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University of Colorado, Boulder CU Scholar Undergraduate Honors Theses Honors Program Spring 2017 Vegetative Response to Long-Term Resource Manipulations in the Alpine Tundra Evelyn Beaury [email protected] Follow this and additional works at: http://scholar.colorado.edu/honr_theses Part of the Biochemistry Commons, Biodiversity Commons, Biology Commons, Ecology and Evolutionary Biology Commons, and the Plant Sciences Commons Recommended Citation Beaury, Evelyn, "Vegetative Response to Long-Term Resource Manipulations in the Alpine Tundra" (2017). Undergraduate Honors Theses. 1289. http://scholar.colorado.edu/honr_theses/1289 This Thesis is brought to you for free and open access by Honors Program at CU Scholar. It has been accepted for inclusion in Undergraduate Honors Theses by an authorized administrator of CU Scholar. For more information, please contact [email protected]. Vegetative Response to Long-Term Resource Manipulations in the Alpine Tundra By Eve Beaury Ecology & Evolutionary Biology, University of Colorado at Boulder March 13th, 2017 Thesis Advisor: Dr. Timothy Seastedt, Ecology & Evolutionary Biology Defense Committee: Dr. Timothy Seastedt, Ecology & Evolutionary Biology Dr. Pieter Johnson, Ecology & Evolutionary Biology Dr. Daniel Doak, Environmental Studies 1 Abstract Considering their sensitivity to change, alpine plant communities are useful systems in studying the indirect effects of anthropogenic activities on the environment. Climate change is increasing variability of temperature and precipitation, shifting wind patterns, and altering nutrient composition and cycling (especially deposition of nitrogen (N) and phosphorus (P)). Therefore, it is becoming increasingly important to understand how climate change impacts vegetation. This study continues efforts of a Long Term Ecological Research program in the Colorado Rocky Mountains by surveying plant community composition in response to nutrient additions (N and P) and changing moisture regimes mimicking potential climate shifts. In addition to updating such surveys, species-specific responses to nutrients and functional differences between treatments were considered in order to expand our understanding of how alpine ecosystems function. Over time, there has been a shift towards species that capitalize on added N and P rather than deposition of one or the other. This indicates that P deposition may neutralize the effects of N deposition, favoring generalist species. Additionally, alpine vegetation appears to be relatively resistant to changes in moisture caused by snowmelt. A longer growing season, as evidenced by cover increases in areas with earlier snowmelt, may increase primary productivity in the alpine tundra. Neither N nor P additions alone related to any single functional trait, but both leaf area (typically smaller in stressful environments) and chlorophyll content (indicating photosynthetic rates) appear to increase in the presence of N and P. Overall, these vegetative communities remain resistant to certain climatic alterations and may even mitigate the impacts of shifts such as N deposition and changing precipitation patterns. 2 Keywords: alpine plant communities; nitrogen; phosphorus; snowmelt; climate change Introduction The alpine tundra presents a unique study system classified by low temperatures, a short growing season, and often, a dependence on winter snowpack as a water resource during the summer. In this study, I focus on the herbaceous plants in the alpine, given this ecosystem’s dependence on vegetation to support higher trophic levels (organisms higher on the food chain), drive productivity (energy production), and withstand drastic weather changes throughout the year. In addition, the short growing season in the tundra creates a narrow window within which to collect vegetative data, and the alpine experiences change that may predict environmental response in lower-elevation ecosystems, thus providing a system to study the effects of climate change from season to season. In this study, I focus on community and functional trait (plant characteristics) responses to longterm resource manipulations in order to evaluate change over time and predict future conditions of a site in the Colorado Rocky Mountains. Specifically, I address whether or not plant community structures uphold over time in response to added nitrogen and phosphorus as well as different timings of snowmelt. Background I. On overview of research on Niwot Ridge Over the last several decades, Niwot Ridge—located 5.6 kilometers east of the Continental Divide in the Colorado Rocky Mountains—has participated in a Long-Term Ecological Research (LTER) program aimed at understanding the functioning of high- 3 elevation ecosystems. As climate change centralizes many ecological considerations, Niwot Ridge has focused its research on exploring the changes that mountain environments are likely to face under warming temperatures and shifting precipitation patterns. The alpine faces a unique balance between resilience, as an ecosystem relatively untouched by direct human impact during its evolution under naturally harsh conditions, and fragility, in that it now experiences the indirect effects of anthropogenic activities (Williams et al. 2015b). However, these factors are influenced by climate, and under the changing conditions against which the environment continues to battle, the alpine has emerged as a likely “bellwether” of climate change (Smith et al. 2009; Wookey et al. 2009; Williams et al. 2015b). That is, trends in alpine ecosystems may reflect, and help us anticipate, how areas at lower elevations will respond to global change. Under these considerations, Niwot Ridge LTER documents long-term changes due to a warming climate—in addition to other measurements—in order to predict future conditions. Thus far, research has found that the alpine is experiencing an overall increase in precipitation, a modest shift in wind patterns carrying the precipitation, a higher presence of nitrogen (N) due to human activity, and evidence of phosphorus (P) deposition as well (Bowman et al. 2015; Kittel et al. 2015; Niwot LTER unpublished data). These changes likely result in an increase in winter snowpack and a change in the timing of snowmelt, which consequently affect the length of the growing season, increase soil moisture throughout the growing season, increase microbial respiration (promoting decomposition and nutrient cycling), and cause a higher presence of shrubs in comparison to other vegetation types (Spasojevic et al. 2013; Kittel et al. 2015; Suding et al. 2015). For areas that sit below alpine ecosystems, this affects the amount and quality 4 of snow that melts down into lakes, rivers, and sources of drinking water (Williams et al. 2015a). Alpine plant species are strongly dependent on snowmelt and nutrient composition during the short growing season. In response to the shifts in these factors, plant dynamics are likely to change (Billings and Bliss 