Influence of light availability and soil productivity on insect herbivory on bilberry (Vaccinium myrtillus L.) leaves following mammalian herbivory

Marcel Schrijvers-Gonlag; Christina Skarpe; Harry Peter Andreassen

doi:10.1371/journal.pone.0230509

. 2020 Mar 27;15(3):e0230509. doi: 10.1371/journal.pone.0230509

Influence of light availability and soil productivity on insect herbivory on bilberry (Vaccinium myrtillus L.) leaves following mammalian herbivory

Marcel Schrijvers-Gonlag ^1,^*, Christina Skarpe ¹, Harry Peter Andreassen ¹

Editor: Livia Maria Silva Ataide²

PMCID: PMC7100976 PMID: 32218604

Abstract

Vegetative parts of bilberry (Vaccinium myrtillus) are important forage for many boreal forest mammal, bird and insect species. Plant palatability to insects is affected by concentration of nutrients and defense compounds in plants. We expected that palatability of bilberry leaves to insect herbivores is influenced by light availability and soil productivity (both affecting nitrogen concentration and constitutive carbon-based defense compound concentration) and herbivory by mammals (affecting nitrogen concentration and induced carbon-based defense compound concentration). We studied bilberry leaf herbivory under different light availability, soil productivity and mammalian herbivory pressure in small sampling units (1m x 1m) in boreal forest in Norway. We used generalized linear mixed models and generalized additive mixed models to model insect herbivory on bilberry leaves as a function of shade, soil productivity and mammalian herbivory. Observed insect herbivory on bilberry leaves increased with increasing shade levels. Predicted insect herbivory increased with increasing previous mammalian herbivory at high shade levels and this response was magnified at higher soil productivity levels. At low to intermediate shade levels, this response was only present under high soil productivity levels. Our results indicate that light availability is more important for variation in bilberry leaf palatability than soil nutrient conditions.

Introduction

Bilberry (Vaccinium myrtillus L.) is a deciduous clonal dwarf shrub with evergreen shoots that is abundant on many nutrient-poor soils in the boreal forest region of Scandinavia [1–6]. The vegetative parts of bilberry are important forage for many mammal, bird and insect species [7–13]. Insect herbivores can be indirectly affected by mammalian herbivores, which can modify food quantity, e.g., plant cover and biomass, and food quality, e.g., nutrient concentration [14–16] and the concentration and composition of chemical defense metabolites in plants [17–19]. The production of chemical defense metabolites is one of many defense strategies used by plants to minimize the negative effect of herbivory on plant fitness [20, 21].

Several hypotheses about constitutive and inducible defense are relevant for bilberry-herbivore interactions. In this paper we use 'constitutive defense' and 'inducible defense' as Tuomi and colleagues do [22]: constitutive defense levels are not affected by herbivores, whereas induced defense refers to the change in plant resistance as a response to herbivory. Induced defense is only possible if the plant possesses phenotypic plasticity in defense, which applies to bilberry [23]. Below, we introduce briefly three existing plant defense hypotheses and describe how plant nutrient concentration and defenses are expected to be influenced by soil productivity, light availability and herbivory. After combining this information (Fig 1) we present our own predictions.

Fig 1 — Theoretical relationship between (a,d,g) light availability, (b,e,h) soil productivity and (c,f,i) herbivory (predictor variables) and (a,b,c) carbon-based defense compounds (CBDCs), (d,e,f) nutrient concentration and (g,h,i) palatability (response variables) in/of bilberry (*Vaccinium myrtillus*) leaves, assuming a positive linear relationship between secondary metabolites and CBDCs. The combination (indicated by a plus sign) of (a) and (d) results (indicated by a vertical arrow) in (g); (b) combined with (e) results in (h); (c) combined with (f) results in (i). Herbivory refers to previous mammalian herbivory (pruning). Palatability is the combined effect of CBDCs and nutrient concentration. Palatability under different (h) soil productivity (level of nutrients available to the individual plant) and (i) herbivory pressure ranges between (h) j and k and (i) m and n, dependent on whether palatability is less (j and m) or more (k and n) affected by CBDCs than by nutrient concentration. Sources (a-c): (a) Carbon:Nutrient Balance (CNB) hypothesis, Growth-Differentiation Balance (GDB) hypothesis; (b) GDB hypothesis; (c) Optimal Defense hypotheses, CNB hypothesis. Sources (d-f): see references in text.

The Optimal Defense (OD) hypotheses state that defenses are costly (in terms of fitness) because they divert resources from growth, and assume that herbivory is the primary selective force shaping quantitative patterns of secondary metabolism. As a result, expression of resistance (e.g., production of inducible defenses, which are secondary metabolism compounds) should be low when herbivores are nearly absent and increase when the plant is under attack [24–29].

The Carbon:Nutrient Balance (CNB) hypothesis is a model of how the supply of carbon and nutrients in the environment influences the phenotypic expression of secondary metabolism by plants [22, 28, 30]. The CNB hypothesis predicts that increased nitrogen availability permits plants to allocate more carbon to growth, resulting in less carbon-based defense compounds (CBDCs). A similar decrease in CBDCs is predicted with increasing shade, as this decreases the C:N ratio by limiting carbon assimilation more than nutrient uptake [31]. Accordingly, light availability is positively correlated with production of many CBDCs [19, 28, 32, 33]. Furthermore, herbivory can alter the carbon:nutrient balance within plants, that may influence the level of CBDCs. Because many deciduous woody species growing on nutrient-poor soils store carbon in stems and roots [22, 34], herbivory on shoots and leaves is expected to increase the level of CBDCs in bilberry.

The expanded Growth-Differentiation Balance (GDB) hypothesis includes all extrinsic factors affecting secondary metabolism, not only carbon and nutrients as in the CNB hypothesis. The GDB hypothesis acknowledges that in plant development there is a constant tradeoff between growth and differentiation requirements. For any resource-shortage that slows growth more than it slows photosynthesis, the GDB hypothesis predicts a unimodal effect of availability of this resource on secondary metabolite production [28, 31, 35]. Consequently, under non-shady and low soil productivity conditions, nitrogen-demanding growth processes are more limited than production of CBDCs.

In addition to concentration and type of defense compounds, palatability is also affected by nutrient concentration in plants [36, 37]. Nitrogen concentration, which is often used as a proxy for nutrient concentration, increases in bilberry after nitrogen fertilization and is positively related to habitat productivity [19, 38–43, but see 44, 45]. Nitrogen concentration in leaves is negatively related to light availability [46–48, see also 49]. Pruning (partial or complete removal of stem/shoots) reduces bud numbers and increases the root:shoot ratio, resulting in decreased competition for nutrients among meristems and, thus, increased nutrient concentration in new plant tissue [50–54]. Indeed, nitrogen concentration increases after browsing in several woody species, often regardless of soil productivity [55–59].

