Basic and Applied Ecology 32 (2018) 103–109 Soil nutrients indirectly influence intraspecific plant selection in white-tailed deer Jacob L. Dykes a , ∗ , Bronson K. Strickland a , Steve Demarais a , Daniel B. Reynolds b , Marcus A. Lashley a a Department of Wildlife, Fisheries, and Aquaculture, Mississippi State University, Mississippi State, MS 39762, USA b Department of Plant and Soil Sciences, Mississippi State University, Mississippi State, MS 39762, USA Received 4 April 2018; accepted 5 August 2018 Available online 9 August 2018 Abstract Few attempts have been made to determine how soil productivity influences diet selection in herbivores, likely because environmental characteristics known to influence diet selection such as plant community structure and herbivore nutritional demands are often confounded with changes in soil productivity. We designed a soil-amendment experiment to isolate the effects of soil productivity on diet selection by manipulating soil productivity and quantifying intraspecific plant selection within a population of white-tailed deer ( Odocoileus virginianus ). We hypothesized soil productivity would indirectly influence deer plant selection by directly affecting plant tissue chemistry. Soil productivity indeed influenced diet selection indirectly because soil amendments only affected deer plant selection when palatable plants were present. Soil amendments increased plant phosphorus concentrations, and plant phosphorus concentrations explained 47% of the variation in diet selection. Thus, our data indicate plant nutritional quality mediates the indirect effects of soil productivity on herbivore diet selection. Previous research demonstrating differential influences of herbivory on plant communities across a soil productivity gradient may in part be explained by indirect effects of soil productivity on diet selection. © 2018 Gesellschaft f ̈ ur ̈ Okologie. Published by Elsevier GmbH. All rights reserved. Keywords: Diet selection; Herbivore; Nutrient addition; Nutritional quality; Soil productivity; Deer Introduction Soil productivity is a measure of the primary produc- tivity that a given soil type can sustain based on nutrient availability (Keddy, Twolan-Strutt, & Shipley 1997). Soil productivity ultimately shapes plant communities (Venterink, Van der Vliet, & Wassen 2001) by regulating plant species abundance, composition, and tissue chemistry (Demchik & Sharpe 2001; Juice et al. 2006; Jones, Demarais, Strickland, & Edwards 2008). Soil nitrogen (N), phosphorus (P), and ∗ Corresponding author. E-mail address: jld475@msstate.edu (J.L. Dykes). potassium (K) are the primary nutrients responsible for reg- ulating these community characteristics (Bridgham, Pastor, Janssens, Chapin, & Malterer 1996; Verhoeven, Koerselman, & Meuleman 1996; Van Duren & Pegtel 2000). Nitrogen availability is perhaps most important because it is often limited and strongly influences species composition by pro- moting plants with adaptations to use alternative nitrogen sources when soil N is low and by promoting plants adapted to exploit soil N when it is abundant (Tamm 1991; Aerts & Chapin 1999). Because of the direct influences of soil productivity on plant communities, soil productivity has a strong indirect influence on nutrient availability to herbi- vores (Cowan, Jordan, Grimes, & Gill 1970; Blair, Short, & https://doi.org/10.1016/j.baae.2018.08.001 1439-1791/© 2018 Gesellschaft f ̈ ur ̈ Okologie. Published by Elsevier GmbH. All rights reserved. 104 J.L. Dykes et al. / Basic and Applied Ecology 32 (2018) 103–109 Epps 1977; Chapin 1980; Biere 1995; Fraser & Grime 1998). For example, Fraser and Grime (1998) documented a 50% increase in plant biomass grown in highly fertile soil com- pared to plants grown in soil with low fertility, subsequently increasing herbivore abundance. Disentangling the effects of soil productivity on diet selec- tion is difficult because plant community structure and animal nutritional demands are confounding factors linked to soil productivity. In addition to the large literature base link- ing soil productivity to changes in plant communities, soil productivity is also linked to variation in herbivore pheno- type (Gill 1956; Gaillard, Delorme, Boutin, Van Laere, & Boisaubert 1996; Strickland & Demarais 2000; Herfindal, Saether, Solberg, Andersen, & Høgda 2006; Jones et al. 2008, 2010a; Lehoczki, Erdélyi, Sonkoly, Szemethy, & Csányi 2011), and more importantly, fitness (Gill 