1959; Bowman 2000; Gasarch and Seastedt 2015a,b; Schmidt et al. 2015; Suding et al. 2015). Vegetation of the Niwot Ridge alpine tundra includes many species of shrubs (small woody plants), graminoids (grasses, sedges, and rushes), and forbs (herbaceous flowering plants), which typically have slow growth rates that limit their ability to quickly adjust to change (Bowman 2000). A myriad of studies through the Niwot Ridge LTER program have compiled information regarding alpine species’ responses to nutrient changes, snowpack, microbial relationships, productivity, and functional diversity, which is the set of a plant’s traits that describe its role within an ecosystem (Venn et al. 2011; Gasarch and Seastedt 2015a,b; Suding et al. 2015). These factors alter community composition, species’ dominance, and even allow new species to show presence in high-elevation ecosystems. Although alpine plant communities are susceptible to change, they have also shown resilience to date (Spasojevic at al. 2013). Whether or not this resilience will continue under ongoing climate change is a question left unanswered. II. Current theory explaining vegetative responses to resource drivers The alpine tundra of Niwot Ridge, as a naturally low-nutrient system and one greatly affected by snow, emerges as a biome thought to be especially susceptible to the effects of climate change (Ernakovich et al. 2014). For example, this area is sensitive to changes in atmospheric chemistry such as nutrients coming in from dust and changing 5 source winds, as well as N deposition through rainfall increasing from human activity and enhanced by global warming (Bowman et al. 2015; Rouston et al. 2016). These added nutrients have resulted in various plant responses dependent on community type, life form, and nutrient uptake (Bowman et al. 2015; Gasarch and Seastedt 2015a,b; Suding et al. 2015). For example, in response to high levels of N, alpine species richness and diversity tend to decrease while species that respond to N and graminoids may increase (Suding et al. 2005; Bowman et al. 2015; Gasarch and Seastedt 2015a). There is currently a gap in research involving response to P. However, individual species likely show varying effects to N, P, or the combination of the two, and many species seem to be both N- and P-limited (Theodose and Bowman 1997; Gasarch and Seastedt 2015a; Gough et al. 2016). In a changing alpine environment, the varying and species-specific responses to nutrients show one of the complicated resource interactions happening in these plant communities. As mentioned, the moisture coming from snowmelt provides an invaluable resource for alpine plant communities during the short summer growing season. An earlier snowmelt brought on by warmer temperatures, as shown by Venn et al. (2011), may result in plant functional trait responses favoring a high leaf area and plant height, indicating species that maintain water balance and compete for light. Pickering et al. (2014) supports these trends in functional traits and also finds that early snowmelt favors alpine graminoids and generalists over other life forms. Graminoids are typically taller and more competitive species, so resource shifts lengthening the growing season provide an ideal opportunity for these species to take over alpine communities (Matteodo et al. 2016). Snowmelt also triggers phenological responses, which are the events in an 6 organism’s life cycle. Although most snowbed species are familiar with, and able to adjust to, inter-annual variation, earlier flowering times may alter plant development, allocation of resources, and community distribution (Carbognani et al. 2016). These resource shifts in terms of moisture provided by snowmelt enhance competition and have the potential to affect plant processes on a species-specific level, which then change the overall distribution of plant species and their interactions. To summarize, the effects of warming, resource distributions, and timing and distribution of snowmelt have varying impacts depending on community type and functional patterns (Debinski et al. 2010; Spasojevic and Suding 2012). Species in highelevation systems, as evidenced by their persistence, have spent endless years adjusting to severe conditions. The recent warming and shift in precipitation due to climate change present trends new to most alpine species. Consequently, current literature emphasizes the importance of alpine resources and their susceptibility to the conditions brought on by environmental change. The countless interactions involved in plant communities and the individuality of species’ responses to resource shifts emphasize the need to understand the dynamics in alpine vegetation in order to predict future assemblages and to better manage resources to maintain diverse, stable, and productive ecosystems. III. Research questions and hypotheses tested here Considering the many factors discussed, the vegetation of the alpine tundra provides a unique study system to explore the effects of environmental stress in an area where time seems to move faster than at lower elevations. Therefore, this study continues efforts of the Niwot Ridge LTER program by comparing plant communities through time to monitor shifts in response to climate, evaluate the impact of snow manipulation, and 7 continue studying the effects of long-term nutrient additions. In doing so, these data aim to confirm patterns observed in previous studies, monitor the resilience of alpine environments, and make predictions about environmental response in lower-elevation ecosystems. In addition, this study adds functional trait responses into the analysis of community composition, creating a more complete idea of the biotic interactions across varying resource and landscape gradients, thus encompassing the dynamics in communities facing environmental change (Dıaz and Cabido 1997; Spasojevic and Suding 2012; Venn, Pickering, and Green 2014). In doing so, these data test why, under different treatments, certain species find success over others, why these communities are arranged as such, which traits dominate in alpine environments, and how the alpine will respond to climate change. These are important measures with the potential to disrupt alpine stability by affecting larger-scale ecosystem processes such as nutrient cycling, primary productivity, and relationships between trophic levels (Wookey et al. 2009). Methods I. Study site This study was conducted in the alpine of Niwot Ridge in the Colorado Rocky Mountains, specifically in the Saddle area (Figure 1) at an average elevation of 3500 meters (m) and 5.6 kilometers east of the Continental Divide (0° 03ʹ N, 105° 35ʹ W). The climate here is typical of an alpine tundra environment with long and cold winters and a short summer growing season lasting from mid-May until August. The average annual temperature is about -1° Celsius (C), and around 2000 millimeters of precipitation fall 8 each year (calculated from Niwot LTER public data). About 80% of this precipitation falls as snow (Williams