Based on what precedes, palatability of bilberry leaves to insect herbivores is affected by the combined concentration in CBDCs and nutrients, which are affected by light availability, soil productivity and herbivory (Fig 1). According to Fig 1I, the relationship between mammalian herbivory and subsequent insect herbivory on bilberry varies depending on whether insects profit more from increasing nutrient concentrations in bilberry leaves than they suffer from increasing defense compound concentrations in these leaves, or vice versa. While this relationship has been studied in other woody species, e.g., northern willow (Salix glauca L.) [58], this relationship is, to our knowledge, not known for bilberry. The aim of our study was to assess whether bilberry leaf palatability to insects is affected by light availability, soil productivity and previous mammalian herbivory. Therefore, we investigated bilberry leaf palatability to insects under different levels of light availability, soil productivity and mammalian herbivory pressure in small sampling units (1m x 1m) in six boreal forest areas in southeastern Norway in the period 2013–2015. We assumed that under similar light availability and soil productivity conditions, the change in leaf palatability caused by induced changes in CBDCs in leaves is counter-balanced by induced changes in nutrient concentration in these leaves, resulting in bilberry leaf palatability showing no correlation with previous mammalian herbivory. Based on this assumption, and the theory highlighted in Fig 1G–1I we predicted that bilberry leaf palatability:

I. is negatively correlated with light availability,

II. shows a unimodal relationship with soil productivity, and

III. is not correlated with previous mammalian herbivory.

Methods

Study area

We conducted the study in the Østerdalen valley in southeastern Norway (Fig 2) in the period 2013–2015. The study area was at elevation 288–810 m a.s.l. and consisted mainly of coniferous boreal forest interspersed with streams, marshes and grasslands with free-ranging domestic livestock (sheep and cows) during the snow-free season. Common wild mammalian herbivore species in the area were moose (Alces alces L.), red deer (Cervus elaphus L.), roe deer (Capreolus capreolus L.), mountain hare (Lepus timidus L.), several small rodent species and, to the west of the Glomma River (Fig 2), reindeer (Rangifer tarandus L.). During the study period, annual mean temperature was 4°C (-9°C in January and 16°C in July) at Evenstad weather station (61°26’N, 11°05'E, elevation 257 m a.s.l.); annual mean precipitation was 818 mm at Rena Flyplass weather station (61°11’N, 11°22'E, elevation 255 m a.s.l.) [60]. No permits for field site access were necessary, according to Norwegian law (friluftsloven: LOV-1957-06-28-16) that permitted access by foot to natural areas.

Study design

We sampled within six blocks of 16 km² (4 km x 4 km) each (Fig 2, black squares). In the center of each block, we used four 1.5 km long transect lines, parallel and spaced by 500 m. Each line contained four survey locations for bilberry data collection and soil sampling. Each survey location consisted of two vegetation sampling quadrats of 1 m² (1m x 1m, permanently marked), separated by approximately 40 m. In each quadrat we estimated bilberry cover (%) and insect herbivory on bilberry leaves: we estimated chewing damage as the proportion of leaf area eaten in the shape of holes ('hole herbivory') and the proportion of leaf area eaten at the edge of the leaves ('edge herbivory'). We also looked for signs of ‘present-year mammalian herbivory’, i.e., herbivory on stems and shoots that had occurred during or since the previous winter, and we estimated the proportion of biomass that had been taken away (refered to as 'previous mammalian herbivory' in this paper). We sampled the vegetation once a year (8–29 July 2013, 1–22 July 2014 and 7–24 July 2015). In 2015 we recorded tree species composition of the surrounding forest for each quadrat. We estimated the proportion of shade from the tree canopies at each survey location in 2014 and used these for both quadrats. We used three categories: less than 20% (low shade level), between 20% and 80% (intermediate shade level), more than 80% (high shade level). As low and high shade levels were assumed to result in clearly different palatability (Fig 1G), these categories were made narrow. We collected soil samples (the upper organic layer down to maximum 10 cm) nearby every quadrat with a metal bulb planter in October 2014. We merged the two soil samples at each survey location and used these for both quadrats. We stored the samples frozen (-18°C) prior to analysis. All samples were analyzed for ammonium lactate extractable phosphorus (measuring method uncertainty ± 20%, method reference SS028310T1/SS-EN) and total nitrogen (measuring method uncertainty ± 10%, method reference EN 15104:2011/EN 15407:2011) (Eurofins Food & Agro Testing Sweden AB, Kristianstad/Linköping, April 2015). We did not use inorganic ammonium (NH₄⁺) or nitrate (NO₃^–) concentrations, as organic nitrogen is an important source of nitrogen to bilberry [45, see also 61].

Data analyses

We focused our analyses on quadrats in evergreen forest where bilberry was present, and with non-missing data for insect and mammalian herbivory, shade, phosphorus and nitrogen, which left 455 quadrats for analyses. We considered that the single sampling for shade and soil was representative for the whole study period. We combined edge and hole herbivory as 'insect herbivory' (response variable), which we used as a proxy for bilberry leaf palatability.

Prediction I: Leaf palatability and light availability

To investigate prediction I we modeled insect herbivory as a function of shade ('shade model'). We added year as a fixed effect to account for annual variability, caused by variability in, e.g., field workers, vole density and weather (S1 File). The response variable (insect herbivory) was a proportion (a continuous variable with a value from 0 to 1), therefore we used a beta distribution with a logit link function [62]. We used generalized linear mixed models (GLMMs) fitted using the package 'glmmTMB' in the software 'R' [63]. All analyses in this study were performed in R, version 3.6.2. [64]. Before modeling, we checked for collinearity between all predictor variables. Prior to analyses we used the transformation: (insect herbivory x (n– 1) + 0.5) / n (where n is the number of observations) for the response variable, to deal with actual observations equal to 0 or 1 [65, 66]. Given our study design, we initially included a nested random component in the model with survey location nested within transect line nested within block. The corresponding estimates of variance were very small so we removed the line and block grouping variables from the random component in the models that we used for analyses [67]. We used Akaike's information criterion (AIC) to compare the shade model with a similar model without the fixed effect shade [68]. We used the package 'emmeans' to further investigate the relationship between insect herbivory and light availability [69]. We validated the model by evaluating residual diagnostics using the package 'DHARMa' [70]. Unless otherwise stated, we used a significance level of 5% in all our analyses in this study.

