Forest canopy insects are safer from predators in the tropics than at higher latitudes

Domain: chemistry
Published: 2026-02-27
Editorial outcome: major_revision

Abstract
Theory suggests that predation pressure decreases with latitude. To test this hypothesis, we studied predation for insect on forest understory and canopy vegetation using six canopy cranes across a latitudinal gradient (51°N to 34°S). We find contrasting predation patterns: predation is highest in the canopy at high latitudes, whereas it decreases towards low latitudes, where it is more pronounced in the understory. These differential latitudinal trends are driven by shifts in the relative roles of bird and arthropod predators, alongside variations in natural prey abundance. Our findings highlight how predator-prey dynamics differ across forest strata and challenge assumptions about latitudinal predation gradients.

Introduction
Biotic interactions are expected to be stronger and more important at lower latitudes 1-3, mirroring the fundamental pattern of increasing species diversity towards the tropics 4,5. Similarly, steep gradients in biotic interactions are predicted along vertical gradients within forests, with biotic interactions expected to be stronger in the canopy, as environmental conditions and species composition differ markedly between the understory and canopy. While the research of latitudinal patterns in plant-herbivore interactions has seen a proliferation of data and theoretical developments 7-10, predator-prey interactions along latitudinal gradients have received comparatively less attention 11,12. Roslin et al. 11 conducted a global experiment using dummy plasticine caterpillars across a range of habitats, from forests to tundra, where bite marks allowed predator identification. Their study showed an increase in predation by arthropods towards the equator, while predation rate (Box 1) by vertebrates did not exhibit any latitudinal pattern. Using a comparable method but limited to forest habitats, Zvereva et al. 12 confirmed an equatorial peak in predation rate by arthropods but observed the opposite latitudinal trend in vertebrate predation rate. Irrespective to the type of predators (i.e., summarizing predation rate by all types of predators), both global studies consistently observed higher predation rate in tropical regions 11,12. However, Zvereva et al. 12 focused exclusively on the forest understory, and Roslin et al. 11 included various habitats where caterpillars were always placed near ground level. Consequently, both studies are potentially missing differences in predation between the forest understory and canopy, where most plant and insect biomass and interactions are expected to be concentrated 11-13.

Forest canopies are hotspots for biodiversity and focal points for biodiversity processes 6,13, but also the “last frontiers” of ecological research with limited access and knowledge 14,15. There are pronounced gradients in microclimatic conditions between forest strata, with temperature and light availability increasing towards canopy, while humidity being generally higher in the understory. These differences influence resource availability and the distribution and activity of both prey and predators, adding other dimensions to the predation patterns 14, 15. In turn, forest canopies typically harbour species-rich and distinct communities 14. While some studies have confirmed that vertical gradient patterns are steeper than those observed along latitudinal gradients 6, 17, others have shown that vertical stratification is less pronounced than previously believed 18. Previous research along vertical forest strata showed predation rate by birds and ants 19 as well as predation pressure by birds 20 to be higher in tropical canopies than in tropical understories. This could be explained by the fact that the total prey abundance, expressed as the density of arthropods per leaf area multiplied by available leaf area, is expected to be higher in the canopy due to the greater availability of plant biomass 15.

Endotherms, and insectivorous birds in particular, may track the local food availability through various spatial movements: from the understory to the canopy, regionally along elevation gradients, and globally through latitudinal migrations 21. Therefore, we might expect them to impose relatively homogenous predation pressure across latitudes, or even elevated predation pressure, in breeding grounds at temperate latitudes where they migrate to breed 21. In ectotherms, however, the increase in predation towards the canopies and tropics may be amplified by an increase in temperature, as they are more dependent on it.

Assuming that predator density and activity levels are higher in the canopy than in the understory, we hypothesise that the predation rate will also be relatively higher in the canopy than in the understory. This should be especially true at low latitudes where the differences between canopy and understory in terms of predator density, prey availability, and environmental conditions are expected to be more pronounced. To test the hypothesis of higher predation rates in the tropics and forest canopies, we employ six research canopy cranes at sites spanning from 51.2°N to 33.62°S (Supplementary Table S1) to access both the forest canopy (10-35m above ground) and understory (ca. 2-3 m) at each location 6. We place 3,413 dummy caterpillars modelled from green plasticine 11 on the foliage and monitor them over 72 hours, i.e., for 10,239 caterpillar-days. Additionally, we survey local communities of birds and ants to test how the species richness and abundance of predators correlated with predation rate. To obtain an insight into patterns of predation pressure, we consider density and abundance of natural prey, the abundance of predators, and predation rate. Here we show contrasting patterns in predation: predation being highest in the canopy at high latitudes, whereas decreasing towards low latitudes, where it is more pronounced in the understory. These differential latitudinal trends are driven by shifts in the relative roles of bird and arthropod predators, alongside variations in natural prey abundance.

Results
Total predation rates (in 72 hours) varied with the interaction between latitude and forest strata (Fig. 1, Supplementary Table S3). At low latitudes, caterpillars had a higher probability of being attacked when placed in the understory. In contrast, caterpillars had a higher probability of being attacked when placed in the canopy at high latitudes. In understories, the probability of a caterpillar being attacked decreased from 26.7% (95% CI = 10.9, 51.7) at ca. equatorial KAK site to 7.63 % (95% CI = 2.6, 20.2) at 51ºN (LAK) and to 19.8 % (95% CI = 7.5, 42.8) at 34ºS (EUC) (Supplementary Table S4). Thus, at the highest latitude studied (LAK), a caterpillar in the understory was more than three times more likely to be attacked than an understory caterpillar at the ca. equatorial site (KAK). In canopies, we observed the opposite trend; the probability of a canopy caterpillar being attacked increased, as modelled using a second-degree polynomial, from 5% (95% CI = 1.7, 13.3) at KAK site to 52.8% (95% CI = 25.9, 77.1) at the highest latitude studied (LAK) (Supplementary Table S4). In other words, a caterpillar was about ten times more likely to be attacked in temperate canopies than in tropical canopies. Based on our data from both strata of the six study sites, the mean predation (averaged across strata) rate on dummy caterpillars was slightly higher in temperate than in tropical regions (Fig. 1). This suggests previous studies conducted exclusively in the understory may have underestimated the overall predation rate on dummy caterpillars in temperate regions, where predation is higher in the canopy than in the understory.

From a total of 724 attacked caterpillars, 504 were attacked by arthropods, 165 by birds, and 55 by mammals. While understory predation rates by birds had a slight peak in the tropical reagions, canopy predation rates by birds increased from 0.9% (95% CI = 0.3, 3.1) at tropical KAK to 15.5% (95% CI = 5.3, 27.3) and 5.7% (95% CI = 2.1, 14.1) in the northernmost (LAK) and southernmost (EUC) locations, respectively (Fig. 2, Supplementary Table S4). The arthropod predation rates in forest understories peaked near the equator and decreased towards the northern pole (but not towards the south pole) from 23.8% (95% CI = 10.7, 44.2) at KAK to 10.5% (95% CI = 4.1, 22.6) at LAK. The arthropod predation rates in forest canopies showed practically the opposite trend and increased towards both poles from 4.7% (95% CI = 1.9, 11.7) at BUB to 36.4% (95% CI = 17.6, 60) at EUC and 26.4% (95% CI = 12.1, 48.7) at LAK (Fig. 2, Supplementary Table S4).

In concordance with Roslin et al. 11 and in contrast to Zvereva et al. 12, we detected no systematic, and low, trend in the predation rate by birds along the latitudinal gradient in forest understories. By expanding our research into forest canopies, we found that predation rates by birds are higher at high latitudes than in the tropics. This suggests that previous results 11,12 underestimated overall predation rates by birds in temperate regions, likely due to differences in the caterpillars' location (>0.5 m vs. 2 m above ground) and potentially also due to the duration of the experiments (4 days vs. 64 days). Caterpillars closer to the ground may experience fewer bird attacks in the vertically complex forests of the tropics compared to those in temperate habitats. Longer exposure may then cause birds to habituate to dummy caterpillars and reduce their attacks, especially in temperate forests where birds tend to occupy stable territories.

As expected, the abundance of birds was stable across latitude. However, more birds were detected in understories than canopies in the tropics, with the opposite trend observed at temperate sites. Overall, predation rates by birds correlated significantly with the number of insectivorous birds (P = 0.018, r = 0.664, t = 1.78) and tended to be associated with their biomass (Fig.3).

Our survey of predators confirmed the well-known trend of rapid increase in the abundance of ants towards the tropics (Fig. 3) 11,12. In the tropics, there were higher ant densities in canopies than in understories whereas we found the opposite trend at our temperate sites 22,23. Thus, the ant abundance did not correlate with the number of attacks caused by arthropods (Fig. 3). Attacks by arthropods other than ants could explain the observed trends across latitudes and strata. For example, the majority (99%) of wasps were captured 15m above ground in temperate forest canopies 24, and predation caused by wasps was higher in canopy than in understory 25. Moreover, while the majority of ants rely at least partially on predation, and some are obligate predators, certain ants in tropical canopies may be herbivorous 23,26. Unfortunately, the method used does not reliably distinguish bite marks made by ants from those made by other arthropods 27, 28.

To interpret our results on predation rates in the context of ecological importance of global predation pressure trends, it is essential to consider the abundance of prey.

The ecological importance of predation pressure is a product of predation rate and prey abundance 11. To the best of our knowledge, there are no studies that quantify latitudinal trends in arthropod abundance in individual forest strata. Our data show that at the temperate and mild-temperate sites (LAK, TOM, EUC), the density of arthropods per foliage area were consistently ca. 3-4x higher in the understory than in the canopy (Fig. 3), whereas densities of arthropods did not differ between the two strata at tropical sites (Daintree Forest and Kakoba) and were comparable with the densities in temperate canopies (Fig. 3). Furthermore, when we analysed available data on leaf area per forest floor (leaf area indices), we found nearly no latitudinal trend in the amount of understory leaf area. In contrast, the amount of canopy leaf area peaked in the tropics and was consistently higher than the amount of leaf area in the understory at most latitudes (Supplementary Fig. S2). Although predation rates were equally high in the canopy and understory, predation pressure is likely greater in the canopy due to higher prey density and greater leaf area per forest floor unit in this stratum.