1956; Jones, Strickland, Demarais, & Blaylock 2010b). This is prob- lematic for understanding how soil productivity affects diet selection because the structure of plant communities and the nutritional demands of animals contribute to plant selection (Vangilder, Torgerson, & Porath 1982; Ceacero et al. 2009, 2015; Dykes 2018). Thus, to fully understand how soil pro- ductivity affects diet selection, an experiment designed to manipulate soil productivity while controlling for changes in the plant community and animal nutritional demands is needed. We designed a soil-amendment experiment where we manipulated soil productivity to determine how intraspecific plant selection was influenced within a population of white- tailed deer ( Odocoileus virginianus ; hereafter deer). Because we used a single plant species and our manipulated gradient in soil productivity was accessible by the same population, our design enabled us to control for influences of plant commu- nity structure and animal nutritional demands. Moreover, we conducted an additional paired trial with the same manipula- tions but without the presence of a palatable plant to ensure any observed changes in behavior were not directly linked to soil amendments. We hypothesized that soil productivity would indirectly influence deer plant selection. We tested three predictions from that hypothesis: (A) soil productivity would influence deer plant selection but only when a palatable plant was present, (B) soil amendment would increase plant nutrient concentrations, and (C) changes in plant nutrients would explain deer plant selection (Fig. 1). Materials and methods Experimental design We conducted this study at the Andrews Forestry and Wildlife Laboratory located in the Interior Flatwoods soil region of Oktibbeha County, Mississippi. The property totals 220 ha comprised of about 210 ha of loblolly pine ( Pinus taeda ) forest and 10 ha of forest openings. We used a randomized block design to account for biases associated with microsite conditions (e.g., moisture, shade, Fig. 1. Conceptual diagram of hypothesis: soil productivity indi- rectly affects white-tailed deer ( Odocoileus virginianus ; hereafter deer) plant selection, and three associated predictions: (A) soil pro- ductivity would influence deer plant selection but only when a palatable plant was present (dashed line indicates indirect effect); (B) soil amendment would increase plant nutrient concentrations, and (C) changes in plant nutrients would explain deer plant selection. deer behavior, topography). We established experimental blocks in separate forest openings. Each block (n = 4) con- tained 9 plots (plot size = 0.02 ha) in which we randomized soil-amendment treatments. To prepare plots for planting, we used broad-spectrum herbicide, mowing, disking, and tilling to remove competing vegetation. We collected soil sub- samples randomly throughout each individual experimental block and combined for a single soil sample represent- ing that particular block. Soil analyses were completed at the Mississippi State University Extension Soils Laboratory (http://extension.msstate.edu/lawn-and-garden/soil-testing). Each randomized block included four plots of a cool- season legume, balansa clover ( Trifolium michelianum ), and four plots of a cool-season cereal grain, winter wheat ( Triticum aestivum ), planted on October 5, 2016. We chose balansa clover and winter wheat due to their popularity in deer food plots, availability, and differences in plant phenology. Treatments were applied to plots on October 6, 2016 and included control (no amendment), nutrient addition (NPK fertilizer), pH neutralization (CaCO 3 lime), and pH neu- tralization + nutrient addition (lime + fertilizer, Fig. 2). Soil amendment (i.e., lime and fertilizer) volumes were deter- mined by recommendations from laboratory soil analyses for peak soil productivity conditions in the respective block and thus varied across blocks. In addition, we monitored deer vis- itation in an unmanipulated fallow plot within each block to account for deer occurrences not associated with plantings or soil-amendment treatments. Comparing selection of palatable and unpalatable plants allowed us to disentangle direct and indirect effects of soil-amendment treatments on deer plant selection. All plants were protected from herbivory by electric fencing until April 2017 when balansa clover was actively grow- ing and presumed palatable but winter wheat had senesced which is generally considered