During the past decade, shale resources have been heavily developed in the United States, an industry that will steadily increase over the next several years [10]. The majority of environmental impacts that stem from these activities parallel those recorded for traditional petroleum-extraction, and as such can be predictably monitored [23]. Others are instead UNG-specific, such as poor well integrity and accidental wastewater release, and are compounded by the geographic distribution of shale plays across the continent [24] (Fig. 1a). Environmental risks associated with UNG are hence more difficult to predict and to track, in that sufficient data regarding their breadth and depth have yet to accumulate. This, in turn, delays the designation of appropriate environmental policies that would otherwise provide for their regulation [25, 26].
Research activities that evaluate these impacts are ongoing in the Fayetteville Shale of northwest Arkansas [19, 20] (Fig. 1b, c), and have now been expanded so as to encompass biofilm communities as biological indicators of study catchments (this study). The composition of microbial communities reflects sensitivity and exposure of these catchments to anthropogenic activities [14], such as urbanization, deforestation, agricultural development, habitat fragmentation, and others [27], including UNG-extraction. It is of interest to potentially parse these situations according to the manner by which they drive stream microbial diversity. Similarly, ecosystem processes are also driven by hydrology, stream gradient, stream order, and stream chemistry (among others), and these also modulate the composition of biofilm communities [15]. Given this, we first tested (and rejected) the hypothesis that environmental variability was similar among our minimally impacted (MICZ) versus potentially impacted (PICZ) study sites.
Ecological variation among study sites
Instead, we found significant differences among several test variables, as evaluated by Group. For example, MICZ-sites reflected catchments with significantly greater ‘%-forested’ area, but significantly less ‘%-pasture’ (Table 2). Of interest is the fact that several other variables showed elevated but not significantly different values, as gauged by the Bonferroni-corrected probability value for multiple comparisons. We comment on this situation below.
Significant environmental differences between the two groups were also noted when multivariate analyses incorporated the ten variables across the three categories. Sites separated along PC-1, with strong positive (MICZ) and negative (PICZ) loadings manifested according to stream morphology, anthropogenic land use, and water chemistry (Fig. 4a). There was also considerably more variance among PICZ-sites, with paired catchments (i.e., 2-A/2-C and 2-D/ 2-B) well separated on PC-2. Somewhat surprisingly, these sites also showed a strong and concerted response to those variables not deemed significant in the univariate analyses. MICZ-sites displayed much less variability, yet were similarly separated on PC-2 according to a composite of variables that were significant (i.e., ‘%-forest’) and non-significant (i.e., ‘slope’ and ‘elevation’).
The univariate statistics provided differentiation by Group according to individual variables evaluated singly whereas the multivariate analyses provided broader patterns much more interpretable at the ecosystem level, yet not apparent from the separate univariate analyses. This was due largely to the reduced degrees of freedom in the univariate analyses, as constrained by small sample sizes parsed between groups and gauged with Bonferroni-adjusted probabilities. Although our multivariate analyses did not provide statistical probabilities within a hypothesis-testing framework, they more easily depicted the disparity within- and among-Groups, as promoted by watershed, land use, and water chemistry.
The variability in biofilm communities among study sites
Having established the environmental context for our sampling sites by Group, we could then contrast their biofilm communities (Fig. 4b). Groups again separated in multivariate space, albeit less distinctively and with a greater spread among PICZ-sites along PC-1. PICZ-sites also exhibited less variation than did MICZ-sites along PC-2. Clearly, microbial composition varies both among- and within-sites, but with different microbial taxa driving this result in each Group.
For example, Spartobacteria (non-significant in the 1-way ANOVA) clearly associated with MICZ-site 1-C, and differentiated it from all others, whereas site 1-B (associated with 1-C in Fig. 4a) was arrayed quite distantly from other MICZ-sites on PC-2. Furthermore, one site from each Group (i.e., 1-D/ 2-A) fell close to the origin of the PC-axes, suggesting a low overall diversity in their microbial composition (results not shown).
These differences indicate a disparity between biofilm community composition and environmental variability among sites, a result that parallels those from other studies. For instance, microbial assemblages will often group according to historical (i.e., phylogenetic) events [28], but also in response to more contemporary biochemical conditions associated with streams [29]. In this study, numerous factors (per Tables 1, 2 and 3) obviously impact the relationship between biofilm communities and their environment. This result confounds any ‘cause-and-effect’ scenarios for the observed patterns. However, we draw two strong conclusions from the multivariate analyses: PIZC-sites display greater ecological variability within the environmental matrix (Fig. 4a), yet are much less variable when embedded within the biofilm community matrix (Fig. 4b).
An alternate approach would be to contrast our results with those from studies in other shale plays that employed biofilm communities as bioindicators of fracking. Yet many of the latter are tangential to the present study, in that they examined biofilm communities in either flowback [30] or produced waters [30, 31]. Few evaluated stream catchments into which groundwater from fracked sites would eventually percolate, as herein. One study that did so evaluated headwater streams in the Marcellus shale (PA) (Fig. 1a), and found significantly lower species richness and evenness values at sites impacted by fracking [24]. Several of these sites also contained an abundance of bacterial OTUs that correlated positively with decreasing pH, suggesting more acidic stream environments. The diversity of carbon sources available in a stream promotes the functioning of its biofilm communities, and as diversity decreases, so does the community [32]. In this sense, a reduction in carbon sources would be an ecological explanation for the observed reduction in species richness at these sites, although this was not stated as such.