Some caveats of our study include the fact that we compare predation rates captured during a sharp spring peak in arthropod abundance in temperate forests to those captured during the lower but stable arthropod abundance in the tropics 29. We used approximately two dummy caterpillars per 1m2 of foliage. This is a typical density for temperate canopies in spring as well as any season or stratum in a tropical forest. But it is lower than the spring density observed in the temperate forest understory that reached 15 caterpillars per 1m2 in Tomakomai during May (Supplementary Table S2). Hence, predation rate in temperate understories could be underestimated as birds might prefer abundant real caterpillars. To account for the effects of varying prey abundance, the next logical step would include designing longer experiments covering entire growing seasons. Another point to consider is the lower number of generations per year in temperate arthropods (1-2) in comparison to the tropical ones (5-6, but 10-12 for some species), which might result in higher annual production of arthropods in the tropics. Despite this having no effect on the predation rate in the current study, it can influence the impact of predation on prey. From the perspective of arthropods, the predation pressure in both the canopy and understory could be higher in temperate forests if the relative abundances of predators and prey were considered. Real arthropods also accumulate the risk of being predated over the developmental time which is slightly shorter in the warmer climates than in cooler regions 11. Considering the overall results of our study, we might expect even higher pressure on caterpillars in cooler regions, where they have longer development times and face higher predation rates.

Overall, our study revealed that forest strata play an important role in shaping trophic interactions across latitudinal gradients. Studies on the vertical dimensions of predation and the focus on predator identity have revealed clear patterns in selection pressure on lower trophic levels. These patterns highlight how multiple environmental gradients simultaneously influence the strength of trophic interactions 30-33, including predation e.g. 11,12,34. Furthermore, we show that the relative importance of different predator groups differs across forest strata and latitudinal gradients, and therefore may differentially impact the mechanisms that regulate herbivore abundance. Whether or not these patterns translate into net herbivory damage remains unresolved because plant defences and productivity also play their part. Our study further highlights the great potential of large-scale, empirical studies that employ consistent methods, and the value of using the network of canopy cranes in order to access forest canopies at sites across the world. Although we admit that working from these cranes is neither easy nor cheap, they represent the most efficient means for accessing these fascinating habitats of great scientific and conservation value.

Methods
Study sites
Our study was conducted at 6 out of 15 canopy cranes available worldwide at the time of our study 6, spanning a latitudinal gradient between 51.2 and -33.62 degrees. The cranes were situated in undisturbed lowland forests typical for each region (33 – 152 m asl, except for the Bubeng crane at 707 m asl). At each study site, the experiment was conducted during late spring or summer (Supplementary Table S1). Using standardized protocols for surveying predation rates (Supplementary Methods) and communities of predators in forest canopies and understories in several continents, we tested the strength of predator-prey interactions. Additionally, we related the biomass and abundance of predators (birds and ants) and density and abundance of prey items (arthropod herbivores) to the observed predation rates.

Measurement of predation rate using plasticine dummy caterpillars
To study predation rates, we loosely followed the protocol by Roslin et al. 11. Predation rates were monitored by standardised plasticine dummies of lepidopteran caterpillars 11,35,28 made from odourless, non-toxic coloured plasticine (Koh-in-Noor in an equal mixture of two colours: green and light green and Newclay Products, Newton Abbot, UK, Supplementary Table S1), by pressing it through a sugar paste extruder (Sugarcraft, Amazon), which is the typical size of a late instar caterpillars (2.5-3 x 25-30 mm, Supplementary Fig. S1). Dummy caterpillars resembled undefended, green geometrid larvae. This type of caterpillar dummy is often used in predation rate studies, as it represents one of the most abundant Lepidoptera morphologies found in forests throughout the world. Geometridae are among the largest insect families, with almost 25,000 described species 36,37. Geometrid caterpillars, and in particular their plasticine dummies, may not be attractive to all visually and chemically orienting predators. Hence, this study focuses on a standardized comparison of predation rate across latitudes and forest strata by a standardized repeatable method, rather than a measurement of absolute predation rates.

At each study site, 600 to 640 caterpillars were exposed. Five dummy caterpillars were attached to each of the 64 tree saplings or 60-64 tree branches in canopies. All saplings were at least 10 m apart and branches in the canopy were at least 4 m apart. As an exception, in Leipzig, 3 caterpillars were attached per sapling and branch, which were all at least 4 m apart. Each caterpillar within the sapling or branch was separated from the others by at least 30 cm. We used entomological pins (or Loctite 401 Super glue, Henkel, Düsseldorf, DE in Leipzig) to attach the caterpillars to the small branch or stalk of a leaf which was neither damaged nor touching any other branch or leaf, to avoid scratches on the caterpillars. The caterpillars were exposed on 1.5 - 2 m tall saplings in the understory and at 13 - 30 m in the upper forest canopy layer, depending on the site. We avoided conducting the experiment on days with heavy rain or weather conditions that could be considered unusual for the given sites.

We checked the caterpillars 72 hours after deployment (with several exemptions when the caterpillars were checked after 96 hours). Based on tooth, beak, mandibular or radular marks, all feeding damage on caterpillars was attributed to one of six predator groups: birds, mammals, arthropods, lizards, or gastropods (i.e., snails or slugs). Caterpillars that were not retrieved were scored as lost and, together with the caterpillars eaten by gastropods, were excluded from the analyses (but see Supplementary Methods for additional analyses). As the scoring of feeding marks involves some subjectivity 27,28, only well-trained researchers checked the caterpillars and they also took photos of the marks, which were later confirmed by a single observer (KS).

Survey of predator communities
Birds: We used point-counts and passive recordings to estimate the abundance and biomass of birds at each forest stratum for each study site. Point counts were carried out at 16 points regularly spaced along a 2,350‐m transect (successive points were 150 ± 5 m apart, to avoid overlap, and up to 120 m apart in elevation). All birds seen or heard within a fixed radial distance of 0–50 m (estimated or measured by a laser rangefinder) were recorded 38 and their height above ground was noted. We started surveys 15 min before sunrise, each count lasted 15 min so that all 16 points were surveyed before 11:00 (i.e., a survey on all 16 points represents one replication in time). All points and all study sites were surveyed equally, and the survey was replicated six times (i.e., in 6 days).

Further, a songmeter SM3BAT (Wildlife Acoustics) with one external acoustic (SMM_A1 Wildlife Acoustic) microphone was set to record the first 10 min of every 30 min time period (10 min recording, 20 min sleeping) throughout the whole day. The songmeter was set up in the forest canopy for a month (at the same height where caterpillars were exposed) and in the forest understory (1.5 m above ground) for another month of the survey. In Leipzig, two Song Meters were set up for a month simultaneously in both strata. We used manual identification of the bird calls from the songmeter recordings. Acoustic data from songmeter were used as an equivalent of eight spatial sampling points (i.e., 17th to 24th point), and 48-15 minutes of recordings were randomly selected from the whole set of recordings collected between 6 AM and 6 PM. Thus, the recordings from the Song Meter (one third of the dataset) and the point counts (two thirds of the dataset) were combined to calculate the abundance of insectivorous birds.

Later, we used the Handbook of the birds of the world 39 to obtain the body weight and feeding guild of each bird species to determine the biomass of insectivorous predators at each forest strata. We calculated abundances of insectivorous birds per transect (i.e., 16+8 points, 0.78 ha *18 = 18.72 ha) from which we calculated the mean (across six days) abundance of insectivorous birds per 10 ha. Considering the vertical distribution of birds, we then obtained abundances of insectivorous birds separately for each stratum and we multiplied this by the body weight of individual bird species to obtain the biomass of insectivorous birds per 10 ha (in kg).

Ants: We used baits to survey the ant communities potentially responsible for the attacks on our dummy caterpillars 40. The baits were exposed on eight randomly selected sapling and canopy branches of each of the eight focal plant species (64 samples in understory and 64 samples in canopy). Different saplings and branches were used for the ant surveys to avoid disturbance of the experiment. Moreover, the chosen saplings and branches were randomly scattered between those used for the exposure of the dummy caterpillars, having similar size and amount of foliage. Two types of baits (each roughly 2-3 cm3) were used: 1) tuna chunks in vegetable oil (Giana) and 2) cotton balls soaked in sugar solution. Baits were attached to each selected sapling or canopy branch separated by at least 20 cm, and the positions of the baits were alternated (i.e., lower or higher on the trunk of saplings, closer to or further from the trunk on the canopy branches, or altering positions on the branch forks if present). Baits were checked after 4 hours of exposure, ants were visually morphotyped and the number of individuals per morphotype were counted. All or up to five individuals of each morphotype occupying the bait were collected into 2 ml vials filled with DNA grade ethanol (99%). Due to limited access to species-level identification of ants, only total abundances were used in this report.

Survey of arthropod communities
Arthropod communities were collected by beating (on 1.5 x 1.5 m white beating sheets) from 24 branches (3 branches per each of the 8 plant species) in the canopy and 40 saplings in the understory (5 saplings per each of the 8 plant species) at each study site. The sampling was repeated at the beginning and at the peak of season (i.e., ±14 days before and ca. 2 months after the survey of predation rate). The branches were located on the same adult trees and in proximity of the branches where dummy caterpillars were exposed. In the understory, saplings were located randomly between the saplings on which we placed the dummy caterpillars and were of similar height. For each of the chosen branches and saplings, we measured the mean area of a single leaf and made three independent estimates of the number of leaves prior to beating. We identified all collected arthropods >1 mm into feeding guilds and calculated their abundance per m2 of foliage (Supplementary Table S2).