unpalatable (Ball, Hoveland, & Lacefield 2007; Lashley, Chitwood, Harper, Moorman, & DePerno 2014; see Supplementary Appendix A). This comparison allowed us to determine if the soil-amendment treatment itself influenced deer plant selection directly. J.L. Dykes et al. / Basic and Applied Ecology 32 (2018) 103–109 105 Fig. 2. Experimental design quantifying white-tailed deer ( Odocoileus virginianus ) plant selection across a cool-season legume and cool- season cereal grain, planted on October 2016, receiving treatments to manipulate nutritional quality. Balansa clover ( Trifolium michelianum ) and winter wheat ( Triticum aestivum ) were randomly assigned and planted separately in four equal-sized 13 × 13 m adjacent plots within each block. To manipulate intraspecific plant qualities, each plot excluding the fallow plot received one soil-amendment treatment (according to soil analyses): control (no amendment), nutrient addition (NPK fertilizer), pH neutralization (CaCO 3 lime), or pH neutralization + nutrient addition (lime + fertilizer). Each plot was protected by an electric fence until April 2017 then monitored with camera traps for a period of 2 weeks in Oktibbeha County, MS. Plant sampling Immediately before allowing herbivore access to plants, we sampled all plant biomass within a randomly placed 0.80 m 2 sampling quadrat at an above ground height of 4 cm to mea- sure available biomass within each plot. Following Lashley et al.’s (2014) plant handling protocol, we dried plant sam- ples to constant mass in a convection oven at a temperature of 47 ◦ C. Samples were weighed to the nearest gram and then shipped to Dairy One Forage Lab (http://dairyone.com; certi- fied by the National Forage Testing Association) for nutrient analysis. We measured 14 nutritional parameters that might influence diet selection based on previous literature: crude protein (CP), protein solubility (Prot. Solub.), neutral deter- gent fiber (NDF), calcium (Ca), phosphorus (P), magnesium (Mg), potassium (K), sodium (Na), iron (Fe), zinc (Zn), cop- per (Cu), manganese (Mn), molybdenum (Mo), and sulfur (S) (McDowell 1992; Robbins 1993). Animal sampling Deer plant selection was monitored during feeding bouts with motion-triggered camera traps on the perimeter of each plot set with a 1-minute delay between pictures. Fences were removed from two blocks in early April to allow herbi- vore access for a 2-week feeding bout, electric fencing was reestablished and then removed from the other two blocks for a 2-week feeding bout at the end of April. We used a 2-week feeding bout to ensure no plots were depleted, effec- tively influencing selection, and to ensure appropriate sample sizes were obtained to make accurate and precise estimates of behavior (Rowcliffe, Kays, Kranstauber, Carbone, & Jansen 2014; Lashley et al. 2018). We recorded the posture of each deer in each photograph. Posture was recorded in all pictures as alert, actively feeding, or searching (Lashley et al. 2014; Cherry, Conner, & Warren 2015; Biggerstaff, Lashley, Chitwood, Moorman, & DePerno 2017; Schuttler et al. 2017). Each deer photographed in the actively feeding posture was classified as a selection event for that particular plot (Lashley et al. 2014; Biggerstaff et al. 2017). Thus, in group sizes >1, a single picture could yield >1 selection event. Data analysis To assist in preventing bias due to failed plots (i.e., too little biomass to be attractive), we plotted the distribution of biomass for each forage type and removed the 25% quar- tile, considering them failed plots. We then used R (Version 3.4.1, www.r-project.org) to complete all statistical analyses. We used the GLM function with Poisson-distributed errors to perform linear regressions relating deer plant selection to soil-amendment treatment with and without a palatable plant present. We used various data transformations (i.e., square- root, cubed-root, log) to address the assumptions of normality of each variable when necessary. We used Welch’s t -test due to unequal variance and sample size to assess if mean plant biomass was similar between plots with and without a palat- able plant present. We performed an analysis of variance to test the effect of treatment on nutrient concentrations in palat- able plants. We adjusted deer plant selection in each plot by subtracting the number of deer photographed actively feeding 106 J.L. Dykes et al. / Basic and Applied Ecology 32 (2018) 103–109 within the associated fallow plot. This