Prediction II: Leaf palatability and soil productivity

To investigate prediction II we first performed a principal component analysis (PCA) with the two standardized variables phosphorus and nitrogen to obtain a single composite covariate (called PC1) for soil productivity to use in our subsequent modeling (S1 File) [71]. We modeled insect herbivory as a function of soil productivity ('soil model'). Similar to the shade model (see Prediction I), we first checked for collinearity between all predictor variables, used the transformed response variable and a beta distribution with a logit link function, added year as a fixed effect and used survey location in the random component. We used generalized additive mixed models (GAMMs) fitted using the package 'mgcv' [72, 73]. To evaluate the existence of a unimodal relationship we compared a soil model fitted with a non-linear relationship, i.e., a GAMM with a smooth term, with a soil model fitted with a linear relationship, i.e., a GAMM without a smooth term, and with a similar model without the fixed effect soil productivity, by their AIC values. We validated the models by evaluating the standardized residuals graphically [74–76].

Prediction III: Leaf palatability and mammalian herbivory

To investigate the relationship insect herbivory–previous mammalian herbivory under different levels of light availability and soil productivity, we made scatterplots and added linear regression lines for insect and previous mammalian herbivory, at all possible combinations of shade conditions and soil productivity levels. Soil productivity levels were obtained by categorizing the numerical variable soil productivity (see prediction II) into three evenly distributed (same number of observations) soil productivity classes: low, intermediate, high. Means and standard error (SE) values for the different classes were calculated with the package 'emmeans'. To investigate prediction III, we modeled insect herbivory as a function of previous mammalian herbivory, shade, soil productivity, and all their possible interactions. Similar to the shade model (see Prediction I), we first checked for collinearity between all predictor variables, used GLMMs fitted using the package 'glmmTMB', used the transformed response variable and a beta distribution with a logit link function, added year as a fixed effect and used survey location in the random component. In addition, we standardized the variable previous mammalian herbivory prior to modeling using the package 'arm' [77]. We performed model selection using AIC and model evaluation using the package 'DHARMa'. We used the parameter estimates of the best (most parsimonious) model to predict insect herbivory on bilberry leaves following mammalian herbivory under different light conditions (low, intermediate, high shade levels) and on soils with different productivity (low, intermediate, high levels). To visualize the predicted insect herbivory values we used the first, second (the median) and third quartile of the variable soil productivity for low, intermediate and high soil productivity, respectively.

Results

Across quadrats, herbivory was low (Fig 3) but frequent, and more often due to insects than to mammals (S1 File). Quadrats at exposed and half-open locations were twice as frequent as quadrats in shady conditions, nitrogen and phosphorus levels showed little variation (S1 File).

Prediction I: Leaf palatability and light availability

Correlation between the predictor variables shade and year was very low (Pearson's correlation coefficient: ρ = 0.027). Estimates of variance for the initially used nested random component were: survey location:(line:block) = 0.008 (n = 88), line:block = 0.004 (n = 24), block = 0.007 (n = 6). The estimated variance of survey location, when only survey location was used in the random component, was 0.021 (n = 88). The shade model had a lower AIC value than a similar model without the fixed effect shade (but with the fixed effect year and the random component): -2605.23 versus -2598.80, respectively. The shade model revealed a positive correlation between insect herbivory and shade (S1 and S3 Tables). Using the shade model, there was no significant difference in insect herbivory between the intermediate and high shade levels (Tukey's HSD test: df = 448, P = 0.68). In this model, insect herbivory at low shade level differed from insect herbivory at intermediate and high shade levels (Tukey's HSD test: df = 448, P = 0.02 and 0.01, respectively). Analyses with the DHARMa package showed that the model fit was quite poor (e.g., overdispersion present). In a linear model (both with and without the fixed effect year; no random component, Gaussian distribution with identity link) insect herbivory at high shade levels differed from insect herbivory at both low and intermediate shade levels but there was no significant difference between low and intermediate shade levels (Fig 3A; S2 Table). We conclude that our data supports prediction I.

Prediction II: Leaf palatability and soil productivity

Correlation between the predictor variables soil and year was low (Pearson's correlation coefficient: ρ = 0.092). Estimates of variance for the initially used nested random component in the soil model fitted with a non-linear relationship were: survey location:(line:block) = 0.144 (n = 88), line:block = 0.024 (n = 24), block = 0.028 (n = 6). The estimated variance of survey location, when only survey location was used in the random component, was 0.194 (n = 88). Based on their AIC values, there was no difference between the soil model with a non-linear fit, the soil model with a linear fit and a similar model without the fixed effect soil productivity (but with the fixed effect year and the random component) (AIC values: 1492.151, 1490.151 and 1491.687, respectively). Consequently, there was not enough non-linearity in the relationship between the variables to warrant a (more complex) non-linear model. Moreover, based on the AIC values the model with and the model without the covariate soil were as good in predicting insect herbivory. Model validation showed that the model fit for all models was quite poor (e.g., heterogeneity present). We conclude that our data does not support prediction II.

Prediction III: Leaf palatability and mammalian herbivory

Observations with the 151 highest PC1 values were assigned to class 'low soil productivity levels' (mean = 1.193, SE = 0.035), observations with the 151 lowest PC1 values were assigned to class 'high soil productivity levels' (mean = -1.156, SE = 0.035), the remaining ones (n = 153) were assigned to class 'intermediate soil productivity levels' (mean = -0.037, SE = 0.035). Insect herbivory related to previous mammalian herbivory is shown in Fig 4, at all possible combinations of shade conditions and soil productivity levels. In six panels no correlation (P > 0.10) was present between mammalian and subsequent insect herbivory. The combination intermediate shade levels and low productivity levels yielded a tendency for a negative linear relationship (slope = -0.02, ANOVA: F_1,53 = 2.85, P = 0.097) but the explained variation was low (adjusted R-squared = 0.03). A significant positive linear relationship between mammalian and subsequent insect herbivory was present in two panels: high shade levels and intermediate productivity levels (slope = 0.19, ANOVA: F_1,24 = 10.85, P = 0.0031) and intermediate shade levels and high productivity levels (slope = 0.13, ANOVA: F_1,57 = 9.97, P = 0.0025). The explained variation was 28% and 13%, which can be considered as important effect sizes in ecological studies with a low degree of control, like our field study [78, 79]. The linear relationship between insect herbivory and previous mammalian herbivory independent of shade and soil was significant (slope = 0.04, ANOVA: F_1,453 = 12.46, P = 0.00046) but the explained variation was very low (adjusted R-squared = 0.02), see S1 File.