Analyses
We used a set of generalised linear mixed-effects models (GLMMs) and their comparison based on the AICc values to investigate how latitude and forest strata relate to predation rates. The response variable was the number of attacked versus non-attacked dummy caterpillars, per branch, excluding those caterpillars that were lost or attacked by gastropods. Assuming binomial-distribution errors and a logit-link function, we modelled this response as a function of latitude, forest strata and their interaction. Latitude was included either as signed latitude (to distinguish hemispheres) or as absolute latitude, fitted as a first- or second-degree polynomial. We fitted separate models for predation rate by birds, by arthropod predators and by total predation rate by all predators. Site, plant species and branch were included as random factors to capture the structure of variation provided by the study design. For each response variable, we first built a null model with all the random factors plus a fixed intercept and then compared it with combinations of latitude and/or forest strata. Latitude was included either as signed latitude (to distinguish hemispheres) or as absolute latitude, fitted as a first- or second-degree polynomial. Additionally, we calculated Pearson correlations between predation rate and the abundances of predators and of herbivorous arthropods, as prey items, to investigate their relationships. All models were fitted in R 4.5.1 41, using package lme4, and predictions from the most parsimonious models were calculated with package merTools.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This manuscript refers to two earlier studies, one by Roslin et al. (2017) on higher predation risk for insect prey at low latitudes and elevations, using green plasticine caterpillar mimics, the other one by Zvereva et al. (2019) on opposite latitudinal response patterns of bird and arthropod predators to differently coloured plasticine caterpillar mimics. Here, the study bears on predation patterns in two different forest strata (understory and canopy), also using green plasticine mimics. This introduces an interesting additional component to the global picture. This promising approach, however, is disappoing for many reasons. At this stage, I do not believe that the manuscript is ready for publication anywhere.\n\nGeneral comments\nThe methods are poorly explained, referring to other studies, or skipping important elements, and the additional information is far from providing clarity, both in the text and in the text and in the supplementary material. Among other data, a full account of all bird, ant and other arthropod species identified during the study is necessary. The study also relies on too many assumptions that the reader must take as granted.\n1. The use of mimics has its limitations, and this is not particularly discussed.\n- There is a difference between a bird's attack, most of the time lethal, and an ant's attack, not necessarily lethal. In addition, a bird is likely to remember an unpalatable prey and to form rapidly a negative search image; this is not necessarily true for an ant. Also, according to the bird species, this avoidance image can vary.\n- Predation on mimics is influenced by the abundance of real prey. This has been briefly considered in the discussion (\"In contrast to predation rate (equally high in canopy as in understory), predation pressure is likely higher in canopy, influenced by prey density and by leaf area per forest floor (both higher in canopy\") but discarded, nevertheless.\n- The lost mimics could have been removed by birds, but here they were consistently discarded in the analysis, which could have biased the results. Unless I missed it, the proportion of lost mimics has not been given.\n- I also wonder how mimics were counted when bearing the marks of several predators (say, bird AND arthropod). This has not been discussed.\n- Finally, whilst Figure 1C in the Extended data gives a clear view of a bird attack, Fig. 1E is so small that the arthropod attacks are hardly distinguishable.\n2. Predators are treated as undescribed items: \"birds\", \"ants\" and \"arthropods\". Each of these categories include species with different feeding regimes, which have not been considered. The authors announce (L273) that \"data on diversity and more detailed data on abundances of individual ant species will be published elsewhere\". As these detailed data influence the analysis developed here, they should have been fully given and analysed in this study\n3. Predation pressure is defined in Box 1 as \"a function of predation rate and density of prey and predators\". The functon(s) should be defined.\n\nDetailed remarks\n- L16 et sqq. the Abstract is not very explicative, in particular the sentence \"This pattern was driven by change in relative importance of predation by birds versus arthropods and its interplay with the abundance of the natural prey\"\n- L46. \"plant-herbivore interactions\": actually a \"latitudinal patterns in plant-herbivore interactions\". Idem for \"the predator-prey interactions\" below.\n- L62. \"Vertical climatic gradients within a forest thus add other dimensions to the predation patterns\". Vertical climatic gradients within a forest have not been discussed so far, and the authors expect the readers to take this as a given. How does microclimate vary along a vertical gradient in a forest? Which other factors vary along this gradient? In addition, \"thus\" is not justified here since climatic gradients have not been discussed.\n- L63. \"via abundance of prey items and predators 14, Box 1).\". Box 1 does in no way illustrate the sentence above relative to vertical climatic gradients\n- L64. \"(e.g., 17,18, showing the vertical gradients...\" What is the relevance of these reference here? Refs 6 and 17, on the other hand, are relevant later in this sentence.\n- L68. \"total abundance of prey, is expected to be higher in the canopy due to greater canopy plant biomass.\". Any quantitative data, or reference, supporting this statement?\n- L69. \"predation by ectotherms, such as arthropods, should be more temperature-dependent\". This statement relies on the climatic gradient alluded to previously, and which was not substantiated.\n- L73. \"and also globally, by migration\" Please explain how migration addresses vertical gradients within a forest.\n- L73. \"Considering that the trends among different predator groups fade\". I do not understand. What are the \"trends among predator groups\"? What do you mean by \"fade\"?\n- L75. \"we can therefore hypothesise a homogenous overall predation pressure across latitudes, or even elevated predation pressure, in breeding grounds at temperate latitudes\". This hypothesis should be more strongly argumented.\n- L78. \"Thus, we can hypothesise\". The arguments (ectotherm behaviour, migrations) leading to this hypothesis (predation rate higher in the canopy) does not appear fully convincing.\n- L79. \"This should be especially true at low latitudes\". Explain why.\n- L99. \"Based on our data from the six study sites, mean predation rate (averaged across strata) was equally high in canopy as in understory (...). This means that previous studies conducted only in understory underestimated the overall predation rate in temperate regions, where it is significantly higher in canopy than in understory\". Again, this is under the assumption that predation rates on the mimics reflected predation rates on real prey, thus discounting learned avoidance among birds, and discounting the fact that all bite marks on a mimic caterpillar are not equivalent (a bird's mark does not equal an ant's).\n- L104. \"Globally, more caterpillars were attacked by predatory arthropods than by vertebrates.\". See my remark above regarding negative search image among birds, and about lost mimics that could be attributed to birds.\n- L122. \"tended to be associated with their abundance (Fig.2, Extended Data Table 1) \" Fig. 2 shows proportions, not abundance. Table 1 does not provide this information.\n- L129. \"Attacks by other arthropods than ants, or feeding specializations of ants,...\" More details regarding the ant surveys could have provided information in this respect.\n- L143. \"Although a comprehensive assessment goes beyond the current study\". The current study would have greatly benefited from a more comprehensive assessment. As it stands, the study is frustratingly poor in data, which makes it difficult to interpret the results.\n- L146. \"but consistently higher canopy leaf area in canopy than in understory\" Check this sentence.\n- L155. \"But it is lower than a spring density in temperate forest canopy that reached 40 caterpillars per 1m2 in the Tomakomai canopy in May.\" We need the data.\n- L157. \"predation rate in temperate canopies could be underestimated as birds might prefer abundant real caterpillars.\" As said before, this spoils the results to a large extent.\n- L165. \"Real arthropods accumulate the risk of being predated over the developmental time which varies along latitude less than predation rate\". Roslin et al. (2017) took this into account; I do not see that you did.\n- L168. \"despite being previously neglected dimension of predation studies\" Check this sentence.\n- L189. \"Using standardised protocols for surveying predation rate and communities of predators...\" More details about these \"standardised protocols\" are necessary.\n- L221. \"Based on tooth, beak, mandibular 221 or radular marks...\" As said already, detailed pictures of these marks would be welcome in the Supplementary to allow the readers to appreciate at which degree of precision the attributions were done.\n- L223. \"Caterpillars that were not retrieved were scored as lost\" As also said already, how did you make sure that they were not taken or dislodged by birds?\n- L234. \"All birds seen or heard within a fixed radial distance\" How could you determine the range at which you heard a bird?\n- L240. \"Further, a Song Meter (...) was set\" Was there any attempt to compare song meter and direct measurements , and if so, why are they not reported ?\n- L242. \"The Song Meter was set up in the forest canopy for the first month of the experiment (at the same height where caterpillars were exposed)\" What is the range of a song meter, and how did you ascertain that the recordings belonged to the stratum where the recorder was set up?\n- L273. \"data on diversity and more detailed data on abundances of individual ant species will be published elsewhere.\". Trying to split the data this way makes the present study less reliable, because, as mentioned above and among many other things, the diversity of ant diets would influence the interpretation of the results.\nJean-Claude Grégoire", "reviewer_2": "In their manuscript, “Forest canopy insects are safer from predators in the tropics than at higher latitudes,” the Authors report on a distributed study of predation rate differences between forest canopies and understory. The Authors hypothesized that predation rates and predation pressure will be higher in the canopy due to the higher abundance and diversity of predators in this stratum of forests. They measured predation rates at six study sites, primarily in Oceania and Pacific East Asia, using standardized caterpillar models made of plasticine. Novelly, they used canopy cranes at these sites to deploy plasticine caterpillars both at the frequently studied ground level and high in the forest canopy (10-35m, depending on local canopy height). The main result was that understory and canopy predation show opposing latitudinal patterns, with understory predation peaking at equatorial latitudes and canopy predation increasing towards the poles, determined using a generalized linear mixed model. The Authors conducted supporting analyses to separate predation patterns out between vertebrate and invertebrate predators, then related predation patterns to the abundances of these groups with a correlation analysis.\n\nI think this study question is important, and the Authors have found a clever way to study predation differences between forest strata despite the inherent logistical challenges of doing this kind of work. Probing the causal predictors of variation in predation rates is badly needed to continue making sense of the increasingly popular plasticine prey model approach, and I applaud the Authors work to quantify both the predator and prey communities at their sites. Teasing apart the causes of latitudinal patterns will need this kind of close attention to mechanism.\n\nMy enthusiasm for these ideas, the study questions, and the Authors’ creativity in attempting to answer them was tempered by several methodological and analytical decisions that I feel cannot justify the main conclusions. I explain my reasons below in hopes of giving the Authors an avenue to address my concerns.\n\nFirst, the main result concerning contrasting latitudinal gradients is not supported by any inferential statistics test. In text, the predation rate differences are reported without statistics (e.g., p-values, R^2). In the corresponding figures (Figs. 1 and 2), the fitted regression line from the generalized linear mixed model is shown without any depiction of the uncertainty (e.g., standard errors, confidence intervals). Formal statistical tests are especially important because of how few latitudinal replicates were possible (a constraint beyond the Authors’ control).