The richness and evenness of species within biofilm communities
In our study, the species richness, evenness, and number of OTUs in biofilm communities were not significantly different when compared between MICZ- and PICZ-sites. Yet such comparisons often mask the interactions among OTUs within these communities. For example, a decrease in abundance of some taxa can also stimulate growth in others normally more rare, a situation that would promote rather than depress evenness [29, 32]. Those streams with lowest values for evenness in each of our Groups [i.e. 1-B and 2-D; 21] may indeed reflect this consideration. For example, 1-B is a headwater stream (stream order = 1) with the greatest ‘%-forest’ in the study (=96%) both of these environmental aspects would promote deposition of leaf litter into the stream that, in turn, must be decomposed. This similarly constrains the biofilm community.
The two least diverse streams in an ecological sense (i.e., 1-A and 1-B) also had low numbers of OTUs [21], again suggesting the potential for a reduction in available nutrients [19]. In a similar vein, PICZ-site 2-D had the highest value for ‘%-pasture’ in the study, and was also associated with elevated levels of available phosphates and nitrates (Fig. 4a), both of which can promote a few dominant species. This was represented at PICZ-sites by the elevated abundances of two Cyanobacterial classes (i.e., Synechococcophycideae and Oscillatoriophycideae). Cyanobacteria are primary producers that seemingly track the significantly elevated levels of nitrogen and phosphorus found in these streams.
A second but related limitation with regard to species richness and evenness is the strong competition among bacteria and hyphomycetes (stream fungi), as promoted by the reduction in dissolved organic matter (DOM) [27]. Dissolved nitrogen primarily exists as nitrates within ground and surface waters, and must be transformed by microbes before entering into and moving through the ecosystem. This, in turn, could promote bacterial OTUs more strongly competitive, at the expense of those less competitive, a situation that would also constrain biofilm community diversity. In addition, and as a second consideration, elevated nitrogen levels are often associated with UNG well sites [19].
Additionally, the removal of pollutants can, paradoxically, also reduce microbial diversity and evenness [33], suggesting (as above) that external sources of carbon can promote the development of OTUs normally more rare. These caveats, in turn, provide numerous potential corollaries to explain the low values for evenness at sites, particularly when carbon sources have become more limited due to fracking [24, 32].
Biofilm communities as bioindicators
The function of many bacterial lineages is not well understood at the ecosystem level, despite their abundances in soil and aquatic systems, and this in turn makes it more difficult to ascertain their status as potential bioindicators. Despite this, general functions are indeed assignable to some clades. Many Synechococcophycideae, for example, employ unique metabolic pathways that allow them to persist in highly acidic environments such as volcanic seeps. The Oscillatoriophycideae is an equally diverse clade that can also serve a bioindicator for organic pollutants. For example, Microcystis (a genus of Oscillatoriophycideae) is abundant at PICZ-sites, and its presence may point to the presence of elevated polycyclic aromatic hydrocarbons (PAHs) that in turn promote its growth [34].
In addition, the genomes of aquatic Spartobacteria encode for a diversity of glycoside hydrolases that are employed in the degradation of complex carbohydrates [35]. This physiological aspect also explains its common co-occurrence with Cyanobacteria, in that the former metabolizes the complex carbohydrates produced by the latter [12]. Spartobacteria should thus positively correlate with Cyanobacteria at PICZ-sites, but was instead found to be significantly reduced. Brine contamination is a well-known fracking by-product, and it continues to be pulled upwards from deeper strata long after drilling has subsided [36]. In addition, PICZ-sites also reflected greater conductance in their water chemistry. Spartobacteria has a pronounced intolerance for salt, and these environmental conditions at PICZ-sites would impede its expected proliferation.
In an attempt to gain a more comprehensive perspective, we can also contrast results from this study with those from earlier studies at the same sites. For example, UNG development had a definite impact on stream macroinvertebrate communities, with short-lived generalists being more abundant at those sites [20]. Yet these effects were difficult to parse across specific taxa, or to specifically associate with the benthic habitat found at PICZ-site.
A second study [19] found increased primary production and eutrophication at sites impacted by UNG activities, and this was interpreted as a potential response to the enhanced levels of nitrogen these sites displayed. Our data support these conclusions in that two classes of Cyanobacteria were clearly more abundant at impacted sites, suggesting the presence of an environment that is beneficial for primary production. Our statistical analyses also verified significant levels of ‘total nitrogen’ and ‘total phosphorus’ at these sites, as well as heightened conductance.
Overall, the observed differences between MICZ-sites and PICZ-sites may reflect the accessibility of sites chosen for UNG well construction, and as such, may add an additional consideration for the design controlled studies to gauge the effects of fracking (see Discussion).