allowed us to account for random deer visitation not associated with plant selection. We then used linear models to evaluate the influence of plant nutrients on deer selection of palatable plants. An alpha level of ≤ 0.05 was used to determine significance. Results We collected 3493 photographs of deer containing 5099 individuals. Of those, 49% of deer were photographed in the actively feeding posture and classified as a selection event. We detected 93% more total deer and 94% more deer in the actively feeding posture in the palatable plots than unpalat- able plots. Biomass did not differ between the palatable and unpalatable plants (two-sample t -test, df = 21.199, t = 0.658, p = 0.518; see Supplementary Appendix A). Deer plant selec- tion was influenced by all treatments in the palatable plants but had no effect in the unpalatable plants (Figs. 1 A and 3 A; Table 1). We obtained a sample size > 100 in all plots containing a palatable plant which is the minimum sample size recommended when using camera trap data (Lashley et al. 2018). Plant biomass (ANOVA, df = 3,12, F = 4.416, p = 0.026), P (ANOVA, df = 3,12, F = 8.704, p = 0.002; Figs. 1 B and 3 B), and Mg (ANOVA, df = 3,12, F = 4.441, p = 0.026) were affected by the nutrient addition, pH neutralization, and pH neutralization + nutrient addition treatments in the palat- able plants. We removed Mg from the model evaluating the influence of plant nutrients on deer selection of palatable plants because of multicollinearity with P (R 2 = 0.79) and generally P has been presented as a more important nutri- ent in diet selection of white-tailed deer (Lashley, Chitwood, Harper, Moorman, & DePerno 2015). Phosphorus (p = 0.019) but not biomass (p = 0.739, R 2 = 0.002) had a positive influ- ence on deer plant selection and P concentration explained almost half of the variation in plant selection (R 2 = 0.47; Figs. 1 C and 3 C). Discussion Soil productivity indirectly influenced diet selection by altering P concentrations in plant tissues. Increased plant P concentrations may have been a direct effect of P addi- tion or indirectly the addition of N to the soil depending on which nutrient is more limiting to plant growth (Tessier & Raynal 2003). Our results are consistent with the Thornley model of photosynthate partitioning, whereby soil nutrient addition favored photosynthate partitioning of xylem-mobile nutrients to the leaf organs, effectively elevating leaf P con- centrations (Marschner, Kirkby, & Cakmak 1996). The fact that we did not observe an increase in leaf N is likely an indi- cation our plants were P-limited, which is also supported by our relatively high N:P (i.e., 12:1) in plant leaves from control treatments. Also, because plants had access to full irradiance, photosynthetic capacity was likely maximized without nutri- ent additions, and because leaf N is highly correlated with leaf photosynthetic capacity, we should not expect leaf N to be affected by nutrient additions in this experiment (Evans 1989). Because P is often a limiting nutrient to primary pro- duction in terrestrial ecosystems (Elser et al. 2007; Vitousek, Porder, Houlton, & Chadwick 2010), and therefore to her- bivores, it may be the most important nutrient in herbivore diet selection (Vangilder et al. 1982; Grasman & Hellgren 1993; Hewitt 2011; Lashley et al. 2015). Thus, coupling our results with previous experiments suggests factors affecting P availability in leaf organs may determine the probabil- ity of herbivore selection across many terrestrial landscapes (Campo & Dirzo 2003; Santiago et al. 2012; Lashley et al. 2015). Soil productivity indirectly influencing herbivore foraging behavior may partially explain differential herbivore effects on plants across soil productivity gradients. Several studies suggest soil productivity gradients are important when con- sidering herbivore effects on plant diversity (Grubb 1992; Ritchie, Tilman, & Knops 1998; Ritchie & Olff 1999), regen- eration, and propagule transport (Olff & Ritchie 1998). Large herbivores can increase plant diversity across productivity gradients by affecting seed dispersal, regeneration success, and soil nutrients through excrements (Steinauer & Collins 1995; Olff & Ritchie 1998). However, plant diversity may decrease across a soil productivity gradient when large her- bivore densities are high relative to the productivity of the soil (Milchunas, Sala, & Lauenroth 1988). Our data indicate differences in herbivore effects on plant communities