded30. We held collection jars on ice while in the field, then preserved specimens in 95% ethanol when we returned to the lab (within a few hours of collection). All organisms were counted and identified to species when possible, but some groups were identified to Order or Family, and then cross-checked with lists of known local species. If this was not possible, specimens were assigned to morphospecies, indicating they appeared to be a unique species based on morphology. Representative specimens from each species or morphospecies were photographed and measured.Giant kelp holdfastsGiant kelp holdfasts were sampled for free-living invertebrates. In the field, holdfast circumference and two slant height measures were taken, as well as basal stipe circumference. A subsample of approximately 25% of the holdfast was collected by SCUBA in a large plastic zip bag, and frozen until processing (n = 7). The samples were processed for organisms  > 500 microns, and holdfast tissue was weighed after organisms and debris were removed. Organisms were counted, identified to species or morphospecies when possible, and measured30. Some groups were identified to Family, and then matched to lists of known local species.Taxon-specific methods: gastropodsSmall gastropods are a diverse but overlooked group that lives in benthic turf algae. Algal clumps were collected haphazardly by either laying down a 7 × 7 cm quadrat and collecting all algae within the quadrat, or by collecting clumps of a particular alga and weighing at the lab. All gastropods were removed by hand under a stereomicroscope, counted, identified to species or morphospecies, measured, and photographed30.Parasitological collectionsWe collected fish and invertebrates and dissected them for parasites, with the goal of identifying the most common parasites in the food web. We targeted host groups that are known to transmit trophically-transmitted parasites in other systems. We collected most organisms from mainland sites, and sampled opportunistically at sites on Anacapa, Santa Cruz, and Santa Rosa islands30 (Fig. 2). A list of all species dissected and sample sizes is provided30.Fish collectionsWe prioritized collecting the most common and abundant fish species based on survey data from 2000–2014 (SBC LTER), as well as personal observation, expert opinion, and amount of parasite data in the literature. Other species (lower abundance or higher past study effort) were collected opportunistically. Fish were collected primarily by spear on SCUBA. Specific size classes were not targeted and the spear tips used were appropriate for the focal species. Small benthic fish were collected using dip nets. All fish were collected under UCSB IACUC protocol 549.2. Fish were either stored on ice and processed within 24 hours of collection or frozen until processing.Invertebrate collectionsInvertebrates are necessary intermediate hosts in many parasite life cycles, but relatively few parasite life cycles have been described in marine environments. We targeted invertebrate species that were abundant and potentially important as intermediate hosts for parasites. We did not collect sessile colonial taxa, such as hydroids, gorgonians, sponges, and tunicates, as they were not expected to be hosts for trophically transmitted parasites (but these hosts do merit further study). Most sampled invertebrates were gastropods and small crustaceans, as they host trophically-transmitted parasites in other food webs. Bivalves, large crustaceans, echinoderms, and polychaetes were also dissected. Large invertebrates were collected by hand or using a rock chisel and scraper when appropriate. Small invertebrates were sampled by collecting benthic substrates in plastic or fine mesh bags and removing organisms in the lab. Invertebrates were held live in flow-through seawater until the time of dissection or frozen until processing.Parasitological assessmentFor each host dissection, the exterior and all internal soft tissues were examined for parasite life stages. For larger species, entire host organs were usually searched by pressing soft tissues thin between two glass plates (“squashed”) and examining with a stereomicroscope. However, to increase sample size, bilaterally symmetric organs (e.g. gills) were examined from one randomly determined side, and large organs (e.g. muscle, liver) were subsampled in larger fishes. Small crustaceans and soft-bodied invertebrates were squashed whole. We identified gut contents where feasible to improve host diet data and inform parasite life cycles. We recorded host mass, length (or other species-appropriate measurement), collection method, and host condition at time of dissection (e.g. frozen, fresh). We counted and identified all parasites to the lowest possible taxonomic level and assigned a morphospecies code when species-level identification was not possible. Only a few putative parasites were excluded from additional analysis because they had no identifying features. Dissection data30 includes species not included in the full food web (see below for discussion of justifications for node inclusion).Node list assemblyNodes in the web included free-living species that used the water column and benthic zones within kelp forests as feeding habitat (including transient kelp-forest visitors but excluding rare and vagrant species) and