et al. 2015a) and is redistributed across the landscape by strong winds sourcing from the northwest, thereby generating large moisture and snow-free length differences among the alpine plant communities (Kittel et al. 2015). This study area represents a diverse landscape containing several community types and a snow fence that manipulates snow depths, creating a drift as pictured in Figure 2. From 1993-2015, the fence stood 60m long and 2.6m high. For the winter of 2015-16, it was halved to 30m in length in order to measure a recovery response (i.e. the snowdrift is smaller, so the vegetation behind the removed area of the fence faced a longer growing season with less available moisture than in the 1993-2015 interval). On the Saddle, 86 2m2 plots are located within and around the snow fence—each classified as residing in a dry, mesic (moist), or wet meadow community based on the vegetation type and the natural moisture gradient of the area. In addition, these plots are subject to various nutrient enrichments as part of LTER started in 1993. The treatments include control (no added nutrients), added phosphorus (P), added nitrogen (N), or added nitrogen and phosphorus (N+P). The frequency and amounts added to each plot have been detailed in Gasarch and Seastedt (2015b), but current additions are 10 grams (g) of N per m2 as calcium nitrate and 2 g of P per m2 as superphosphate. Every other year, nutrients are distributed evenly on the soil surface across each plot. The most recent additions occurred at the beginning of the 2016 growing season. Of the 86 plots on the Saddle, only the dry and mesic meadow plots—of which there are 70—participated in the current snow manipulation study. This analysis focused on these 70 plots. Of this subset, 38 plots sit in the area originally impacted by the 60m 9 snow fence (i.e. within the manipulated snowdrift). Now that the fence has been halved to 30m, 15 of the original 38 plots sit in the recovery area, while the other 23 of the 38 plots remain within the footprint of snow generated by the fence. Therefore, to summarize, this study focused on 23 plots having added snow, 15 recovery plots, and 32 reference plots (outside of the snow fence) to total 70 plots. Each of these plots also experience one of the four nutrient treatments and consist of species common in dry or mesic meadow communities. The remaining 16 of the 86 plots are found in a wet meadow community, which were not represented within the snow fence area and were not included in this study. Figure 1: Locations in the Niwot Ridge LTER study area. Figure from Williams et al. 2015b. 10 Figure 2: Aerial image of the Saddle area of Niwot Ridge, Colorado. This image of the snow fence, standing 60 meters long and 2.6 meters high, was taken in June of 2008. This image shows accumulated snow due to the presence of the snow fence. The dry and mesic meadow plots sit in the area to the right of the snow fence both underneath and around the snowdrift currently pictured. II. Data collection and analysis Data were collected in the summer of 2016 to record community composition, which included a combination of graminoids, shrubs, forbs, bare ground, lichen, moss, rocks, and plant litter. Composition was recorded using the point intercept method with a 1m x 1m quadrat placed in the northwest corner of each plot. The quadrat was made of PVC pipe, stood about a foot above the ground using legs, and was strung with line to create a 10x10 grid (i.e. 100 points to collect data per plot). At each intersection of string, a pin flag was used to point from the quadrat directly down to the ground. I then recorded the plant species touching the pin flag. If more than one plant species occurred directly underneath a point, the second and third species were included. Plants were identified 11 down to the species level. Checking 2016 findings with those obtained in 2012 resulted in minor corrections to the raw counts of Deschampsia cespitosa and Festuca brachyphylla in seven dry meadow plots. Dry meadow plots were sampled first, from about June to July, and then the mesic meadow plots were surveyed during July. Species richness (the number of species present) was also recorded within the 1m2 area designated by the quadrat. Using these data, I calculated species diversity per plot using the Shannon Diversity Index (H’ = -Σ pi *ln(pi) where H’=diversity and pi=proportion of each species relative to total species). Plants that occurred in each plot, but were not present in composition, were given a count of 0.1 and included in species diversity. I also calculated species evenness per plot by dividing diversity by species richness to give an image of the relative distributions of species in a community. Functional trait data for plant species in the alpine were collected and reported by Spasojevic and Suding (2012) according to protocols outlined by Cornelissen et al. (2003). Traits selected for this analysis included height, stomatal conductance, chlorophyll content, leaf area (LA), specific leaf area (SLA), and percent N content. Plant height indicates competition for light, stomatal conductance correlates with water retention, N and chlorophyll content relate to photosynthetic rates, and both LA and SLA relate to a plant’s energy and water balance (Spasojevic and Suding 2012). In this study, I focused on the average traits of the ten most abundant species that dominated relative vegetative cover. Trait values for these species are reported in Table 1. Data were analyzed using R (v. 3.3.1) and Statistical Analysis Institute (SAS v. 9.4) programs. To evaluate change from 2012 to 2016, the absolute cover and relative cover per species per plot were averaged and compared between years using paired t- 12 tests. Absolute cover is the average hits of vascular plants per plot per treatment. Relative cover is given as the percent of vegetation of a certain type out of the total vascular plants per plot per treatment. This analysis combined cover for Carex scopulorum and Carex aquatilis for the 2016 values, for data from 2012 did not differentiate between these two while data from 2016 did. Community composition data were slightly skewed from an expected poisson distribution for count data, so I used generalized linear mixed-effects models to account for random effects between plots when analyzing individual species and life form (either graminoid, forb, or shrub) responses to treatments. Total cover, species richness, and species diversity each represented a normal distribution and were analyzed using generalized linear models. Species evenness data were slightly skewed, so I took the natural log of these data before analyzing them with generalized linear models. Dependent variables were tested against the presence of N, the presence of P, and the interaction between the two. When analyzing patterns in functional traits, I evaluated community trait response by focusing on the values of the ten most abundant species. Since functional trait data were measured prior to this study, for each plot, I