Fig 4 — Insect herbivory versus previous mammalian herbivory on bilberry (*Vaccinium myrtillus*) in exposed areas (shade < 20%), half open areas (shade between 20% and 80%) and shaded areas (> 80% shade) and at low, intermediate and high soil productivity levels. In each panel the number of observations (n) is given, and the P-value (ANOVA) for the linear regression (regression line shown in each panel) is indicated as: *** 0 < P < 0.001; ** 0.001 < P < 0.01; * 0.01 < P < 0.05; # 0.05 < P < 0.10; blank P > 0.10. If P < 0.10 the adjusted R-squared value is given.

Correlation in the set of predictor variables that we used in our modeling was low (highest Pearson's correlation coefficient: ρ = 0.26). Estimates of variance for the initially used nested random component in the full model were: survey location:(line:block) = 0.018 (n = 88), line:block = 0.003 (n = 24), block = 0.010 (n = 6). The estimated variance of survey location in the full model, when only survey location was used in the random component, was 0.032 (n = 88). In total 35 models were used in our model selection analyses. The best model included interactions between soil productivity and previous mammalian herbivory, between shade and previous mammalian herbivory, and between shade and soil productivity (S4 Table). Analyses with the DHARMa package showed that the model fit was quite poor (e.g., overdispersion present). The parameter estimates of the best model (Table 1) were used to predict insect herbivory in Fig 5. These predicted values are for 2014 as this year had the highest estimate compared to 2013 and 2015 (Table 1); predictions for 2013 and 2015 show similar curves but with less amplitude. In shady conditions, predicted insect herbivory increased with previous mammalian herbivory; the rate of increase was lowest at low soil productivity levels and highest at high soil productivity levels (Fig 5C). With low and intermediate shade levels (Fig 5A and 5B), insect herbivory was predicted to show either little positive correlation with previous mammalian herbivory (soils with high productivity levels) or (almost) no correlation (soils with low and intermediate productivity levels). We conclude that our data does not support prediction III.

Table 1. Parameter estimates for the best model of variables affecting insect herbivory on bilberry leaves.

Parameter estimate, standard error, 95% confidence interval and P-value are presented for the intercept and each of the fixed effects in the best model (S4 Table). Note that the model used a logit link function (the estimates are on a logit-scale, not the response scale), that the predictor variable previous mammalian herbivory was standardized and that the response variable was transformed prior to analyses (see text). Therefore, also the back-transformed estimate (back-transformed from both logit transformation and response variable transformation) is presented for the intercept and each of the fixed effects (thus, this value is on the response scale). Parameter estimate and 95% confidence interval are also presented for the standard deviation of the random component and for the dispersion parameter. Number of observations: 455.

Parameter	Estimate	SE	lCI	uCI	P-value	Sign	BE
Intercept	-3.92	0.09	-4.11	-3.74	0.00	^***	0.02
Soil	-0.06	0.07	-0.19	0.08	0.40		0.49
Shade < 20%	-0.23	0.09	-0.41	-0.05	0.01	^*	0.44
Shade > 80%	0.07	0.11	-0.15	0.30	0.52		0.52
Mammal	0.12	0.13	-0.14	0.38	0.35		0.53
Year 2014	0.42	0.09	0.24	0.60	0.00	^***	0.60
Year 2015	-0.05	0.10	-0.23	0.14	0.63		0.49
Soil : Mammal	-0.24	0.06	-0.36	-0.13	0.00	^***	0.44
Soil : Shade < 20%	0.05	0.09	-0.12	0.23	0.54		0.51
Soil : Shade > 80%	-0.24	0.12	-0.46	-0.01	0.04	^*	0.44
Shade < 20% : Mammal	0.20	0.18	-0.16	0.56	0.27		0.55
Shade > 80% : Mammal	0.69	0.16	0.37	1.01	0.00	^***	0.67
Location (st.dev.)	0.18		0.08	0.37
Dispersion parameter	55.83		47.33	65.85

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Mammal = previous mammalian herbivory; Location (st.dev) = survey location (standard deviation); SE = standard error; lCI = lower 95% confidence interval; uCI = upper 95% confidence interval; Sign = significance level

*** 0 < P < 0.001

** 0.001 < P < 0.01

* 0.01 < P < 0.05; blank P > 0.05; BE = back-transformed estimate.

Fig 5 — Predicted insect herbivory on bilberry (*Vaccinium myrtillus*) leaves, growing at low, intermediate and high soil productivity levels, as a function of previous mammalian herbivory in 2014, under conditions of (a) low, (b) intermediate and (c) high shade levels. Predictions based on parameter estimates for the best model (Table 1).

Discussion

Plant defense theory predicts that palatability of bilberry leaves to insect herbivores is influenced by light availability, soil productivity and herbivory by mammals, as these factors affect nutrient and CBDC concentration (Fig 1). We found that insect herbivory had a positive relationship with previous mammalian herbivory at high shade levels. At intermediate and low shade levels, this relationship was weak (bilberry growing at high soil productivity levels) or absent (bilberry growing at intermediate or low soil productivity levels) (Fig 5).

Prediction I: Leaf palatability and light availability

According to our model, insect herbivory increases with previous mammalian herbivory and with soil productivity, especially under shady conditions (Fig 5). The difference between the observed relationship insect herbivory–soil productivity (Fig 3C) and the model predictions (Fig 5) indicates that also previous mammalian herbivory and light conditions are influencing palatability of bilberry leaves to insects, in accordance with the mentioned theories on plant defense. Richardson and colleagues [44] found that insect herbivory on bilberry increased after nutrient addition and with experimental warming. However, they used open top chambers (OTCs) in which photosynthesis often is reduced [80]. This means that the increase in insect herbivory found by Richardson and colleagues [44] may have been caused by a combination of fertilization, higher temperature and reduced light availability. The latter is in accordance with our finding that light availability is important for leaf palatability and in line with our prediction I.

Our results indicate that light availability is more important for variation in bilberry leaf palatability than soil nutrient conditions. This is in agreement with the results from a study on bilberry leaves in northern Finland [81]. In a study in northern Sweden, some particular CBDCs (flavonoids) in bilberry leaves were not affected by nitrogen fertilization [82]. The authors suggest that light conditions may be a regulator for the synthesis and accumulation of flavonoids, which are important in plant protection against ultraviolet-B radiation (UV-B) [82, 83]. In our study we incorporated light conditions by estimating the proportion of shade but we did not measure temperature nor UV-B, which affect several CBDCs in foliage, potentially altering insect herbivore performance either positively or negatively [84–92].