\n\nSecond, the statistical model underlying the main result is inadequately described to determine its suitability for the experimental design. Lines 290-293 describe the response variable as a proportion, but immediately below the response for the statistical model is described as following a binomial distribution (i.e., counts and trials). The proportion vs. count/trial response structures are both valid ways to process these data, but the count/trial approach is much more statistically powerful. For the random effects, only a term for “plant species” that the plasticine caterpillars were attached to is described. This is a good practice, but I the absence of (1) a site-level random intercept and (2) a cluster or group-level random intercept are quite glaring. The multiple trials at each site are not independent replications of that latitude. Likewise, the risk of attack is not independent between dummies that were attached to the same branch. Failing to account for these in the statistical model is pseudoreplication. Finally, Extended Data Table 2 reports AIC model comparisons between a very elaborate set of candidate models. This is not described in the Methods. More importantly, it is not appropriate to conduct null hypothesis tests on model coefficients after choosing the model with AIC (Tredennick et al. 2021 Ecology doi: 10.1002/ecy.3336). Doing so will inflate the type 1 error by an unknowable amount, so the p-values cannot be trusted for inference nor corrected to remedy the problem. I strongly recommend the Authors focus on a minimal set of fixed effects predictors along with the random effects necessary to account for their experimental design. Six latitudinal replicates will almost certainly not offer enough statistical power to detect polynomial or other non-linear effects of latitude.\n\nThird, there was a substantial design difference in plasticine caterpillar aggregation at one site, Leipzig. Fewer caterpillars were attached to each branch (3 vs. 5 elsewhere), and these groups were much closer together (4m vs. 10m elsewhere). The Authors don’t present data to test for impacts of these differences on predation rates. I would be less concerned for a dataset with more latitudinal replicates and if the methodology difference was at a middle latitude (i.e., less influence on the slope). But here, the unusual site is only one of six, and it is at one of the most extreme latitudes where it has greatest leverage to affect the overall slope.\n\nLastly, I include a few line-specific comments where more minor edits would improve clarity:\n19: The use of “global” to describe this small set of sites is overreaching.\n44-45: I don’t follow the logic of this sentence. Why do latitudinal gradients in biotic interactions lead us to predict similar gradients in forests?\n45-47: This sentence is worded generally, but needs clarification that the advancements are in the area of latitudinal patterns. There has been a lot of recent theory and empirical work for predator-prey interactions in other contexts.\n55: Roslin et al. included a range of habitat types, not just forests. I think it’s reasonable to charge that Zvereva et al. may have underestimated predation by omitting canopy habitat because all their sites were in forest. Criticizing Roslin et al. for not standardizing habitats is completely fair, but it seems disingenuous to claim that they underestimated predation by not including forest canopy. In fact sites were shrubland and tundra, so the dummy caterpillars were in fact only deployed in the “canopy” at these low-growing sites much like the Authors varied the canopy height based on local vegetation height. Maybe “near ground level” is a better way to collectively describe what has been done by these two previous studies, limiting the novelty claims about underestimated predation to comparisons with Zvereva et al.?\n63-64: “these expectations” isn’t clear. Do you mean patterns in biodiversity, patterns in the strength of interactions, or both?\n72: Repeated words “local” and “locally”\n73-77: I found this sentence very difficult to parse due to the many clauses it contains. Break it up.\n91-92: I don’t understand this result. Were the canopy caterpillars attacked more in the temperate zone versus the tropics? Or is the comparison that in temperate zones, the canopy caterpillars were attacked more than those in the understory?\n97: What is meant by “non-linearly” here? The [0,1] boundaries of the probability scale mean that every fitted regression will be curvilinear if there is any effect of the continuous predictor. It’s not clear whether the Authors included a non-linear predictor term in their model such that the relationship on the link scale is also non-linear. Consider clarifying the method and result in this part.\n117-119: I don’t understand how experiment duration could interfere with the detection of geographic patterns in predation. This claim needs further explanation.\n121-124: This sentence states that the result both is and is not statistically significant."}, "author_response": "Response: We have improved the methodological descriptions to the best of our ability, addressing any areas that required clarification. Regarding data availability, we are happy to share the bird data. However, we hope it is understandable that we cannot provide species-level identifications for ants and spiders, as they were never identified to that level. Nevertheless, we provide relevant data, including caterpillar densities, herbivorous arthropod densities, and ant abundances. The focus of our manuscript is on predation rates, and we believe the reported patterns remain valid regardless of the precise identity of the arthropods present. What matters in this context is whether predators have more or fewer natural prey options to select from, rather than the specific species composition.\n\n1. The use of mimics has its limitations, and this is not particularly discussed.\n- There is a difference between a bird's attack, most of the time lethal, and an ant's attack, not necessarily lethal. In addition, a bird is likely to remember an unpalatable prey and to form rapidly a negative search image; this is not necessarily true for an ant. Also, according to the bird species, this avoidance image can vary.\nResponse: We would like to clarify that our method was never intended to compare predation between different predator groups, as the method is not suited for it. We clearly stated that now in Supplementary methods: “To study the predation rate, we used dummy caterpillars. Despite some criticism of this method (2), researchers generally accept that the attack rates on plasticine models - although they do not reflect the absolute values of predation pressure - can be useful in comparisons between different localities (3)”. Instead, it provides a relative measure of predation rates within a single predator group across sites. Therefore, we cannot directly address the first claim regarding differences in lethality between bird and ant attacks. Throughout the text, we have made it clear that our focus is on the latitudinal patterns of bird and arthropod predation, rather than an explicit comparison between them.\nRegarding predator learning and avoidance, some sedentary birds may indeed learn to recognize and avoid unpalatable prey. However, based on our extensive experience with this method, birds encountering plasticine dummy caterpillars tend to peck at them repeatedly rather than avoid them outright. Frustrated birds often attempt to attack another dummy before eventually losing interest, typically only after several days during the breeding season. To minimize any potential habituation effects, we limited the experiment to 72 hours per site, which we strongly believe was too short for birds to develop avoidance behavior. Moreover, the chances of an individual bird encountering multiple dummy caterpillars were minimal. We again specified addressed this problem in the Supplementary Methods, where we added a whole paragraph and several references”.\nWe acknowledge that different predator species may respond to dummy caterpillars in varying ways. However, because our method does not allow predator species identification and predator communities differ entirely between study sites, accounting for these species-specific responses is not feasible. Therefore, we analyze and discuss our results at the community level.\n\n- Predation on mimics is influenced by the abundance of real prey. This has been briefly considered in the discussion (\"In contrast to predation rate (equally high in canopy as in understory), predation pressure is likely higher in canopy, influenced by prey density and by leaf area per forest floor (both higher in canopy\") but discarded, nevertheless.\nResponse: We would like to clarify that we did not discard this aspect but rather considered it in our interpretation. Our findings show that higher densities of natural prey were recorded in areas where we also observed higher predation rates. This suggests that even in environments with abundant prey, predators still attacked a significant number of dummy caterpillars, potentially leading to an underestimation of the actual predation rate.\nOverall, our results indicate higher predation in the canopies of temperate forests, and we believe that the true predation pressure there could be even greater than our data suggest.\n\n- The lost mimics could have been removed by birds, but here they were consistently discarded in the analysis, which could have biased the results. Unless I missed it, the proportion of lost mimics has not been given.\nResponse: We were providing the numbers of lost mimics in the Supplementary Methods. To respond to the concern, we rerun all the analyses once again, considering the lost caterpillars being removed by birds. We added several paragraphs of the text to the Supplementary Methods and results into Supplementary Table S5 and S6. The results clearly show that the pattern doesn’t change significantly, and the results are nearly identical.\n\n- I also wonder how mimics were counted when bearing the marks of several predators (say, bird AND arthropod). This has not been discussed.\nResponse: We indeed did not discuss it in depth, as there were only 7 caterpillars attacked both by birds and arthropods. We were mentioning it in the Supplementary Methods. As we were treating the whole sapling or a branch as a sample, such predation even was simply added to the count of the dead caterpillars. E.g. in the situation where 5 caterpillars were exposed, and 2 attacked by 2 types of predators, we calculated the ratio as 3 alive and 2 dead.\n\n- Finally, whilst Figure 1C in the Extended data gives a clear view of a bird attack, Fig. 1E is so small that the arthropod attacks are hardly distinguishable.\nResponse: We improved Figure S1, added another bite to that figure, and enlarged part C and improved it’s contrast. We also added to the Figure a link to additional figures in the GitHub repository.\nhttps://github.com/KatkaSam/CATEX_BABE/blob/master/figures/Supplementary_Bites_DummyPrey.pdf\n\n2. Predators are treated as undescribed items: \"birds\", \"ants\" and \"arthropods\". Each of these categories include species with different feeding regimes, which have not been considered. The authors announce (L273) that \"data on diversity and more detailed data on abundances of individual ant species will be published elsewhere\". As these detailed data influence the analysis developed here, they should have been fully given and analysed in this study\nResponse: To distinguish the predation attacks into these three categories is the only safe and robust method, as shown by previous studies (we specify it also in the Supplementary Methods). This is a common limitation of this methodology, which is hard to overcome. We acknowledge that the groups considered include animals with different feeding regimes, but we believe that the important aspect is the potential death of the caterpillar attacked by a bird. Surely, attacks by ants and arthropods might be less lethal, but the method was never designed and aimed to compare the predation between groups of predators (which we now stress more). The data on birds and their feeding guilds were provided in the associated GitHub dataset. Unfortunately, data on abundances of ants are available only, not on their identifications.\n\n3. Predation pressure is defined in Box 1 as \"a function of predation rate and density of prey and predators\". The functon(s) should be defined.\nResponse: We used the term function in a general sense rather than referring to specific mathematical formulations describing predator-prey interactions. Given the scope, and focus on predation rate, of our work, it is not necessary to define multiple possible equations. In a simplified form, predation pressure can be understood as the product of predation rate, prey density, and predator density. We would like to keep the word as it is, or we can potentially change it to “interaction”, which should be more neutral.