multiplied the proportion of each species by its corresponding trait value and then summed the values for the ten most abundant species to simulate community trait response to treatments. For example, if there was a higher abundance of a taller species, this brought up the community height for a plot. I then took the natural log of these data to transform them into a normal distribution, averaged trait values across treatments, and compared them using a one-way ANOVA to specifically look at N+P versus N and P treatments (instead of testing the 13 presence of N or P on a dependent variable, which does not exclude N+P treatments when testing each nutrient individually). N content for Carex aquatilis was not recorded in the original functional trait data set, so it was excluded when analyzing this trait. Lastly, I analyzed correlations between the traits using linear models. The output of each analysis is described in the Results section, and the Appendix displays some of these data as well. Table 1: Functional trait data for plant species found on Niwot Ridge, Colorado. These data were collected and described in Spasojevic and Suding (2012). Average trait values of the ten most abundant plant species from this analysis are included, and below they are ordered from most to least abundant in terms of relative cover: Geum rossii, Deschampsia cespitosa, Carex scopulorum, Artemisia scopulorum, Trifolium parryi, Kobresia myosuroides, Carex aquatilis, Lloydia serotina, Erigeron simplex, Oreoxis alpina. Nitrogen content for C. aquatilis was not recorded and was therefore not included in %N analyses. Stomatal conductance and chlorophyll content are measured in units specific to the devices used in Spasojevic and Suding (2012). Plant Species Height (cm) Stomatal Chlorophyll Leaf Specific Nitrogen Conductance Content Area Leaf Area (%) (cm2) (cm2/g) G. rossii 12.46 199.89 540.91 7.45 95.68 1.40 D. cespitosa 40.76 207.12 339.18 3.20 76.61 1.21 C. scopulorum 27.93 180.70 500.34 5.64 140.63 2.69 A. scopulorum 16.01 239.30 246.46 2.98 154.24 2.37 T. parryi 8.08 172.28 684.47 5.18 137.30 2.65 K. myosuroides 7.74 178.90 339.55 0.48 43.25 2.67 C. aquatilis 24.40 34.34 607.94 6.98 146.53 NA L. serotina 10.51 151.83 120.55 1.62 88.12 3.90 E. simplex 9.77 205.77 541.46 1.00 171.72 2.04 O. alpina 3.84 189.90 310.44 0.94 29.00 2.13 14 Results I. Overview This study observed 47 species of vascular plants, areas of bare ground, as well as ground cover by lichen, moss, rocks, and plant litter. Across all plots, absolute cover ranged from 72 to 187 hits of vascular plants, averaging to 126.6 hits per plot. Vegetative hits correlated with productivity (Niwot LTER unpublished data). Species richness ranged from 4 to 20 species with an average of 12.9 species per plot. Richness was not correlated with plant cover. Overall, plots in the mesic meadow had significantly higher plant cover than plots in the dry meadow (p<0.000), although species richness (and diversity, but not significantly) was higher in the dry meadow (p=0.011, Figure 4). Nutrient treatments in both meadow types had fairly similar cover (Figure 3). Graminoids favored the mesic meadow (p<0.000), but forb and graminoid cover were similar within each meadow type (Figure 8). When looking at snow manipulation, the recovery plots had the highest absolute cover per plot (although there was visible evidence of earlier senescing in this area), plots unaffected by the snow fence had the second highest, and the areas remaining in the snowdrift had the lowest absolute cover per plot. To examine patterns of individual species, I focused on measures from the ten most abundant species in this analysis, which accounted for 78% of total cover of vascular plants across all plots. These included the following, in order of most to least abundant: Geum rossii (forb), Deschampsia cespitosa (graminoid), Carex scopulorum (graminoid), Artemisia scopulorum (forb), Trifolium parryi (forb), Kobresia myosuroides (graminoid), Carex aquatilis (graminoid), Lloydia serotina (forb), Erigeron simplex 15 (forb), and Oreoxis alpina (forb). These species accounted for 68% of cover in the dry meadow and 81% in the mesic meadow. Four of the most abundant species had higher cover in the mesic meadow, Oreoxis alpina (p=0.000) and Kobresia myosuroides (p=0.008) preferred the dry meadow, and cover of the remaining four most abundant species did not differ between meadow types (Figure 9). 2016 Cover Absolute Cover (total hits) 160 * 140 120 100 80 60 40 20 0 Control N N+P P Control N Dry N+P P Mesic Treatment per Meadow Type *p<0.05 Figure 3: Absolute cover for the 2016 growing season averaged across all plots in the Saddle area of Niwot Ridge, Colorado. Absolute cover is measured in total hits of vascular plants per plot, therefore excluding cover of bare ground, lichen, moss, rocks, and plant litter. Data are divided by meadow type—either dry or mesic—and secondarily by nutrient additions, which include control (no nutrients added), added nitrogen (N), added phosphorus (P), or added N and P (N+P). The asterisk (p<0.05) indicates significance between meadow types. Error bars represent standard error. II. Change through time In order to evaluate change over the last four years, data collected over the summer of 2016 were compared against data collected in 2012, as published by Gasarch and Seastedt (2015a,b). In general, canopy cover did not increase over this time period, but there were significant changes in community distribution and structure. For example, 16 over time, species richness decreased in both meadow types and all nutrient treatments except for the N+P plots in the dry meadow. Species diversity measures were also lower across all treatments, although evenness remained stable between years. When comparing trends between treatments, species richness and diversity both showed less of a negative response to N in 2016, especially in the dry meadow. Species evenness showed less of a negative response to P in the dry meadow and to N in the mesic meadow. All 2012 measures were significantly affected by N additions and meadow type. In 2016, only richness differed between meadow types (p=0.011), N affected all measures, and diversity and evenness also differed in the presence of P and N+P. Figure 4 displays these patterns for 2016. Lastly, the ratio of forbs to graminoids was similar between years. Patterns in individual species also changed over time (Figure 5). The perennial forb and most abundant species of this site, Geum rossii, showed a significant increase in cover (p<0.000) from 2012 to 2016 when ignoring individual treatments. The perennial grass Deschampsia cespitosa was the second most abundant species in both years of data collection, but it decreased significantly in absolute cover over time (p=0.027). As for the rest of the dominant species of 2016, the two species of Carex, Artemisia scopulorum, and Kobresia myosuroides showed significant increases in absolute cover (Carex p=0.000, A. scopulorum p=0.008, K. myosuroides p=0.004). The four remaining species—Oreoxis alpina, Trifolium parryi, Lloydia serotina, and Erigeron simplex—did not change in cover over the time period. Although Trifolium parryi did not increase, when grouping together the three species of Trifolium found on the Saddle (known Nfixers), cover significantly increased between years (p<0.000). Cover of the dominant alpine shrubs—three species of the genus Salix—increased between 2012 and 2016. 