Prediction II: Leaf palatability and soil productivity

We found no support for a non-linear effect of soil productivity on bilberry leaf palatability to insects. Our observations may not cover the full ecological range for soil productivity of bilberry (S1 File). Soil productivity is generally low in boreal forests [93, 94]. The productivity might be too low to see any response in insect herbivory on bilberry. Additionally, the small spatial scale of the study (one valley) may have limited the spatial variation in soil productivity. Indeed, there is only small variation in nitrogen and phosphorus concentrations in our dataset. Furthermore, as bilberry is adapted to relatively nutrient-poor environments, increased soil productivity may not trigger a direct response [95].

The CNB hypothesis predicts that nitrogen enrichment permits plants to allocate more carbon to growth, resulting in a decrease in CBDCs. This does not apply to all plant secondary metabolites, as proteins and many phenolics compete for the precursor phenylalanine [96, 97]. This precursor was used by Jones and Hartley [98] in their protein competition model for predicting total phenolic concentration in leaves. Consequently, as biosynthesis of terpenoids and of hydrolyzable tannins presumably proceeds without direct competition with protein synthesis [96], these secondary metabolites are likely to follow the CNB hypothesis, while others, e.g., flavonoids [19] and condensed tannins, may not. Therefore, if bilberry is attacked by leaf-chewing insect species that are less sensitive to terpenoids and hydrolyzable tannins but that respond negatively to flavonoids and condensed tannins in leaves, insect herbivory on bilberry leaves may not be correlated to soil productivity. This means that the relationship between leaf palatability and soil productivity may depend on the insect species involved.

Prediction III: Leaf palatability and mammalian herbivory

An important limitation of our study is the uncertainty in our main covariate: the estimation of the proportion of biomass that had been taken away by mammals. Estimating something that is no longer present can be challenging! We did not take any observations of biomass before herbivory, for example by using photographs [99]. Still, we found limited support for a significant positive relationship between observed mammalian and subsequent insect herbivory. At high shade levels the predicted insect herbivory increased with increasing previous mammalian herbivory. At low and intermediate shade levels, our third prediction seems to hold at least for bilberry growing at low and intermediate soil productivity levels.

The observed increase in insect herbivory following mammalian herbivory indicates that under certain light and soil nutrient conditions bilberry leaf palatability is more affected by leaf nutrient concentration than by leaf CBDC concentration (m in Fig 1I). As reviewed by Koricheva and colleagues, several studies, including a study with leaf-eating larvae on bilberry, showed that insect performance on experimentally stressed woody species improved with stress level until reaching some threshold, above which performance declined [23, 100]. However, a non-linear model with soil production did not markedly improve the predictions and was selected against with our current data.

Conclusion

Our study indicates that light availability is important for bilberry leaf palatability, as insect herbivory on bilberry leaves increased with increasing shade (confirming our first prediction). Our results indicate that under certain light and soil nutrient conditions bilberry leaf palatability following mammalian herbivory on bilberry is more affected by leaf nutrient concentration than by leaf CBDC concentration. Furthermore, we did not find a straightforward correlation between insect herbivory and soil productivity alone (falsifying our second prediction), without taking into account light conditions: our results indicate that at high shade levels bilberry leaf palatability is positively correlated with previous mammalian herbivory (falsifying our third prediction) and this response is magnified at higher soil productivity levels. At low to intermediate shade levels, this response is only present under high soil productivity levels. Our results indicate that light availability is more important for variation in bilberry leaf palatability than soil productivity.

Supporting information

S1 File

(PDF)

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S1 Table. Insect herbivory: Estimated Marginal Means (EMMs) per shade level in the shade model.

Estimated marginal mean values for insect herbivory, their standard error, degrees of freedom and 95% confidence intervals are presented for each level of the variable shade in the shade model. Note that the model used a logit link function (the estimates are on a logit-scale, not the response scale) and that the response variable was transformed prior to analyses (see text in the manuscript). Therefore, also the back-transformed estimated marginal means (back-transformed from both logit transformation and response variable transformation) are presented (thus, these values are on the response scale). To make differences visible, three digits are given for the back-transformed estimated marginal means. Results are averaged over the levels of the variable year. Number of observations: 455.

(PDF)

Click here for additional data file.^{(12.2KB, pdf)}

S2 Table. Insect herbivory: Estimated Marginal Means (EMMs) per shade level in a linear model and the contrast estimates with Tukey's HSD test values.

Estimated marginal mean values for insect herbivory, their standard error, degrees of freedom and 95% confidence intervals are presented for each level of the variable shade in a linear model with and without year as a fixed effect. In the first model, results are averaged over the levels of the variable year. Similar information is presented for the contrast estimates; in addition, their P values based on Tukey's HSD test are given. Number of observations: 455.

(PDF)

Click here for additional data file.^{(265.2KB, pdf)}

S3 Table. Parameter estimates for the shade model of variables affecting insect herbivory on bilberry leaves.

Parameter estimates, standard error, 95% confidence interval and P-values are presented for the intercept and each of the fixed effects in the shade model. Note that the model used a logit link function (the estimates are on a logit-scale, not the response scale) and that the response variable was transformed prior to analyses (see text in the manuscript). Therefore, also the back-transformed estimates (back-transformed from both logit transformation and response variable transformation) are presented for the intercept and each of the fixed effects (thus, these values are on the response scale). Parameter estimates and 95% confidence interval are also presented for the standard deviation of the random component and for the dispersion parameter. Number of observations: 455.

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Click here for additional data file.^{(15.4KB, pdf)}

S4 Table. Modeling of variables affecting insect herbivory on bilberry leaves in southeastern Norway in 2013–2015.

Model inferences based on Generalised Linear Mixed Modeling (beta regression with logit link). Best models based on AIC selection; only the five best models are presented, and the null model for comparison purposes. In addition to the presented model sets in the table, all models contained the random component (1|survey location). The first model (Δ AIC = 0.00) is the most parimonious model. The second model (Δ AIC = 0.50) is the full model. See text for description of the fixed effects and random component. Number of observations: 455.