\n\nDetailed remarks\n- L16 et sqq. the Abstract is not very explicative, in particular the sentence \"This pattern was driven by change in relative importance of predation by birds versus arthropods and its interplay with the abundance of the natural prey\"\nResponse: We rewrote the sentence and made the abstract more explicative\n\n- L46. \"plant-herbivore interactions\": actually a \"latitudinal patterns in plant-herbivore interactions\". Idem for \"the predator-prey interactions\" below.\nResponse: We appreciate the reviewer’s comment and have revised the sentence to clarify the context. The updated sentence now reads: \"While the research of latitudinal patterns in plant-herbivore interactions has seen a proliferation of data and theoretical developments 7-10, predator-prey interactions along latitudinal gradients have received comparatively less attention 11,12.\"\n\n- L62. \"Vertical climatic gradients within a forest thus add other dimensions to the predation patterns\". Vertical climatic gradients within a forest have not been discussed so far, and the authors expect the readers to take this as a given. How does microclimate vary along a vertical gradient in a forest? Which other factors vary along this gradient? In addition, \"thus\" is not justified here since climatic gradients have not been discussed.\nResponse: As a part of other edits in the surrounding text, the whole sentence was removed. However, in the changed sentences, now we discuss the climatic gradient in more detail, as well as we focus on the microclimate along vertical gradient. Now lines 47-50\n\n- L63. \"via abundance of prey items and predators 14, Box 1).\". Box 1 does in no way illustrate the sentence above relative to vertical climatic gradients\nResponse: We aimed to link the box to the terms predation rate and predation, which were in the sentences. However, now we moved the link to the Box one much higher in the text, after we mention the word predation rate for the first time. The link is now in the sentence: “Their study showed an increase in predation by arthropods towards the equator, while predation rate (Box 1) by vertebrates did not exhibit any latitudinal pattern.” Line 55 now\n\n- L64. \"(e.g., 17,18, showing the vertical gradients...\" What is the relevance of these reference here? Refs 6 and 17, on the other hand, are relevant later in this sentence.\nResponse: We are sorry, we reorganized the references. A mistake occurred there due to numbering and a broken hyperlink to reference.\n\n- L68. \"total abundance of prey, is expected to be higher in the canopy due to greater canopy plant biomass.\". Any quantitative data, or reference, supporting this statement?\nResponse: We added the references which were already included in the surrounding sentences also to this one, where it is relevant. The sentence now sounds: “This could be explained by the fact that the density of prey per leaf area, i.e. the total prey abundance, is expected to be higher in the canopy due to the greater availability of plant biomass 15.” A potentially good reference showing the pattern is also Basset et al. 2015, however we can’t add it due to word and reference limit. Basset, Y., Cizek, L., Cuénoud, P., Didham, R. K., Novotny, V., Ødegaard, F., ... & Leponce, M. (2015). Arthropod distribution in a tropical rainforest: tackling a four dimensional puzzle. PloS one, 10(12), e0144110. Who says that wary explicitly\n\n- L69. \"predation by ectotherms, such as arthropods, should be more temperature-dependent\". This statement relies on the climatic gradient alluded to previously, and which was not substantiated.\nResponse: As stated above, we extended the description of the temperature gradients now, and clarified the text. Lines 79-83\n\n- L73. \"and also globally, by migration\" Please explain how migration addresses vertical gradients within a forest.\nResponse: See the point below – it refers to the same sentence\n\n- L73. \"Considering that the trends among different predator groups fade\". I do not understand. What are the \"trends among predator groups\"? What do you mean by \"fade\"?\nResponse: We agree that the sentence was difficult to understand. The word migration was associated with the later part of the complex sentence. We deleted it and moved it higher in the paragraph in a different form. Now it reads: Endotherms, and insectivorous birds in particular, may be able to follow the local food availability through various spatial movements: from understory to canopy, regionally along elevation gradients, and globally through latitudinal migrations 21.\n\n- L75. \"we can therefore hypothesise a homogenous overall predation pressure across latitudes, or even elevated predation pressure, in breeding grounds at temperate latitudes\". This hypothesis should be more strongly argumented.\nResponse: As we reworded the sentences about the temperature gradients, and the migration, we adjusted also this sentence. Lines 79-83 now\n\n- L78. \"Thus, we can hypothesise\". The arguments (ectotherm behaviour, migrations) leading to this hypothesis (predation rate higher in the canopy) does not appear fully convincing.\nResponse: First of all, we reworded the earlier sentences, which improved the reasoning. We then restructured this sentence, placing the argument first and avoiding the word “thus”. The sentence now reads: “Assuming that predator density and activity levels are higher in the canopy, we hypothesize that the predation rate will be also relatively higher in the canopy than in the understory.”\n\n- L79. \"This should be especially true at low latitudes\". Explain why.\nResponse: We added the explanation and split the previous two sentences. The sentence now reads: “This should be especially true at low latitudes where the differences between canopy and understory in terms of predator density, prey availability, and environmental conditions are expected to be more pronounced.” Line 88\n\n- L99. \"Based on our data from the six study sites, mean predation rate (averaged across strata) was equally high in canopy as in understory (...). This means that previous studies conducted only in understory underestimated the overall predation rate in temperate regions, where it is significantly higher in canopy than in understory\". Again, this is under the assumption that predation rates on the mimics reflected predation rates on real prey, thus discounting learned avoidance among birds, and discounting the fact that all bite marks on a mimic caterpillar are not equivalent (a bird's mark does not equal an ant's).\nResponse: We specified that the conclusions are relevant to the caterpillar mimics only by adding the specification. If space allows, we would like to also add an additional sentence: This conclusion assumes that predation rates on mimic caterpillars accurately reflect those on real prey, while also acknowledging that not all bite marks on mimic caterpillars are equivalent, as birds and ants may leave different types of marks.\n\n- L104. \"Globally, more caterpillars were attacked by predatory arthropods than by vertebrates.\". See my remark above regarding negative search image among birds, and about lost mimics that could be attributed to birds.\nResponse: We appreciate the reviewer’s comment. While we cannot entirely rule out the possibility of a negative search image effect among birds in natural settings, our extensive aviary experiments suggest the opposite. Birds exposed to dummy caterpillars made from the same material as in this study did not avoid attacking them. On the contrary, they appeared unsatisfied with the “food” and often proceeded to attack additional dummy caterpillars, potentially increasing predation rates rather than decreasing them. Only highly sedentary birds might learn to avoid plasticine caterpillars after several days. However, this should not affect our results, as our experiment lasted only 72 hours, much shorter than the week-long duration typical in similar studies. We added several sentences and references to clear these concerns, into the Supplementary material and methods.\nTo address the other concern, we re-ran all analyses and compared two datasets: one where bird attacks were treated conservatively (i.e., all lost caterpillars were considered non-avian losses) and another where all lost caterpillars were attributed to bird predation. We have described our approach and provided the results in Tables S3 and S4 of the supplementary material.\nFinally, we removed the original sentence, as we had no intention of comparing predation between predators. While we meant it to be purely informative, it indeed sounded like part of the conclusions. The original sentence sounded: “Globally, more caterpillars were attacked by predatory arthropods than by vertebrates.”\n\n- L122. \"tended to be associated with their abundance (Fig.2, Extended Data Table 1) \" Fig. 2 shows proportions, not abundance. Table 1 does not provide this information.\nResponse: We are terribly sorry; this sentence was all messed up. First, there was a 0 missing in the number (P = 0.0184 not P = 0.184). The same result was correctly mentioned in the legend of Figure 3 (i.e., the correct reference). Indeed, Extended Data Table 1 is not relevant here. We fixed the sentence so now it states: Overall, predation rates caused by birds correlated significantly with the number of insectivorous birds (P = 0.018, r = 0.664) and tended to be associated with their biomass (Fig.3).\n\n- L129. \"Attacks by other arthropods than ants, or feeding specializations of ants,...\" More details regarding the ant surveys could have provided information in this respect.\nResponse: As we are not able to provide the ant identification, we removed the part of the sentence saying … “or feeding specializations of ants” … and kept the sentence simplified, pointing out only the factor which we believe is more important. The sentences now say: “Attacks by arthropods other than ants could explain the observed trends across latitudes and strata. For example, the majority (99%) of wasps were captured 15m above ground in temperate forest canopies 26, and predation caused by wasps was higher in canopy than in understory 27.” Also, as the following sentences stated, the identification of ant attacks is impossible, as it is rather difficult to distinguish the arthropods from each other. We wrote several methodologies focusing on this aspect and we refer to them here. Line 146-147\n\n- L143. \"Although a comprehensive assessment goes beyond the current study\". The current study would have greatly benefited from a more comprehensive assessment. As it stands, the study is frustratingly poor in data, which makes it difficult to interpret the results.\nResponse: We appreciate the reviewer’s feedback and recognize that a more comprehensive dataset could provide deeper insights. However, the study was designed to specifically address predation rates within the constraints of time, resources, and feasibility. Unlike many other studies on predation, we additionally also surveyed predator and arthropod densities, adding valuable context to our findings. All data collected during the project are openly available in the associated GitHub repository. We rewrote the relevant sentences as: “Furthermore, when we analyzed available data on leaf area per forest floor (leaf area indices), we found nearly no latitudinal trend in the amount of understory leaf area. In contrast, the amount of canopy leaf area peaked in the tropics and was consistently higher than the amount of leaf area in the understory at most latitudes (Extended Data Fig. 2).”\n\n- L146. \"but consistently higher canopy leaf area in canopy than in understory\" Check this sentence.\nAs a part of the changes linked to the point above, we restructured the whole sentence. Now it says: “Furthermore, when we analysed available data on leaf area per forest floor (leaf area indices), we found nearly no latitudinal trend in the amount of understory leaf area. In contrast, the amount of canopy leaf area peaked in the tropics and was consistently higher than the amount of leaf area in the understory at most latitudes (Supplementary Fig. S2).” Line 161-165\n\n- L155. \"But it is lower than a spring density in temperate forest understories that reached 15 caterpillars per 1m2 in the Tomakomai in May.\" We need the data.\nResponse: We originally had the data placed only in the associated GitHub folder. However, we simplified the table and placed it also to the Supplementary data to Table S3 now.\n\n- L157. \"predation rate in temperate understories could be underestimated as birds might prefer abundant real caterpillars.\" As said before, this spoils the results to a large extent.\nResponse: Another important consideration is that in temperate forests, birds may have had a broader selection of natural caterpillars to prey on, with our models making up only a small fraction of the available prey. This could have led to an underestimation of predation rates—both in comparison to other sites and to natural predation rates—since we standardized caterpillar densities across all sites, using relatively low densities to reflect naturally lower-density sites.\nThis underestimation would be most pronounced in temperate forests, where natural caterpillar densities were higher than our model densities, yet we still recorded higher predation rates. If our method underestimated predation in these areas, it would imply that the actual relative importance of predators in temperate canopies is even greater than reported.