17 To evaluate the snow manipulation study over time, I compared plots unaffected by the snow fence with all plots affected by the snow fence. Areas impacted by the snow fence continued to have lower cover than areas outside of the snow fence. (b) Species Diversity 20 15 Average Species Diversity * 10 5 0 Control N P N+P Control Dry N P N+P Mesic 2 1.9 1.8 1.7 1.6 1.5 1.4 Control N P N+P Control N Dry P Mesic Treatment per Meadow Type Treatment per Meadow Type (c) Species Evenness Average Species Evenness Average Species Richness (a) Species Richness 0.8 0.6 Control N P N+P Dry Control N P N+P Mesic Treatment per Meadow Type *p<0.05 Figure 4: Species richness (a), diversity (b), and evenness (c) for plots in the Saddle area of Niwot Ridge, Colorado. Diversity per plot was calculated using the Shannon Diversity Index (H’ = -Σ pi *ln(pi) where H’=diversity and pi=proportion of each species relative to total species). Evenness per plot was calculated by dividing species diversity by species richness. The values per plot were then averaged together by treatment. Treatments include meadow type—dry or mesic—and nutrient additions, which are control (no nutrients added), added nitrogen (N), added phosphorus (P), or added N and P (N+P). An asterisk indicates significance (p<0.05) between meadow types. Error bars represent standard error. 18 N+P Change from 2012 to 2016 Absolute Cover (hits/plot) 30 25 * 20 15 * * * * 10 2012 2016 5 0 Plant Species *p<0.05 Figure 5: Change in absolute cover from 2012 to 2016 of the ten most abundant species found in the Saddle area of Niwot Ridge, Colorado. Absolute cover is averaged per plot. Cover from 2012 was collected and reported by Gasarch and Seastedt 2015a,b. Carex combines absolute cover for Carex scopulorum and Carex aquatilis because data from 2012 did not differentiate between these two while data from 2016 did. Error bars represent standard error. II. Snow fence For the snow manipulation study of 2016, I compared recovery plots with the plots remaining in the imprint of snow (snow plots) after the fence was halved in the winter of 2015-16. I therefore measured a first-year response to change in snowmelt and soil moisture. Overall, recovery plots had more cover per plot than snow plots (p=0.019). Despite the difference in cover, richness and diversity were similar when comparing treatments. Evenness was higher in the recovery area, but only in the N+P plots (p=0.009). Snowmelt caused differences between nutrient treatments in terms of absolute cover (Figure 6). However, the disparity in sample sizes between treatments (there is only one recovery plot receiving N compared to seven snow plots receiving N) affected 19 significance between snowmelt and nutrients, which was also evident in species-specific responses to snow. Neither life form nor any of the most abundant species were significantly affected by snowmelt alone (Figure 7). Species’ responses to snow were often confounded by nutrient additions, meadow type, or sample size. For example, Carex scopulorum favored the recovery area in the N plots (p=0.049), and Carex aquatilis responded to moisture— cover was low in dry meadow recovery plots and high in mesic meadow snow plots (p=0.033). Functional trait values of plots were not affected by snow treatments despite the growth response of the recovery area. Absolute Cover (hits/plot) Effect of Snow Fence 145 *p<0.05 * 140 135 130 125 120 Control N N+P P Control N Recovery N+P P Snow Nutrient per Snow Fence Treatment Figure 6: Effect of the halved snow fence on absolute cover in the Saddle area of Niwot Ridge, Colorado. Absolute cover is measured in total hits of vascular plants per plot, therefore excluding cover of bare ground, lichen, moss, rocks, and plant litter. Nutrient additions are control (no nutrients added), added nitrogen (N), added phosphorus (P), or added N and P (N+P). The second designation—either recovery or snow—refers to moisture manipulated by the snow fence. “Snow” refers to the area behind the snow fence that sits in a manipulated snowdrift. “Recovery” refers to the area that sits behind the part of the fence that was removed for the winter of 2015-16, and therefore the area that had an earlier snowmelt than in the previous time period. The asterisk (p<0.05) refers to significance between snow treatments. Error bars represent standard error. 20 Snow Fence and Abundant Species Relative Cover (%) 30 25 20 15 10 Recovery Snow 5 0 Plant Species Figure 7: Effect of the halved snow fence on the ten most abundant species in the Saddle area of Niwot Ridge, Colorado. Data are reported in terms of relative cover (percent of a species relative to vascular vegetation), ignoring nutrient additions and meadow type. Error bars represent standard error. III. Nutrient treatments Total cover was not significantly affected by nutrient additions. Species richness was lower in the presence of N (p<0.000). Species diversity was significantly affected by each of the nutrient treatments (N: p<0.000, P: p=0.032, N+P: p=0.028), decreasing in the presence of P. Species evenness also differed between nutrient treatments (N: p=0.005, P: p=0.026), although the moisture regime filtered these effects for N+P plots. Life form showed varying responses to nutrients (Figure 8). Both relative cover and absolute cover are given in these analyses to give an idea of how certain life forms favored treatments overall (absolute), and how they responded in comparison to the other life form (relative). For example, absolute cover of forbs responded negatively to the presence of N (p=0.006), did not respond to P, and responded to N+P differently based 21 on meadow type (p=0.016), favoring the dry meadow. Absolute cover of graminoids was significantly higher in the mesic meadow (p<0.000). Considering this, meadow type affected how graminoids responded to N (p=0.022) and P (0.007), but not to N+P. In terms of relative cover, forbs dominated over graminoids in the P and N+P dry meadow plots as well as the P mesic meadow plots. Graminoids dominated the N+P plots in the mesic meadow. Neither life form significantly dominated the other nutrient treatments (Figure 8). There were also species-specific responses to nutrients, as shown in Figure 9. Cover of Geum rossii was higher in the presence of P across all treatments (p=0.028) and was affected by N+P depending on meadow type, showing higher cover in the dry meadow (p=0.002). Deschampsia cespitosa did not respond differently based on the nutrient additions, but cover was lower in the presence of P. Carex scopulorum responded positively to P overall (p=0.010) and to N in the recovery