(PDF)

Click here for additional data file.^{(211.4KB, pdf)}

Acknowledgments

We thank Olivier Devineau for invaluable help with statistics and extensive comments on the manuscript, David Carricondo Sánchez for coordinating and conducting fieldwork, help with data analyses and for constructive comments, Barbora Malá for substantially contributing to the study design, conducting additional fieldwork and analysing data, Cyril Milleret for help with R and ArcGIS, Morten Odden and Lasse Asmyhr for help with organising and coordinating fieldwork, Maria Greger, Jo Inge Breisjøberget, Barbara Zimmermann, Ane Eriksen Hamilton, Gitte C. Kloek, Vladimir Naumov and Antonio B. S. Poléo for scientific and editorial advice, Zea Walton and Annie Loosen for help with some language issues, Marieke Gonlag-Schrijvers for editorial advice and Yagya Raj Bhatt and Bernardo Toledo González for punching data. We thank all fieldworkers for their efforts: Clementine Crombez, Jason Kandume, Jorge Galindo Guiterrez, Julie Saez, Siegfrid Waas, Solenne Lheritier, Jakob K. N. Brunner, Melissa Brilman, Matthieu Gibert, Carole Parrel, Vincent Hetter, Scarlet van Os, Sabrina Dietz, Axel Becker, Timo Förster, Barbara Joncour, Julia Gómez Catasús, Magnus Hoff Olsen, Farina Sooth, Thomas Vogler, Sofia Willebrand, Emelie Önstedt, Umer Qureshi, Claire Tachon, Olivier Duchene, Andreja Kovše, Jaka Tegelj, Sašo Veselinovič, Andreas Hein, Audrey Jansseune, Marieke Gehem, Florian Nöscher, Vincent Baudon, Corentin Bouffanet, Jan Kiehne, Pierre Lequay, Petrus Martiskin, Urška Mrak, Falk Schreiner, Ulvi Selgis, Md. Shamsuzzaman and all others not mentioned here. MSG thanks the Stack Exchange Q&A web communities Stack Overflow and Cross Validated for invaluable statistical and analytical insights. MSG and CS especially thank Harry P. Andreassen, who, no longer with us († 21 May 2019), initiated this study and contributed highly to earlier versions of the manuscript.

Data Availability

The dataset and script used for the presented analyses are stored in the DataverseNO database and available at https://doi.org/10.18710/89MLBP.

Funding Statement

This study is a part of the BEcoDyn project supported by Inland Norway University of Applied Sciences and a grant from The Research Council of Norway (NFR project 221056; https://prosjektbanken.forskningsradet.no/#/project/NFR/221056/Sprak=en) to HPA. Work done by MSG was only partly funded. The Research Council of Norway (https://www.forskningsradet.no/en/) had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0230509.r001

Decision Letter 0

Livia Maria Silva Ataide

24 Oct 2019

PONE-D-19-24380

Influence of light availability and soil productivity on insect herbivory on bilberry (Vaccinium myrtillus L.) leaves following mammalian herbivory

PLOS ONE

Dear Mr. Schrijvers-Gonlag,

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Academic Editor

PLOS ONE

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Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

**********

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Reviewer #1: No

Reviewer #2: Yes

**********

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Reviewer #2: Yes

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Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: A review of a manuscript entitled “Influence of light availability and soil productivity on insect herbivory on bilberry (Vaccinium myrtillus L.) leaves following mammalian herbivory” for PLoS ONE (PONE-D-19-24380)

General comments

In this study, the authors aimed to evaluate whether the palatability of bilberry leaves (Vaccinium myrtillus) to insect herbivores is influenced by light availability, by soil productivity and by previous herbivory by mammals. A set of generalized linear models were used to test these three variables using a robust sample design. However, the results and discussion are dense, with many figures to look at and re-analyzes being described in the results and discussion. All of this part of data re-analysis to find the best model is part of the methods and I think it should not appear in the results. By reading the methods, the reader expects to see such analyzes and imagines such figures, but during the results the reader finds new analyzes being made based on the previous results. That does not seem appropriate to me here. These should all be described in the methods (or in supplementary documents) and the main results should be presented. This brings me to another issue. besides the text being dense in number of results, there are too many figures (14). In my opinion some tables and figures could be added as supplementary documents (e.g. Table 1, Figures 2, 3, 6, 8, and some ‘re-analyzed’ figures). This ‘cleaning’ of the paper (i.e. reduction in the amount of results by focusing on the main ones) are my main suggestions, since the study deals with an interesting topic and the results are promising. Minor suggestions are outlined below.

Specific comments (L: lines)

L 73-75: I suggest not leaving a sentence “alone” in the text. Please, add it to a paragraph.

L 189-190: What is the criterion used to establish these categories? Distribution of data? There is a much greater amplitude in the intermediate category than in the others.

L 474: Beware, the package itself shows nothing.

I could not access the data via DOI.

Reviewer #2: - The paper claims that bilberry palability by insects following mammalian herbivory is affected by leaf nutrient concentration and that this response is intensified by shade levels.

- The claims are properly placed in the context of previous literature but the readability of the introduction can be improved. Please see comments below.

- The analyses performed support their claims. However, figure 8 regarding the correlation between insect and mammalian herbivory must be improved. The analyses show a significant correlation but for some reason that’s not clear when looking at the figure.

- Information on protocols and analyses seems to be complete.

- The paper could be published provided that the authors improve some aspects (please see comments below).

- Raw data is not included, it would be useful to include it.

- Details of the methodology are sufficient.

- Yes, the manuscript is well organized and written clearly.

Comments

Line 54: There is no connection between the previous paragraph and the paragraph starting in this line. There is a phrase missing introducing this new hypothesis. How are connected the constitutive defense and the optimal defense (OD).

Line 60: Similarly as above, the carbon:nutrient balance (CNB) hypothesis comes out of the blue. Could you please introduce with an explanatory phrase on how this hypothesis is connected with the previous one?

Line 140 to 152: Probably it would be easier for the reader if you integrate this information in the text of the introduction to connect your own hypothesis with the one in the literature.

Line 218: Which are the productivity classes? They have not been introduced so far.

Figure 4a: The scales are so different between insect herbivory and mammalian herbivory that it is difficult to see the trend of the effect of shade on mammalian herbivory. Please separate these two figures. Why in the statistics of figure 4 (lines 303 to 310) there is a report of F and P values of years 2013 and 2014? What about year 2015? Please include missing information.

Why mammals feeding on low soil productivity levels?. Also, there was something going on in 2013: -High mammalian herbivory in quadrats with high shade levels than at quadrats with low shade levels. - there was no difference in mammalian herbivory between the three soil productivity classes. While for the other years a higher mammalian herbivory was registered for low soil productivity. Could you comment on that ?