\nOur key argument is that studies focusing solely on understories likely underestimate predation rates in temperate canopies, and that predation rates in temperate regions are actually higher than previously assumed. If we acknowledge that our method may have underestimated predation in temperate understories, it would only strengthen our conclusion rather than weaken it.\n\n- L165. \"Real arthropods accumulate the risk of being predated over the developmental time which varies along latitude less than predation rate\". Roslin et al. (2017) took this into account; I do not see that you did.\nResponse: In Roslin et al.'s study, we collected literature data showing that caterpillars develop slightly faster in warmer climates than in colder ones. This was done because we were worried that in tropical regions, higher predation rate is balanced by faster development and thus escape from predation. However, that study demonstrated that predation rates decrease more rapidly with latitude than the increase in developmental time from the equator to temperate regions.\nOur current study, however, incorporates the predation in the canopy and reveals an overall higher predation rate in temperate regions compared to the tropics (i.e. opposite to Roslin’s study). This suggests that caterpillars near the equator not only have shorter lifespans but also face lower overall predation risk. In contrast, caterpillars in temperate regions live longer and experience a higher likelihood of predation.\nImportantly, our results highlight the significant role of the canopy and its interaction with latitude. However, comparable data on caterpillar developmental times within the canopy vs. in understory are not available to our knowledge. We have thus reworded the sentence to clarify that we referenced Roslin’s et al. study solely for the information that caterpillars develop slightly faster in warmer regions.\n\n- L168. \"despite being previously neglected dimension of predation studies\" Check this sentence.\nResponse: Thank you for spotting this, we rewrote the sentence completely. Line 188 – 189.\n\n- L189. \"Using standardised protocols for surveying predation rate and communities of predators...\" More details about these \"standardised protocols\" are necessary.\nResponse: We would like to point out, that the methods are in detail described in the Supplementary Material. We therefore add the reference to it. If there is something more specific, we could add, we will be happy to do it. For now. We do not know what specific details are needed\n\n- L221. \"Based on tooth, beak, mandibular 221 or radular marks...\" As said already, detailed pictures of these marks would be welcome in the Supplementary to allow the readers to appreciate at which degree of precision the attributions were done.\nResponse: We had several pictures of the bites in the Supplement Fig. S1. We also published earlier on a guide for identification of the bite (Low et al. 2014), so we believed that referring to it would be sufficient. However, we now added the file with the bites to the GitHub repository. A direct link to it is provided in Figure S1. And also here:\nhttps://github.com/KatkaSam/CATEX_BABE/blob/master/figures/Supplementary_Bites_DummyPrey.pdf\n\n- L223. \"Caterpillars that were not retrieved were scored as lost\" As also said already, how did you make sure that they were not taken or dislodged by birds?\nResponse: Unfortunately, we are not able to say. However, we tried to model an extreme situation, when all caterpillars lost would be taken by birds. We reanalyzed all data and we found no significant differences in results. Most importantly, the latitudinal pattern in predation by birds did not change at all. We now provide additional results in the Supplementary methods, and report the new results in Tables S5 and S6.\n\n- L234. \"All birds seen or heard within a fixed radial distance\" How could you determine the range at which you heard a bird?\nResponse: Estimating the distance from the observer to a singing bird is a common practice. It requires some experience, and when the observer is uncertain, they identify the tree where the bird is perched and measure the distance to it using a laser rangefinder. Alternatively, in unfamiliar terrain, we first measured and marked distances to nearby trees with spray, noting the distances in multiple directions. This helped to calibrate our estimates and improve accuracy. In the original sentence, we specifically stated that we \"estimated or measured\" distances, which we believe sufficiently described the activity.\nTo clarify this in the Supplementary Methods, we also added: \"Practically, this means that we first measured and marked distances to several trees around the point and agreed on which trees (or natural features) were within the 50m range. During the survey, this allowed us to more easily determine whether a singing bird was perched within the designated range.\"\n\n- L240. \"Further, a songmeter (...) was set\" Was there any attempt to compare song meter and direct measurements , and if so, why are they not reported ?\nResponse: We never intended to compare data from both methods. Instead, we used both approaches to optimize our survey efforts throughout the day. While point counts are effective for morning bird surveys, they may miss species that are more active later. At the same time, other surveys—such as ant sampling—needed to be conducted during the warmer parts of the day. To avoid missing birds, we supplemented point counts with passive song meters. However, song meters are less effective during peak morning chorus due to overlapping calls, making species identification challenging. In contrast, they perform better in the afternoon when bird vocalizations are less frequent. In the Supplementary Methods, we now clarify: “Our goal was not to compare the two methods but to obtain more comprehensive data, as morning surveys might miss birds active later in the day.”\n\n- L242. \"The songmeter was set up in the forest canopy for the first month of the experiment (at the same height where caterpillars were exposed)\" What is the range of a song meter, and how did you ascertain that the recordings belonged to the stratum where the recorder was set up?\nResponse: This is indeed a very difficult question. Even the providers of the equipment say “This is a very difficult question to answer. It can vary widely depending on the volume and direction of the source, the humidity, foliage, and other factors. You may be able to hear an owl from half a mile away, but not be able to hear a mouse from a distance of fifty feet. As a rule of thumb, if you can hear it with your ears, the microphone will also hear it.” As we are interested in the insectivorous birds only, which are small and do not move far away, we believe that as long as the recorder detected it, it was not further than 50 m from the recorder.\nTo limit the recordings to canopy and understory respectively, we used the directional external microphones, which do not record in specific directions, so we pointed them to the canopy and just horizontally, 1.5 above ground. It typically works well, and records just relatively small surrounding at the specific height.\nWe added to the extended methods in the supplementary material the sentence: ” The directional acoustic microphones we used were designed to capture sounds with greater accuracy from the direction they were pointed. By positioning them horizontally, we aimed to ensure that the recorded sounds corresponded to the target strata. According to the manufacturer, the microphones' detection range closely resembles that of human hearing, suggesting that the recorded birds were likely at a similar distance to those we would detect during point counts.”\nHere we provide a graph showing the probability of detection of a flycatcher by songmeter vs. human. Figure from: Yip, D. A., Leston, L., Bayne, E. M., Sólymos, P., & Grover, A. (2017). Experimentally derived detection distances from audio recordings and human observers enable integrated analysis of point count data. Avian Conservation and Ecology, 12(1), 11.\n\n- L273. \"data on diversity and more detailed data on abundances of individual ant species will be published elsewhere.\". Trying to split the data this way makes the present study less reliable, because, as mentioned above and among many other things, the diversity of ant diets would influence the interpretation of the results.\nResponse: We agree that this wording was not accurate, and we were not supposed to bring it up. However, the reality is that our colleague, who was hired to do identifications of the ants dropped from the project and did not deliver the species identifications. As it is generally very difficult to find a specialist able to identify the ant species from six very different study sites, all work will be delayed for at least several years. We are of course hoping to have the identifications done later, but at this point we need to move on with the abundance of the ants only. With respect to results, identity of the ants should not be playing a role, as majority of the ants are generalist feeders, predators and scavangers, and some are strict predators.\nBelow, I provide figures from two separate studies conducted at the same time along the same elevational gradient. The results indicate that attacks by ants on the plasticine caterpillars correlated better with the abundances of ants, and even more with presence/absence of the ants on the experimental trees, than with ant species richness.\n\nResponse: We are first thankful for the nice summary and for the intention to help us to improve the manuscript. We tried our best to respond to all concerns below.\n\nFirst, the main result concerning contrasting latitudinal gradients is not supported by any inferential statistics test. In text, the predation rate differences are reported without statistics (e.g., p-values, R^2). In the corresponding figures (Figs. 1 and 2), the fitted regression line from the generalized linear mixed model is shown without any depiction of the uncertainty (e.g., standard errors, confidence intervals). Formal statistical tests are especially important because of how few latitudinal replicates were possible (a constraint beyond the Authors’ control).\nResponse: We are sorry for not clearly stating the statistical approaches used, which we now tried to clarify throughout. All the confidence intervals are mentioned in the Supplementary Table S4, where they might have been overlooked (originally Table S3). Upon the request now, we plot them now also in all graphs and we report them in brackets in the main text. For example, in sentence: “In understories, the probability of a caterpillar being attacked decreased from 26.4% (95% CI: 12.23, 47.74) at KAK … etc. “\n\nSecond, the statistical model underlying the main result is inadequately described to determine its suitability for the experimental design. Lines 290-293 describe the response variable as a proportion, but immediately below the response for the statistical model is described as following a binomial distribution (i.e., counts and trials). The proportion vs. count/trial response structures are both valid ways to process these data, but the count/trial approach is much more statistically powerful.\nResponse: The response variable was modeled using a binomial distribution, with the number of caterpillars attacked (counts) as the numerator and the number of exposed caterpillars (trials) as the denominator. This approach accounts for the count/trial structure of the data and leverages the greater statistical power of this method compared to proportions. Caterpillars lost were excluded from both the count of attacks and the trials. We used for example for bird predation: glmer(cbind(Bird72, Survived72H)~poly(Lat,2)*Strata + (1|Species), data = dataset_catex, family = \"binomial\"). We added part of the explanation to the Supplementary Methods and all scripts and data are available in the associated GitHub folder.\n\nFor the random effects, only a term for “plant species” that the plasticine caterpillars were attached to is described. This is a good practice, but I the absence of (1) a site-level random intercept and (2) a cluster or group-level random intercept are quite glaring. The multiple trials at each site are not independent replications of that latitude. Likewise, the risk of attack is not independent between dummies that were attached to the same branch. Failing to account for these in the statistical model is pseudoreplication.\nResponse: We believe that there is a misunderstanding, as the multiple trials per site were not treated independently. Each branch or sapling represented a sample, where the proportion of attacked caterpillars was expressed (see above). Therefore, we did not need to consider random factors here.\nWe acknowledge the concern regarding statistical power and the inclusion of polynomial terms. However, the inclusion of the quadratic term (poly(Lat, 2)) is biologically motivated, as we hypothesize that predation rates may follow a non-linear pattern across the latitudinal gradient. Additionally, the other reviewer specifically requested the use of polynomial terms to test for curved relationships. We have included the quadratic term in our candidate models to ensure that non-linear effects are adequately tested.