area (p=0.049). Despite patterns in Figure 9j, variation in cover of Carex aquatilis between plots resulted in a lack of significant response to nutrients. Artemisia scopulorum was unaffected by P and favored N and N+P in the dry meadow (N: p=0.015, N+P: p=0.042), although variation between plots also affected significance of these interactions. N additions decreased cover of Trifolium parryi and Erigeron simplex (T. parryi: p=0.028, E. simplex: p=0.000). Both Kobresia myosuroides and Oreoxis alpina showed much higher cover in the dry meadow, and this preference affected their responses to nutrients, which were insignificant despite the patterns in Figures 9e and 9h. Lastly, Lloydia serotina was affected by each nutrient addition (N: p<0.000, P: p=0.001, N+P: p=0.027). Despite these varying responses, Geum rossii had an overwhelming dominance in the P and N+P 22 treatments, and in plots with added N alone, Geum rossii and Deschampsia cespitosa codominated. Cover of Forbs vs. Graminoids 80 * * Relative Cover (%) 70 * * 60 50 40 Forbs 30 Graminoids 20 10 0 Control N N+P P Control N Dry N+P P Mesic Treatment per Meadow Type *p<0.05 Figure 8: Relative plant cover in terms of life form found in the Saddle area of Niwot Ridge, Colorado. These data include vascular plants and exclude shrubs. Data are divided by meadow type—either dry or mesic—and secondarily by nutrient additions, which include control (no nutrients added), added nitrogen (N), added phosphorus (P), or added N and P (N+P). Error bars represent standard error. 50 40 30 20 10 0 * Control N N+P Dry (b) Deschampsia cespitosa * P Control Relative Cover (%) Relative Cover (%) (a) Geum rossii N N+P P Mesic 30 25 20 15 10 5 0 * Control N N+P Dry Treatment per Meadow Type P Control N N+P Mesic Treatment per Meadow Type *p<0.05 23 P (d) Trifolium parryi * 15 Relative Cover (%) Relative Cover (%) (c) Artemisia scopulorum * 10 5 0 Control N N+P P Control N Dry N+P P 20 * 15 10 5 0 Control N Mesic N+P Relative Cover (%) Relative Cover (%) 15 10 5 N N+P P Control N Dry N+P 8 6 4 2 0 Control P N N+P Dry P Control Relative Cover (%) N+P P Control N Dry Mesic N+P P Mesic Treatment per Meadow Type (h) Oreoxis alpina Relative Cover (%) N Mesic 10 (g) Erigeron simplex Control P 12 Treatment per Meadow Type 10 8 6 4 2 0 N+P (f) Lloydia serotina * Control N Treatment per Meadow Type (e) Kobresia myosuroides 0 Control Dry Treatment per Meadow Type 20 P N N+P P Mesic 10 8 6 4 2 0 * Control N N+P Dry Treatment per Meadow Type P Control N N+P Mesic Treatment per Meadow Type *p<0.05 24 P 60 50 40 30 20 10 0 (j) Carex aquatilis * Control N N+P P Control Dry N N+P Relative Cover (%) Relative Cover (%) (i) Carex scopulorum P 15 10 5 0 Mesic Control N N+P P Control N Dry Treatment per Meadow Type N+P Mesic Treatment per Meadow Type *p<0.05 Figure 9: Relative cover distributions for each of the ten most abundant species (a-j) found in the Saddle area of Niwot Ridge, Colorado. Percentages were calculated as cover of each species divided by total cover within each treatment. Total cover included vascular plants, therefore excluding hits of bare ground, lichen, moss, rocks, and plant litter. Data are divided by meadow type—either dry or mesic—and secondarily by nutrient additions, which include control (no nutrients added), added nitrogen (N), added phosphorus (P), or added N and P (N+P). Asterisks refer to significance (p<0.05) of a nutrient treatment within a meadow type, and an asterisk in the middle refers to significance between meadow types. Error bars represent standard error. IV. Functional traits In these analyses, I evaluated community trait response to treatments. Each functional trait was significantly affected by meadow type, showing higher community values in the mesic meadow (p<0.004 for all traits). However, this response was likely related to the fact that relative cover of the ten most abundant species formed a higher percentage of plant cover in the mesic meadow. In general, community functional response tended to increase in the presence of N+P, although only values for LA and chlorophyll content responded significantly (p<0.050, Figure 10). For the other traits— height, stomatal conductance, SLA, and %N—nutrient treatments did not significantly affect community response. There were strong positive correlations between all traits 25 P except for LA and %N, meaning that treatments with high measures for one trait mostly had high measures for all traits. Leaf Area 0.7 Chlorophyll Content 60 * 0.5 0.4 0.3 0.2 40 30 20 10 0.1 0 * 50 Logged Trait Value Logged Trait Value 0.6 0 Control N+P Control N+P *p<0.05 Figure 10: Significant effects of nitrogen and phosphorus on functional traits in the Saddle area of Niwot Ridge, Colorado. Trait values source from Spasojevic and Suding (2012) and include the natural log of average values from the ten most abundant species in this analysis: Geum rossii, Deschampsia cespitosa, Kobresia myosuroides, Carex aquatilis, Carex scopulorum, Lloydia serotina, Trifolium parryi, Artemisia scopulorum, Erigeron simplex, Oreoxis alpina. Traits include leaf area (cm2) and chlorophyll content (units specific to the device used). Data are divided by nutrient treatment—control plots receiving no nutrient additions and N+P plots receiving both N and P. Error bars represent standard error. 26 Discussion After exploring the patterns predicted by previous studies, including those specific to Niwot Ridge and the plots measured on the Saddle, these results confirm several key trends but also contradict important predictions about the trajectory of alpine plant communities. Although community composition and cover differed between treatments and meadow types, the lack of change in total cover over time points to resilience in the alpine, continuing essential ecosystem services such as primary productivity and biomass production to support higher trophic levels. On the other hand, declining richness and diversity over time indicate a loss of species and an increase of cover of the dominant species in most treatments. Specifically, there is greater potential for dominance in wetter areas due to a stronger community trait response and higher cover of the ten most abundant species in the mesic meadow. As for the dry meadow, N+P plots saw consistency in richness over time, showing that if both N and P were added into the alpine, these communities may preserve diversity. Other alpine studies have seen an increase in diversity due to uphill encroachment of subalpine species in response to climate change, so the loss of diversity may only be relative to this study site considering all vegetative plots were located within the same geographical area. Nonetheless, shifts in diversity can affect an ecosystem’s ability to buffer disturbance and provide services, so monitoring these shifts improves understanding of the stability of the alpine. Forbs and graminoids have continued to maintain their relative cover contributions as reported in Gasarch and Seastedt (2015b). Balance in cover between life forms reinforces