parasites of those free-living species. Species was the preferred taxonomic unit, and life stages were included as separate nodes if that life stage was present in the system and had distinct trophic interactions from the adult stage. The fully-resolved free-living food web was constructed with life stage (e.g., larva, adult) nested within species (or morpho-species) (excepting benthic diatoms, planktonic diatoms, dinoflagellates, foraminifera, free-living nematodes, bacteria, free-living ciliates, copepod nauplii, filamentous algae, and invertebrate eggs, which were aggregate nodes). As various forms of detritus are important to energy flow in kelp forests, detritus was broken into four categories based on the typical feeding modes of detritivores and main sources of detritus: carrion, drift macroalgae, small mixed origin (such as would be consumed by a deposit or suspension feeder, with the recognition that this alone is a complex system deserving further resolution) and dissolved organic material. The “drift macroalgae” component was especially important to distinguish, as certain herbivores (sea urchins) are known to prefer drift algae as food but will turn to feeding on live algae when drift algae are sparse. This is a very distinct type of interaction from suspension feeders, which consume small particles of detritus that may be largely bacteria. “Parasites” are consumers which fit the seven types of parasitism defined by Lafferty and Kuris33. Commensal organisms were also recorded. We limited the parasite species list to metazoan species that use kelp-forest species as hosts for at least one stage in their life cycle. Bacterial, viral, fungal, and protozoan pathogens that are important in kelp-forest food webs merit inclusion in further work.We assigned each node a justification code (see below), confidence level, literature reference, and locality of the reference. Additional node metadata includes site on host (ecto-vs. endoparasite), taxonomic information, and life cycle information30 (see below). The node list contains columns with a species ID, and a species-by-stage ID. To work with the life-stage resolution, select the species-by-stage ID as the node identifier in analyses. To work with the species version, select the species ID as the node identifier in analyses. This will collapse all of the interactions to the species, so all of the trophic interactions are preserved and linked to the species node. Network analysis packages in R (such as Cheddar34) will automatically remove duplicate links if they are generated in this process.Life stages as nodesSpecies were partitioned into life-stage nodes (e.g., larva, juvenile, adult) if a species changed its trophic position from one stage to the other and multiple stages were present in the system. Whether or not a distinct life stage resided in the kelp forest was indicated by various data sources (e.g. dissections, published records), or inferred from species life history or trophic interactions. For example, amphipods brood offspring and have crawl-away juveniles. These juveniles remain in the kelp forest (rather than having a pelagic phase), and due to their small size are subject to different predators than adults (e.g. adults are eaten by fishes, while juveniles are eaten by hydroids). This was justification for juvenile amphipods being a distinct node from adult amphipods. On the other hand, many species have planktonic larvae that develop outside of the kelp forest, so only the adult stages were included at the species level. Larval stages of parasites were included if there was no feasible alternative for the focal host to become infected. We assumed that kelp-forest resident hosts became infected through life-cycle stages found within the kelp-forest food web, but that transient hosts could have acquired some parasites outside the kelp forest (e.g., if intermediate hosts were not known from the kelp forest). Likewise, presence of larval parasites in dissections was evidence for including adult stages. For some species, there was insufficient data on life history to infer additional stages. Metadata in the node list indicates whether parasites have additional life stages inside the kelp forest, outside, or unknown. When comparing this food web with others (which rarely separate species into life stages), using our data it is easy to collapse life-stage nodes into species nodes.Justifications for node inclusionWe used multiple lines of evidence to justify whether or not to include a node in the food web. Free-living species were included if they were known from the SBC (see site description above) and were indicated by the data sources described above (e.g. reports, surveys, published papers, guidebooks, expert opinion, etc.). Species lists from regional guidebooks included non-kelp-forest species, so these lists were compared with species lists from long-term monitoring surveys. Following the methods of Lafferty et al. 2006, we excluded most rare species (0.5, we assumed that an unobserved link actually occurred unless otherwise contradicted by species life history. We also then noted the probability of a false positive link (1 – ({widehat{F}}_{{rm{ij}}})). We further identified those few host and parasite species that generated substantial error in the network. To keep the overall error rate to More