\nBased on the other comments, we provided statistical explanations throughout the text as well as to the Supplementary materials\n\nFinally, Extended Data Table 2 reports AIC model comparisons between a very elaborate set of candidate models. This is not described in the Methods. More importantly, it is not appropriate to conduct null hypothesis tests on model coefficients after choosing the model with AIC (Tredennick et al. 2021 Ecology doi: 10.1002/ecy.3336). Doing so will inflate the type 1 error by an unknowable amount, so the p-values cannot be trusted for inference nor corrected to remedy the problem. I strongly recommend the Authors focus on a minimal set of fixed effects predictors along with the random effects necessary to account for their experimental design. Six latitudinal replicates will almost certainly not offer enough statistical power to detect polynomial or other non-linear effects of latitude.\nResponse: Indeed, we compared the AIC and identified which factors are important for the predation rate. After that, we plotted the estimates from the most parsimonious model. Now, upon request of Reviewer 1, we also plotted confidence intervals of the most parsimonious tests. However, again, we never specify anywhere in the text any P values, and we only talk about relative comparisons and patterns.\n\nThird, there was a substantial design difference in plasticine caterpillar aggregation at one site, Leipzig. Fewer caterpillars were attached to each branch (3 vs. 5 elsewhere), and these groups were much closer together (4m vs. 10m elsewhere). The Authors don’t present data to test for impacts of these differences on predation rates. I would be less concerned for a dataset with more latitudinal replicates and if the methodology difference was at a middle latitude (i.e., less influence on the slope). But here, the unusual site is only one of six, and it is at one of the most extreme latitudes where it has greatest leverage to affect the overall slope.\nResponse: At all study sites, we aimed to place ca. 2 caterpillars per m2 of foliage. The branches in Leipzig were in general smaller, thus less caterpillars were placed on them. The noted minimal distances are indeed minimal, and while the team working at other 5 sites aimed for the saplings to be 10-15 m apart and canopy branches to be at least 4 m apart, the Leipzig team aimed for as far as possible distances but go to the minimal 4m but often longer. Unfortunately, these are only estimates, as far as they can be done from the canopy crane gondola without a possibility to measure the distance by a tape or laser (typically around the crown of the tree etc.). To satisfy the concerns, we rerun all the analyses, without the LAK site (see figures below) and we confirmed that the results did not change significantly.\nWe also adjusted the text in the methods in the main text, by explaining that: “All saplings were at least 10 m apart and branches in canopy at least 4 m apart. As an exception, in Leipzig, 3 caterpillars were attached per sapling and branch, which were all at least 4 m apart.”\n\nLastly, I include a few line-specific comments where more minor edits would improve clarity:\n19: The use of “global” to describe this small set of sites is overreaching.\nResponse: We agree with the concern, and we deleted the word “global”, and specified the study spanned a latitudinal gradient.\n\n44-45: I don’t follow the logic of this sentence. Why do latitudinal gradients in biotic interactions lead us to predict similar gradients in forests?\nResponse: We adjusted the sentences and explained that this is because of steep environmental gradients from canopy to understory. We now specifically say: “Similarly, steep gradients in biotic interactions are predicted along vertical gradients within forests, with biotic interactions expected to be stronger in canopy, as environmental conditions and species composition differ markedly between the understory and canopy.”\n\n45-47: This sentence is worded generally, but needs clarification that the advancements are in the area of latitudinal patterns. There has been a lot of recent theory and empirical work for predator-prey interactions in other contexts.\nResponse: We appreciate the reviewer’s comment and have revised the sentence to clarify the context. The updated sentence now reads: \"While the research of latitudinal patterns in plant-herbivore interactions has seen a proliferation of data and theoretical developments 7-10, predator-prey interactions along latitudinal gradients have received comparatively less attention 11,12.\"\n\n55: Roslin et al. included a range of habitat types, not just forests. I think it’s reasonable to charge that Zvereva et al. may have underestimated predation by omitting canopy habitat because all their sites were in forest. Criticizing Roslin et al. for not standardizing habitats is completely fair, but it seems disingenuous to claim that they underestimated predation by not including forest canopy. In fact sites were shrubland and tundra, so the dummy caterpillars were in fact only deployed in the “canopy” at these low-growing sites much like the Authors varied the canopy height based on local vegetation height. Maybe “near ground level” is a better way to collectively describe what has been done by these two previous studies, limiting the novelty claims about underestimated predation to comparisons with Zvereva et al.?\nResponse: We adjusted the paragraph, which now says: “Roslin et al. 11 conducted a global experiment using dummy plasticine caterpillars across a range of habitats, from forests to tundra, where bite marks allowed predator identification. Their study showed an increase in predation by arthropods towards the equator, while predation rate (Box 1) by vertebrates did not exhibit any latitudinal pattern. Using a comparable method but limited to forest habitats, Zvereva et al. 12 confirmed an equatorial peak in predation rate by arthropods but observed the opposite latitudinal trend in vertebrate predation rate. Irrespective to the type of predators (i.e., summarizing predation rate by all types of predators), both global studies consistently observed higher predation rate in tropical regions 11,12. However, while Zvereva et al. 12 focused exclusively on the forest understory, Roslin et al. 11 included various habitats where caterpillars were always placed near ground level. Consequently, both studies may be potentially missing differences in predation between forest understory and canopy, where most plant and insect biomass and interactions are expected to be concentrated 11-13.”\n\n63-64: “these expectations” isn’t clear. Do you mean patterns in biodiversity, patterns in the strength of interactions, or both?\nResponse: This sentence and aspect were deleted due to other revisions of the text. The comment is not relevant anymore.\n\n72: Repeated words “local” and “locally”\nResponse: We are thankful for spotting this. We deleted the duplicated words.\n\n73-77: I found this sentence very difficult to parse due to the many clauses it contains. Break it up.\nResponse: We agree that the sentence was difficulty to understand. The words migration was associated with the later part of the complex sentence. We deleted it and moved it higher in the paragraph in a different form. Now it reads: Endotherms, and insectivorous birds in particular, may be able to follow the local food availability through various spatial movements: from understory to canopy, regionally along elevation gradients, and globally through latitudinal migrations 21.\n\n91-92: I don’t understand this result. Were the canopy caterpillars attacked more in the temperate zone versus the tropics? Or is the comparison that in temperate zones, the canopy caterpillars were attacked more than those in the understory?\nResponse: We split the sentence into two more simple sentences, indicating that we here talk about canopy vs. understory comparisons only, first for tropics, than for temperate. In these sentences, we do not compare canopy between tropics and temperate, as this is mentioned in the following sentences. The simplified results now sound: “At low latitudes, caterpillars had a higher probability of being attacked when placed in the understory. In contrast, caterpillars had a higher probability of being attacked when placed in the canopy at high latitudes.”\n\n97: What is meant by “non-linearly” here? The [0,1] boundaries of the probability scale mean that every fitted regression will be curvilinear if there is any effect of the continuous predictor. It’s not clear whether the Authors included a non-linear predictor term in their model such that the relationship on the link scale is also non-linear. Consider clarifying the method and result in this part.\nResponse: We clarified that a second-degree polynomial was used to model the latitudinal pattern. While this was already mentioned in the Methods section of the supplementary material under Analysis and as it was evident from the tables, we have added the note here as requested. The sentence now reads: “In canopies, we observed the opposite trend; the probability of a canopy caterpillar being attacked increased, as modelled using a second-degree polynomial, from 6.1% (95% CI: 2.4, 14.4) at KAK site to 64.8% (95% CI: 40.7, 82.5) at the highest latitude studied (LAK) (Supplementary Table S4).”\n\n117-119: I don’t understand how experiment duration could interfere with the detection of geographic patterns in predation. This claim needs further explanation.\nResponse: We added the explanation, but we kept it simple as we are reaching the word limit: “Caterpillars lower to the ground may face fewer bird attacks in vertically complex tropical than temperate habitats. Longer exposure may then cause birds to habituate to dummy caterpillars and reduce their attacks, especially in temperate forests where birds tend to occupy stable territories. The methods of the exposition as well as duration could be interfering with latitude, as the habitats have different vertical structure, communities of birds and their territoriality differs. What we do not discuss specifically in the sentences we added is that the experiment was conducted during season of breeding of birds in the warm and cold temperate sites (LAK, TOM, EUC) but the tropical birds at the sites do not have very strong seasonality, as we can’t provide information on how territorial or moving around, they were. Generally, shorter exposition times work more accurately when birds are rather sedentary and territorial.\n\n121-124: This sentence states that the result both is and is not statistically significant.\nResponse: We are terribly sorry, there was 0 missing in the number (P = 0.0184 not P = 0.184). The same result was correctly mentioned in the legend of Figure 3. We fixed the sentence so now it states: Overall, predation rates caused by birds correlated significantly with the number of insectivorous birds (P = 0.018, r = 0.664) and tended to be associated with their biomass (Fig.3)."}, {"round": 2, "reviewer_comments": {"reviewer_2": "Briefly, my initial review raised the following main concerns:\n1) The main result that latitudinal predation patterns differ between the understory and the canopy was not adequately supported by statistical hypothesis testing.\n2) The statistical model description was insufficient to determine suitability for the question, and I highlighted potential issues around the specification of the random effects and the mixing of model selection with hypothesis testing.\n3) Methodological differences at one site could have a confounding effect due to its high leverage as the furthest site away from the equator.\nOn the first issue, the Authors have added 95% confidence intervals to the Results text and figures. I think this is a positive change, but I continue to be puzzled that the rest of the core statistical information (test statistics, p-values, R^2) is being left out. Fundamentally, a critical value from a statistical distribution is required to calculate a confidence interval, meaning that the Authors have chosen an appropriate statistical distribution and Type-I error rate for their inferential test. P-values aren’t the only way to test hypotheses, but the Authors aren’t using one of these alternatives.\nFor the second issue, I thank the Authors for more fully describing their statistical modeling approach in the Methods, and I agree that using counts of attacks and trials is the right way to maximize statistical power in their analysis. However, it’s now clear that both potential issues I raised compromised the initial analysis and have not been addressed by this revision. The key section of the R code is in the file 02_Total_predation_20250116_CI.R (https://github.com/KatkaSam/CATEX_BABE/tree/master) on lines 122-144.