findings in Wookey (2009) and Spasojevic et al. (2013) and contradicts 27 Pickering et al. (2014) and Bowman (2000)—studies that predicted increasing graminoid cover driven by a few species. Graminoids are often viewed as more competitive species than forbs and theorized to capitalize on N deposition, but forbs have shown positive responses to the combination of N and P (Theodose and Bowman 1997). The significant increase of Geum rossii at the expense of Deschampsia cespitosa in the N+P plots show a changing pattern in community dominance over the last four years, signifying Geum rossii as a generalist species and supporting forb response to N and P. Furthermore, the decline of Deschampsia cespitosa in response to N+P, despite its superior rates of nutrient cycling (Steltzer and Bowman 1998), show that P deposition appears to neutralize the benefits of increasing N, indicating the value of a species’, or life form’s, ability to capitalize on N and P rather than just N. If these nutrients are both in abundance in the alpine, the vegetative communities can mitigate soil acidification and nutrients leaching into water sources, as well as maintain efficient rates of decomposition and nutrient cycling. In addition, the amount of N sequestered in an environment relates to the amount of carbon (C) (Fisk et al. 1998). If P deposition facilitates N cycling, which then relates to C sequestration, the alpine has the potential to reduce harmful effects of climate change by sequestering C as well as sequestering N in soil organic forms. The variations between the other of the dominant species portray the complexity of community response to nutrients. There does not appear to be a uniform pattern in how nutrients affect dominance of life form, individual species, or cover in the alpine, but in several cases, N in the absence of P causes lower cover and community measures such as richness, diversity (in the mesic meadow), and evenness. Species of Trifolium are known N-fixers and have previously capitalized on P more so than N+P on Niwot Ridge 28 (Gasarch and Seastedt 2015b), which is consistent with the results found here and once again shows the importance of P deposition in cycling N. In addition, the increase of Trifolium species supports the burst of N-responders, as predicted by Bowman (2000) and Bowman et al. (2015). The increase in shrub cover over time reflects patterns across several alpine environments, including observations on Niwot Ridge (Wookey et al. 2009; Debinski et al. 2010; Spasojevic et al. 2013; Suding 2015). Therefore, there is a likelihood of shrubs threatening to invade alpine meadows, although the mechanism(s) for this increase remain unknown. Community composition and functional traits between snow regimes varied only slightly, indicating a production and cover response but not a compositional response to snowmelt. Although recovery plots had higher cover than snow plots, the consistent difference in overall cover through time between areas affected by the snow fence and areas not affected by the snow fence indicates that added snow during the entire time period of the study (beginning in 1993) overshadowed the first-year response to less moisture. Higher cover in the recovery plots may have merely been a consequence of surveying plots at different times during the season—a difference in phenology rather than an actual difference in cover. However, several studies predict that an earlier snowmelt lengthens the growing season, allowing plants a longer time to grow and increase productivity as a result (Bowman 2000; Pickering et al. 2014; Kittel et al. 2015). The growth of the recovery area reflects this, but otherwise, it does not seem as though one year of earlier snowmelt and less moisture greatly impacted the plant communities of the tundra. Alpine sites, and even different areas within alpine sites, observe dissimilarity when it comes to snowmelt. Niwot Ridge has received more precipitation through time 29 but also more rapid snowmelt, so the lack of community change in the recovery plots may not directly relate to the future of Niwot Ridge, but considering other sites are seeing a lengthening growing season, these results support the contention that the alpine tundra exhibits resilience to some variability in precipitation patterns through time. When discussing functional diversity, each of the dominant species varied between individual traits (i.e. a species with a high value for one trait did not necessarily have high values for all traits). Considering the positive trait correlations, it does not seem that the alpine selects for dominance in certain traits over others, but rather functional traits exhibit codominance within a community, even under varying treatments. Leaf area (LA) is typically smaller in stressful environments so that a plant can conserve energy and retain water. The positive response of LA to N+P indicates that N and P in unison reduce stress by relieving nutrient limitation. This is somewhat predictable considering the alpine is a naturally low-nutrient system, but it also indicates some level of adaptability in alpine plant communities considering their capacity to cycle increased nutrient inputs. Furthermore, larger leaves may provide more food for higher trophic levels during longer growing seasons in the alpine, and larger LA is more typical of forbs than grasses, so there is potential for forbs to increase in dominance in the presence of N and P. Chlorophyll content relates to photosynthesis, and since this trait was also higher in response to N+P, plants receiving these nutrients may grow more throughout the season. Cover of vegetation (and thus biomass) correlated positively with productivity (Niwot LTER unpublished data), so the increase of traits—not only those that are significant—in response to N+P likely point to an increase in primary productivity in the presence of both nutrients. Spasojevic and Suding (2012) also saw 30 increasing trait values in areas of resource abundance, but since traits used in this study were not measured as a real-time response to the nutrient additions, including functional trait measurements in future surveys of plots on the Saddle would reinforce these predictions. Conclusions and Future Directions The alpine of the Colorado Rocky Mountains remains resistant to, and potentially responds positively to, changing precipitation and increased nutrient presence as a result of climate change. Although several trends upheld through time, the change observed over the four-year time period reflects the dynamism in this alpine ecosystem. Vegetative responses to resources indicate the variability of alpine ecosystems and the importance of species-specific responses, although Geum rossii has emerged as the dominant force in the alpine tundra under most conditions. The continued encroachment of shrubs presents a threat for alpine meadows, emphasizing the importance in monitoring these species in the future. The potential for P deposition to neutralize N deposition may mitigate the N in