Figure 6. Please explain briefly in the figure title what you mean with “standardized mammalian herbivory”.

Figure 8. Why an R2 value is not presented in the figure. Please include it. Can you please explain in the figure legend what you mean by “adjusted” R2. The correlation does not seem very strong when the shade variable is taken away…Especially taking into account that the Y axis goes only 35%. It should be 100%.

**********

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2020 Mar 27;15(3):e0230509. doi: 10.1371/journal.pone.0230509.r002

Author response to Decision Letter 0

26 Jan 2020

Journal Requirements:

1. When submitting your revision, we need you to address these additional requirements.

Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

Response MSG: I have studied the style templates in detail and have used these style requirements in the manuscript.

Response MSG: I added this sentence: No permits for field site access were necessary, according to Norwegian law (friluftsloven: LOV-1957-06-28-16) that permitted access by foot to natural areas.

Response MSG: Not necessary to contact any relative of Harry, thanks for the offer.

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

Response MSG: no comment.

________________________________________

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

Response MSG: I assume the reason for this 'no' (reviewer #1) is explained under '5. Review Comments to the Author', see my response there.

________________________________________

3. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: No

Reviewer #2: Yes

Response MSG: All data underlying the findings in the manuscript are fully and freely available via the following URL after the manuscript has been accepted for publication:

https://doi.org/10.18710/89MLBP

Before publication, this information can be accessed via a private URL:

https://dataverse.no/privateurl.xhtml?token=87b6389f-b5cd-4453-9684-36b5cc1cc3f5

________________________________________

4. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

Response MSG: no comment.

________________________________________

5. Review Comments to the Author

General comments

Response MSG: I have moved all the mentioned text parts to the Methods-section or to Supplementary documents, as suggested below by Reviewer #1.

This brings me to another issue. besides the text being dense in number of results, there are too many figures (14). In my opinion some tables and figures could be added as supplementary documents (e.g. Table 1, Figures 2, 3, 6, 8, and some ‘re-analyzed’ figures).

Response MSG: I have moved several text parts, tables and figures to supplementary documents. To improve readability, I have changed the method, result and discussion section extensively and unneccessary analyses (not necessary for the research question and the predictions) have been removed from the manuscript.

This ‘cleaning’ of the paper (i.e. reduction in the amount of results by focusing on the main ones) are my main suggestions, since the study deals with an interesting topic and the results are promising.

Response MSG: This 'cleaning' has been done carefully and extensively, see the revised version of the manuscript.

Minor suggestions are outlined below.

Specific comments (L: lines)

L 73-75: I suggest not leaving a sentence “alone” in the text. Please, add it to a paragraph.

Response MSG: This sentence is about the Growth Rate hypothesis. As we do not use this hypothesis in the manuscript, nor refer to it in the manuscript, I have deleted this sentence.

L 189-190: What is the criterion used to establish these categories? Distribution of data? There is a much greater amplitude in the intermediate category than in the others.

Response MSG: We expected the high and low values to have most impact, and in addition they may suffer least from sampling errors, so we made the very low and very high categories narrow. This is now explained in Methods.

L 474: Beware, the package itself shows nothing.

Response MSG: I have changed the sentence 'The DHARMa package showed ...' into 'Analyses with the DHARMa package showed ...'. I have done the same at line 684 (line number as in the first submitted version).

I could not access the data via DOI.

Response MSG: All data underlying the findings in the manuscript are fully and freely available via the following URL after the manuscript has been accepted for publication:

https://doi.org/10.18710/89MLBP

Before publication, this information can be accessed via a private URL: https://dataverse.no/privateurl.xhtml?token=87b6389f-b5cd-4453-9684-36b5cc1cc3f5

Reviewer #2: - The paper claims that bilberry palability by insects following mammalian herbivory is affected by leaf nutrient concentration and that this response is intensified by shade levels.

- The claims are properly placed in the context of previous literature but the readability of the introduction can be improved. Please see comments below.

Response MSG: The readability of the whole manuscript has been improved by removing less important information, analyses and figures. Figure 8, where Reviewer #2 refers to, has been moved to the Supplementary documents in our revised manuscript, as suggested by Reviewer #1. The direct correlation between insect and mammalian herbivory, as shown in this figure, is weak, but when soil productivity and shade conditions are taken into account the correlation becomes larger (described in the manuscript).

- Information on protocols and analyses seems to be complete.

- The paper could be published provided that the authors improve some aspects (please see comments below).

- Raw data is not included, it would be useful to include it.

Response MSG: All the data, including the scripts that we have used to obtain the results in the manuscript, are fully and freely available via the following URL after the manuscript has been accepted for publication:

https://doi.org/10.18710/89MLBP

Before publication, this information can be accessed via a private URL:

https://dataverse.no/privateurl.xhtml?token=87b6389f-b5cd-4453-9684-36b5cc1cc3f5

- Details of the methodology are sufficient.

- Yes, the manuscript is well organized and written clearly.

Comments

Response MSG: I added two connecting sentences before introducing the three defense hypotheses to improve readability.

Line 140 to 152: Probably it would be easier for the reader if you integrate this information in the text of the introduction to connect your own hypothesis with the one in the literature.

Response MSG: The sentences that I have added (see my response to the comment above) connect the provided theoretical information to our own predictions.

Line 218: Which are the productivity classes? They have not been introduced so far.

Response MSG: The soil productivity classes have been introduced in lines 214-217.

Response MSG: Figure 4 has been changed (is now Figure 3) and this figure has only one axis now. The figure with mammalian herbivory has been removed.

Why in the statistics of figure 4 (lines 303 to 310) there is a report of F and P values of years 2013 and 2014? What about year 2015? Please include missing information.

Response MSG: In the revised manuscript, we removed the analyses on separate years.

Why mammals feeding on low soil productivity levels?.

Response MSG: In the revised manuscript, we removed the analyses on mammalian herbivory and soil productivity (not part of our research question nor our predictions and this improves readability of the manuscript).

Also, there was something going on in 2013: -High mammalian herbivory in quadrats with high shade levels than at quadrats with low shade levels. - there was no difference in mammalian herbivory between the three soil productivity classes. While for the other years a higher mammalian herbivory was registered for low soil productivity. Could you comment on that ?

Response MSG: In the revised manuscript, we removed the analyses on mammalian herbivory and shade as well as the analyses on mammalian herbivory and soil productivity (both are not part of our research question nor our predictions and this improves readability of the manuscript).

Figure 6. Please explain briefly in the figure title what you mean with “standardized mammalian herbivory”.