across these gradients may be in part indirect as a result of shifting herbivore behavior. Previous studies have documented the influence of vari- ous abiotic factors to changes in morphometrics and fitness of ungulates (Jacobson, Guynn, Castle, & Hackett 1977; Mysterud, Langvatn, Yoccoz, & Chr 2001; Herfindal et al. 2006; Strickland & Demarais 2006; Jones et al. 2008; Simard, Côté, Weladji, & Huot 2008; Jones et al. 2010a; Lehoczki et al. 2011). For example, Jacobson (1984) found deer body mass and antler size to be positively correlated with soil nutri- ents. Similarly, Strickland and Demarais (2000) reported deer growth rates, body mass, and antler size varied significantly over soil regions in Mississippi. Horrell, Cohen, Miller, and Chamberlain (2015) noted a significant correlation between forage Ca concentrations and deer body mass and antler size. However, much of the research dealing with those morpho- metric and fitness advantages as a result of increasing soil productivity has assumed linear increases in forage quality are responsible even though data presented indicate a nonlin- ear effect of soil productivity on intraspecific forage quality across plant species (Jones et al. 2008; Horrell et al. 2015). In fact, in some plant species, intraspecific forage quality actu- ally declined with increasing soil productivity. We provide evidence that morphometric and fitness advantages could be in part related to the ability of herbivores to track and alter diet selection to exploit intraspecific fluctuations in forage quality rather than only increases in baseline nutrition in the environment. J.L. Dykes et al. / Basic and Applied Ecology 32 (2018) 103–109 107 Table 1. Parameter estimates for generalized linear model with Poisson-distributed errors and an alpha value of ≤ 0.05 predicting white- tailed deer ( Odocoileus virginianus ) plant selection based on soil-amendment treatments: control (no amendment), nutrient addition (NPK fertilizer), pH neutralization (CaCO 3 lime), and pH neutralization + nutrient addition (lime + fertilizer) to palatable plants (balansa clover, Trifolium michelianum ) and unpalatable plants (winter wheat, Triticum aestivum ) in Oktibbeha County, MS, April 8–May 9, 2017. Term Estimate Std. error Z value Pr (>|z|) Palatable (Intercept) 3.2189 0.2000 16.094 <0.001 Fertilizer 2.3924 0.2023 11.828 <0.001 Lime 0.9555 0.2124 4.498 <0.001 Lime + fertilizer 1.9601 0.2035 9.632 <0.001 Unpalatable (Intercept) − 1.63E + 01 1.49E + 03 − 0.011 0.991 Fertilizer 1.56E + 01 1.49E + 03 0.010 0.992 Lime − 3.30E − 10 2.10E + 03 0.000 1.000 Lime + fertilizer 1.94E + 01 1.49E + 03 0.013 0.990 Fig. 3. (A) Box and whisker plot depicting effects of soil-amendment treatments: control (no amendment), nutrient addition (NPK fertilizer), pH neutralization (CaCO 3 lime), and pH neutralization + nutrient addition (lime + fertilizer) on white-tailed deer ( Odocoileus virginianus ) selection of a palatable plant (balansa clover, Trifolium michelianum ). (B) Box and whisker plot depicting effects of soil-amendment treat- ments: control (no amendment), nutrient addition (NPK fertilizer), pH neutralization (CaCO 3 lime), and pH neutralization + nutrient addition (lime + fertilizer) on phosphorus concentrations in a palatable plant (balansa clover). (C) Scatterplot depicting effects of increased plant phosphorus concentration on deer selection of a palatable plant (balansa clover) in Oktibbeha County, MS, April 8–May 9, 2017. There is ample evidence herbivores can discriminate between high and low quality plant species (Awmack & Leather 2002; Ceacero et al. 2009, 2015) and the ability to differentiate between plants of varying quality is nec- essary to maximize fitness (Gillette, Huang, Hatcher, & Moroz 2000; Sinervo 2013, chp. 6). Post-ingestive feedback has been proposed as the mechanism enabling ungulates to discriminate between plant species of different nutritional quality (Provenza 2005). However, this mechanism has not been thoroughly investigated for intraspecific diet selection. Within plant species, visual and chemical cues may con- found how animals respond to the post-ingestive feedback. Because intraspecific plant quality can vary widely with soil productivity, future research is needed to develop a basic understanding of how herbivores detect intraspecific differ- ences in nutritional quality to improve our understanding of herbivore-plant interactions. 108 J.L. 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