snowmelt and precipitation that melts into rivers and high-elevation lakes, and may even promote a growth response in several alpine plant species. However, since these responses hinge on P deposition balancing N deposition, focusing future studies on incoming P compared to N would ease concerns of the impacts of N deposition on alpine plant communities. If the alpine acts as a “bellwether” of change, the observed resistance to climatic simulations may provide a positive outlook on lower-elevation ecosystems, although once again, this does appear to depend on P deposition, which may be less apparent at 31 lower elevations. In addition, these responses may only maintain ecological integrity up to a point—when vegetation can no longer cycle the influx of nutrients or prolong productivity throughout a lengthening growing season with less moisture. Looking forward, confirming incoming P though dust, observing phenological changes in response to snowmelt, measuring functional trait response to nutrients in real time, and continuously updating the vegetative surveys of this site in the Colorado Rocky Mountains will enhance our understanding of environmental responses to climate change—not only in alpine sites, but also across all environments. Acknowledgements First and foremost, I would like to thank Dr. Tim Seastedt for his help and expertise throughout this process. I would also like to thank Dr. Piet Johnson for his invaluable input and Dr. Dan Doak for his involvement. Thank you to all three for serving on my committee. Next, I would like to thank Wren Kelmen for accompanying me in the alpine and assisting with data collection. Thank you to my fellow honors students for their feedback and constant encouragement. Another thank you goes to the Marion and Gordon Alexander Memorial Fellowship for supporting me in the field. Finally, I would like to thank Dr. Katie Suding, Dr. Jane Smith, Dr. Hope Humphries, and the remaining of the Niwot Ridge community for allowing me to take part in such an in depth research endeavor. These parties have been incredibly influential in my development as an ecologist, and for that I am extremely grateful! 32 Literature Cited Billings, W.D., and L.C. Bliss. 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(2015) Vegetation change at high elevation: scale dependence and interactive effects on Niwot Ridge. Plant Ecology & Diversity 8:713-725. Theodose, A.T., and W.D. Bowman. (1997) Nutrient availability, plant abundance, and species diversity in two alpine tundra communities. Ecological Society of America 78:1861-1872. Venn, S.E., Green, K., Pickering, C.M., and J.W. Morgan. (2011) Using plant functional traits to explain community composition across a strong environmental filter in Australian alpine snowpatches. Plant Ecology 212:1491-1499. Venn, S.E., Pickering, C.M., and K. Green. (2014) Spatial and temporal functional changes in alpine summit vegetation are driven by increases in shrubs and graminoids. AoB Plants 6:1-15. Williams, M.W., Hood, E., Molotch, N.P., Caine, N., Cowie, R., and F. Liu. (2015a) The ‘teflon basin’ myth: hydrology and hydrochemistry of a seasonally snow-covered catchment. Plant Ecology & Diversity 8:639-661. Williams, M.W., Seastedt, T.R., Bowman, W.D., McKnight, D.M., and K.N. Suding. (2015b) An overview of research from a high elevation landscape: the Niwot Ridge, Colorado Long Term Ecological Research programme. Plant Ecology & Diversity 8:497-605. Wookey, P.A., Aerts, R., Bardgett, R.D., Baptists, F., Brathen, K.A., Cornelissen, J.H.C., Gough, L., Hartley, I.P., Hopkins, D.W., Laborel, S., and G.R. Shaver. (2009) 36 Ecosystem feedbacks and cascade processes: understanding their role in the responses of Arctic and alpine ecosystems to environmental change. Global Change Biology 15:1153-1172. 37 Appendix Table 2: Statistical analyses and general output for vascular plant cover, species richness, species diversity, and adjusted species evenness in response to the treatments explored in this study. Each value corresponds to the average measure per plot of each community trait (cover, richness, diversity, and adjusted evenness respectively). Treatments are meadow type, snow manipulation, and nutrient additions. The statistical distribution describes the data and the statistical test refers to the type of analysis used to evaluate the data (glm stands for generalized linear model). The interaction column indicates whether any treatments significantly interacted, meaning that the output depends on more than one treatment. If there is a significant interaction, it is mentioned, but the outputs are not. Asterisks indicate a significant effect of a treatment (p<0.05). Meadow type Snow manipulation Nutrient additions Statistical distribution Statistical test Dry Mesic Snow Recovery Presence N Presence P Presence N and P Interaction Average cover per plot normal glm 110.57 142.71* 116.70 135.20 122.56 132.31 132.00 no Average richness per plot normal glm 13.91* 11.85 11.78 12.80 10.88* 12.44 10.12 no Average diversity per plot normal glm 1.84 1.70 1.75 1.72 1.57* 1.67* 1.42* no Average adjusted evenness per plot left-skewed glm using | ln(evenness) | 0.29 0.30 0.27 0.31 0.34* 0.33* 0.40 yes snow~N~P 38 Table 3: Statistical analyses and average cover per plot in response to treatments for each of the ten most abundant species in the Saddle area of Niwot Ridge, Colorado. Treatments are meadow type, snow manipulation, and nutrient additions. The statistical distribution describes the data and the statistical test refers to the type of analysis used to evaluate the data (glmer stands for generalized linear mixed-effects model). The interaction column indicates whether any treatments significantly interacted, meaning that the output depends on more than one treatment. If there is a significant interaction, it is mentioned, but the outputs are not. Asterisks indicate a significant effect of a treatment (p<0.05). Meadow type Snow manipulation Nutrient additions Plant species Statistical distribution Statistical test Dry Mesic Snow Recovery Presence N Presence P Presence N and P Interactions G. rossii poisson glmer 27.37 36.14* 31.70 30.73 34.95 37.03* 44.38* yes meadow*N*P D. cespitosa poisson glmer 12.69 28.71* 21.57 20.80 20.03 16.75 13.38 no C. scopulorum poisson glmer 3.74 25.97* 10.39 24.87 23.91 23.44* 35.06 yes snow*N A. scopulorum poisson glmer 8.80 10.37 9.35 12.47 7.75* 9.94 7.19 yes meadow*N meadow*N*P T. parryi poisson glmer 4.31 12.74* 8.96 15.27 4.78* 8.59 2.38 no K. myosuroides poisson glmer 10.06* 1.17 1.00 0.00 3.03 4.97 1.00 no L. serotina poisson glmer 4.89 3.74 5.26 4.87 1.28* 1.91* 0.06* no E. simplex poisson glmer 5.17 3.17 5.57 6.73 1.63* 2.13 0.88 no 39 Table 3 continued Meadow type Snow manipulation Nutrient additions Plant species Statistical distribution Statistical test Dry Mesic Snow Recovery Presence N Presence P Presence N and P Interactions O .alpina poisson glmer 5.63* 1.69 1.00 3.73 3.41 4.47 5.75 no C. aquatilis poisson glmer 4.66 4.77 10.57 5.80 8.00 6.59 10.13 yes meadow*snow 40