Response MSG: The “standardized mammalian herbivory” is mentioned in the main text (line 223-224). Figure 6 has been deleted in the revised manuscript.

Figure 8. Why an R2 value is not presented in the figure. Please include it. Can you please explain in the figure legend what you mean by “adjusted” R2.

Response MSG: The R2-value is mentioned in the figure legend. This whole figure 8 has been moved to Supplementary documents. We present the adjusted R2 instead of the non-adjusted R2 as the adjusted R2 is dependent on the number of variables in the model and adjusts for sample size.

The correlation does not seem very strong when the shade variable is taken away…Especially taking into account that the Y axis goes only 35%. It should be 100%.

Response MSG: I assume that this comment refers to Figure 9 in the submitted manuscript (becomes Figure 5 in the revised manuscript). Yes the variable shade is very important in the predicted results and this is mentioned in our results (lines 320-325) and our conclusions (lines 427-432). The y-axis is deliberately presented up till 35 % as the predicted values have maximum values around the value 30. By presenting values only up to 35% at the y-axis the lines in the panels are easier to distinguish from each other.

Attachment

Submitted filename: Response to Reviewers - MSG20200126.docx

Click here for additional data file.^{(31.1KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0230509.r003

Decision Letter 1

Livia Maria Silva Ataide

3 Mar 2020

Influence of light availability and soil productivity on insect herbivory on bilberry (Vaccinium myrtillus L.) leaves following mammalian herbivory

PONE-D-19-24380R1

Dear Dr. Schrijvers-Gonlag,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

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If your institution or institutions have a press office, please notify them about your upcoming paper to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

With kind regards,

Livia Maria Silva Ataide

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #1: Second assessment of the manuscript entitled “Influence of light availability and soil productivity on insect herbivory on bilberry (Vaccinium myrtillus L.) leaves following mammalian herbivory” for Plos One (PONE-D-19-24380R1)

Main comments

In this paper, the authors aimed to assess whether bilberry leaf palatability to insects is affected by light availability, soil productivity, and previous mammalian herbivory. They used a set of generalized linear mixed and additive models to test three main predictions about bilberry leaf palatability using a robust sample design. In my first assessment, I found the results and discussion very dense, with many figures to look at and many re-analyzes being described in both results and discussion. In this new version, I recognize the effort made by the authors to make the text shorter and more objective. I have no new suggestions to make. Therefore, I have a favorable opinion on the publication of this study that deals with an interesting research topic. This paper will be a good piece of work honoring the memory of Professor Harry P. Andreassen.

Reviewer #2: I have already considered that the first version of the manuscript contained an interesting research question, valuable data and a correct statistical analysis. However, there were problems with readability and with the clarity of some of the figures. The new version of the manuscript is much clearer and more enjoyable to read. It was a wise decision to put some of the figures and data as supplementary material. The authors did answer and clarify the questions I had from the previous version.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Pedro Giovâni da Silva

Reviewer #2: Yes: Karen Muñoz Cárdenas

PLoS One. doi: 10.1371/journal.pone.0230509.r004

Acceptance letter

Livia Maria Silva Ataide

13 Mar 2020

PONE-D-19-24380R1

Influence of light availability and soil productivity on insect herbivory on bilberry (Vaccinium myrtillus L.) leaves following mammalian herbivory

Dear Dr. Schrijvers-Gonlag:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

For any other questions or concerns, please email plosone@plos.org.

Thank you for submitting your work to PLOS ONE.

With kind regards,

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on behalf of

Dr. Livia Maria Silva Ataide

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 File

(PDF)

Click here for additional data file.^{(309.9KB, pdf)}

S1 Table. Insect herbivory: Estimated Marginal Means (EMMs) per shade level in the shade model.

(PDF)

Click here for additional data file.^{(12.2KB, pdf)}

S2 Table. Insect herbivory: Estimated Marginal Means (EMMs) per shade level in a linear model and the contrast estimates with Tukey's HSD test values.

Estimated marginal mean values for insect herbivory, their standard error, degrees of freedom and 95% confidence intervals are presented for each level of the variable shade in a linear model with and without year as a fixed effect. In the first model, results are averaged over the levels of the variable year. Similar information is presented for the contrast estimates; in addition, their P values based on Tukey's HSD test are given. Number of observations: 455.

(PDF)

Click here for additional data file.^{(265.2KB, pdf)}

S3 Table. Parameter estimates for the shade model of variables affecting insect herbivory on bilberry leaves.

(PDF)

Click here for additional data file.^{(15.4KB, pdf)}

S4 Table. Modeling of variables affecting insect herbivory on bilberry leaves in southeastern Norway in 2013–2015.

(PDF)

Click here for additional data file.^{(211.4KB, pdf)}

Attachment

Submitted filename: Response to Reviewers - MSG20200126.docx

Click here for additional data file.^{(31.1KB, docx)}

Data Availability Statement

The dataset and script used for the presented analyses are stored in the DataverseNO database and available at https://doi.org/10.18710/89MLBP.

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PERMALINK

Influence of light availability and soil productivity on insect herbivory on bilberry (Vaccinium myrtillus L.) leaves following mammalian herbivory

Marcel Schrijvers-Gonlag

Christina Skarpe

Harry Peter Andreassen

Roles

Abstract

Introduction

Fig 1. Light, soil and herbivory affecting bilberry defense compounds and nutrients = bilberry palatability.

Methods

Study area

Fig 2. Map of the study area (inset: White square) in southeastern Norway.

Study design

Data analyses

Prediction I: Leaf palatability and light availability

Prediction II: Leaf palatability and soil productivity

Prediction III: Leaf palatability and mammalian herbivory

Results

Fig 3. Insect and mammalian herbivory on bilberry at different light availability and soil productivity levels.

Prediction I: Leaf palatability and light availability

Prediction II: Leaf palatability and soil productivity

Prediction III: Leaf palatability and mammalian herbivory

Fig 4. Observed insect versus mammalian herbivory on bilberry at different light availability and soil productivity levels.

Table 1. Parameter estimates for the best model of variables affecting insect herbivory on bilberry leaves.

Fig 5. Predicted insect herbivory on bilberry leaves following mammalian herbivory.

Discussion

Prediction I: Leaf palatability and light availability

Prediction II: Leaf palatability and soil productivity

Prediction III: Leaf palatability and mammalian herbivory

Conclusion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Livia Maria Silva Ataide

Roles

Author response to Decision Letter 0

Decision Letter 1

Livia Maria Silva Ataide

Roles

Acceptance letter

Livia Maria Silva Ataide

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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