\nThe random effect structure must reflect the grouping imposed by the experimental design for the model to be useful. Using counts of attacks and trials doesn’t resolve the issue. Without specifying the grouping structure, the model will overcount the number of true replicates and could be overconfident in the results. In this experiment, there were three different levels at which the 3300 non-lost dummy caterpillars were grouped: the branch/sapling level within species (n=393), the species level within site (n=50), and the site level (n=6). The Authors’ model only “knows” that attack rates are non-independent because of the tree species the dummy caterpillar was placed on, meaning that there are 50 fully-independent groups of observations that inform the test of the latitudinal gradient. But the risk of attack also depends on the characteristics of the dummy caterpillar’s cluster and site. The Authors appear to have directly observed non-independence at the branch/sapling level, stating in their response to Reviewer 1, “Frustrated birds often attempt to attack another dummy.” Attack rates will tend to be ‘contagious’ within clusters on the same branch/sapling, meaning that we need to account for this when we weight their contribution to our estimate of the overall attack rate. By similar logic, we should expect that dummy caterpillars at the same site will have more similar attack rates compared to caterpillars at different sites along the same latitude. The random effect structure must reflect the hierarchical groupings in the experimental design (1|Site/Species/No.) for inference to be valid.\nThroughout the manuscript, the Authors use the language of hypothesis testing and causal relationships between predictors and attack rate responses. A few examples: “To test this hypothesis” (Abstract L23), “we hypothesise that the predation rate will also be relatively higher in the canopy than the understory” (main text L87-88), “to test the hypothesis of higher predation rates in the tropics and forest canopies” (main text L90-91), “we found that predation rates by birds are higher at high latitudes than in the tropics” (main text L129-130), “Overall, our study revealed that forest strata play a significant role in shaping trophic interactions across latitudinal gradients” (main text L188-189). A typical reader would reasonably interpret these as hypothesis tests, even if the corresponding p-values are omitted or the Authors use vaguer phrases like “pattern” or “trend” to describe the model fit. However, the main results of this study are based on a model selected by AIC, which introduces model selection uncertainty that is not accounted for. The paper I referenced explains in detail why model selection before hypothesis testing is anti-conservative and can lead to overconfidence and false inferences. I must stress that it’s not just p-values that are impacted, but also the 95% confidence intervals that are now displayed in support of the Authors’ claims. Choosing a model a priori or model averaging using AIC weights are appropriate options to avoid or account for model selection uncertainty, respectively.\nOn the third issue, I appreciate the Authors’ re-analysis of the data while omitting the Leipzig site. This is absolutely the right approach, but the above statistical issues must be addressed for a re-analysis to be credible.", "reviewer_3": "The reviews of this manuscript were thorough and the authors have adequately addressed them in most cases. The lack of ant diversity availability is understandable given the authors explanation, nevertheless it is an unfortunate gap in this paper and still feels uncomfortably close to paper splitting.\nMy other major concern is that very little is mentioned about forest type, forest structure (density, height, etc), dominant tree species, forest age (or more importantly seral stage), etc. How did the authors account for these differences, which probably dramatically influence predation rates?\nI think methods, including statistics appear sound, as does their interpretation. I was asked to judge whether the authors have adequately addressed the initial reviewers' comments (not to give my own detailed review of this manuscript), and I believe that they have."}, "author_response": "RESPONSE: We thank the reviewer for raising this important point and for highlighting the relevant literature (see previous revision) on the limitations of relying solely on model selection for hypothesis testing when potentially confounding variables are included among candidate models. We fully agree that careful consideration of causal structure is essential when specifying candidate models. However, this concern does not apply to our analyses, as all of our candidate models differ only in terms of the factors Strata and the alternative ways of coding Latitude, with or without their interaction. In this context, all models are causally sound and represent clearly distinct hypotheses, which we evaluate against each other and against the null model. Under these conditions, model selection using AIC provides a valid framework for assessing support for competing hypotheses.\nWith regard to hypothesis testing of parameters in the selected models, we noted that such tests were included in an earlier version of the manuscript at the request of another reviewer. These results were entirely consistent with those from the model selection approach. We removed these redundant tests from the text of the manuscript and we now present only the model comparison results, which provide direct evidence for our hypotheses.\nSpecifically, as the model including interactions between latitude and strata is far better than the model including only the additive term (see also Table S3), it indicates that the effect of latitude on predation differs between strata.\n\nRESPONSE: We have substantially revised and expanded the model descriptions in the Supplementary materials to provide sufficient detail on the model structure, including the specification of random effects, so that their suitability can be fully evaluated. We also clarify our approach regarding the relationship between model selection and hypothesis testing and explain why, in our case, model comparison provides an appropriate framework for evaluating the hypotheses under consideration.\n\nRESPONSE: Using the revised models (as described in point 2 and 2 comments below), we re-analyzed the data excluding the Leipzig site, which is the most distant from the equator. The results are retained: the overall patterns remain consistent even when this site is excluded. We have added a new table and figure to the Supplementary materials to document these results.\n\nRESPONSE: We thank the reviewer for this thoughtful comment. We agree that confidence intervals imply an underlying statistical distribution and Type I error rate, and we acknowledge the value of reporting test statistics and p-values in many contexts. However, in our study the central aim is to compare clearly defined competing models, rather than to test individual parameters against a null hypothesis. For this reason, we rely on an information-theoretic approach (AIC-based model comparison), which provides a direct measure of relative support for alternative hypotheses. In this framework, confidence intervals serve as a transparent way to illustrate parameter uncertainty and effect sizes, while p-values and test statistics are not necessary to support our conclusions.\n\nRESPONSE: We really thank the reviewer for this detailed and constructive feedback. Their explanation made us realize that our initial specification of the random factors did not fully reflect the hierarchical structure of the sampling design. We have now revised the models to include Site, Species, and Branch as random effects, i.e. + (1|Site) + (1|Species) + (1|Branch). As no species occurs at more than one site, and no branch occurs across multiple species, this specification correctly represents the structure of our data.\nWe recalculated all analyses with this revised random-effect structure and updated the corresponding text, tables, and figures in the manuscript. The results are highly consistent with those from our previous models, with only minor numerical differences. For example, the main model comparison (Table S3) remains essentially unchanged (original results on the left, updated results on the right). These recalculations confirm that our conclusions—including the key inference about the interaction between strata and latitude—are robust to the more detailed random-effect specification.\n\nRESPONSE: As noted in our response to Comment 1, our analyses were designed as a comparison of a priori specified models, each representing a distinct biological hypothesis, rather than as a two-step process of model selection followed by hypothesis testing.\n\nRESPONSE: We thank the reviewer for this positive comment. Using the revised models with the corrected random-effect structure, we re-analyzed the data excluding the Leipzig site. The results demonstrate that the overall patterns remain unchanged when this site is omitted. We have added a new table and figure to the Supplementary Materials to document these results.\n\nRESPONSE: Thank you for comment. We agree that the lack of information on the identities of ants is a limitation, and we also regret that these data are not available. We acknowledge that including such information would have further strengthened the paper.\n\nRESPONSE: All study sites are well-preserved old-growth forests (older than 70 years), with the dominant tree species surveyed in this study. Although for the predation survey we used only 8 individuals in the canopy and 8 in the understory per site, this experiment was embedded within the larger BABE project, which included at least 35 individuals per plant species. For this reason, our survey was limited to the most important plant species.\nTo address this concern, we have added available details on forest characteristics (forest age, minimum known area, canopy height) to Table S1. Unfortunately, we do not have data on stand density. However, we note that variation among sites in forest structure is accounted for in the models by including study site as a random factor."}, {"round": 3, "reviewer_comments": {"reviewer_2": "The Authors’ revisions to the random effect structure fully addresses my concerns about the validity of the main results, and I’m very glad to see that the main result was robust to this fix. The nested random effect syntax I proposed (1 | Site/Species/Branch) is equivalent to the crossed random effect syntax the Authors use (1 | Site) + (1 | Species) + (1 | Branch) because of the way the Authors named their groups. The models would differ only if there were overlapping species between sites, or if the Authors hadn’t been careful to avoid re-using branch numbers between species or sites. Everything on this issue looks defensible and rigorous.\n\nI think we’re going to remain in disagreement about the best way to test the main hypothesis—whether there is an interaction between latitude and strata on predation rate—and to discuss the result without misleading readers. I’ve used a wide range of inferential approaches in my own work, including AIC model comparisons as the Authors use here. In short, I don’t have a vendetta against approaches that don’t have p-values. Instead, for this specific study, a null hypothesis significance test (or equivalent) on the latitude*strata coefficient in a single model that was specified a priori would be a clearer way for readers to assess the evidence. Model comparisons with AIC make for weaker hypothesis tests because they are estimating the out-of-sample predictive performance of the full set of coefficients in a model, and it does a poor job at excluding coefficients with spurious effects. It’s comparing differences in groups of coefficients, rather than focusing on the single coefficient that is motivating the experiment. All this rationale is fully described in Tredennick et al. 2021 (10.1002/ecy.3336) that I referred to in my first round of reviews. Relatedly, I strongly discourage presenting the table with p-values for the top-performing model in the Supplement. These p-values are not adjusted to account for model selection bias, and are anti-conservative.\n\nFinally, I’m disappointed that the Authors didn’t appear to make an attempt to temper their language to avoid conflating the model comparison results they show with null hypothesis significance testing--an issue that was central to my main concerns. My previous review highlighted specific lines throughout the manuscript where the results were discussed as if evidence based on significance testing supports their results. As written, these are misleading and it distracts from the evidence the manuscript can defend."}, "author_response": "*** We thank the reviewer for the positive assessment of our revised random‐effects structure. We are grateful for the reviewer’s recognition that our approach is defensible and rigorous, and we are pleased that the main results remain robust under this correction.\n\n*** We thank the reviewer for their thoughtful comments regarding the inference on the latitude × strata interaction. We appreciate the detailed explanation. In the previous round of the revisions, we already removed the unadjusted p-values for the top-performing model from the Supplement, in line with the reviewer’s concern. We double checked now, and there is no single P value in the supplement.\n\n*** We returned to the specific lines pointed out in the previous version of the manuscript, and we adjusted the text even more. We now make sure that all language referring to “effects,” “support,” or “significance” is aligned with AIC-based inference, and statements are explicitly framed in terms of relative model support, not hypothesis acceptance or rejection."}]

Decision letter