Exploring temporal and spatial variation in cotton tensile-strength loss to assess the ecosystem health of non-wadeable rivers

Pingram, Michael A.; Clapcott, Joanne E.; Hamer, Mark P.; Atalah, Javier; Özkundakci, Deniz

doi:10.1016/j.ecolind.2019.105773

Cited by 8 publications

(33 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Previous studies have presented strong cases for the use of functional indicators (Gessner & Chauvet, 2002), several of which highlighted the usefulness of organic matter breakdown as a function of ecological processing potential (Young et al, 2008;Tiegs et al, 2013;Pingram et al, 2020). As all river and stream ecosystems are fuelled by both exogenous and endogenous organic matter, measures of rates of decay provide an indication of the life-supporting capacity.…”

Section: Motivation and Rationalementioning

confidence: 99%

“…As all river and stream environments are fuelled by the combination of terrestrial litter inputs and instream algal material, the measurement of organic matter (OM) breakdown can provide an indication of the food-base functionality of those environments and help to determine its life supporting capacity (Wallace et al, 1997;Boulton & Quinn, 2000;Young et al, 2006;Parkyn et al, 2010). Using organic matter decomposition rates as an indicator has been studied thoroughly since the late 1950s (Hildrew et al, 1984;Webster & Benfield, 1986;Boulton & Boon, 1991), providing a strong foundation for the development of new functional indicators (Gessner & Chauvet, 2002;Young et al, 2008;Tank et al, 2010;Tiegs et al, 2013;Chauvet et al, 2016;Colas et al, 2019;Pingram et al, 2020). Various surfaces have been considered as potential mediums for which to determine organic decomposition including leaf-litter (Campbell & Doeg, 1989;Boulton & Boon, 1991;Friberg & Winterbourn, 1996;Hieber & Gessner, 2002;Barnden & Harding, 2005;Bergfur, 2007;Jinggut & Yule, 2015), wooden materials (Young et al, 2006;Parkyn et al, 2010;Niyogi et al, 2013), and cellulose/cotton materials (Young et al, 2006;Imberger et al, 2010;Parkyn et al, 2010;Clapcott et al, 2012;Tiegs et al, 2013;Tiegs et al, 2019;Pingram et al, 2020).…”

Section: Why Organic Matter Processing?mentioning

confidence: 99%

“…These have considered both small and large spatial scales including changes in habitat (Langhans et al, 2008;Collier et al, 2013a;Burrows et al, 2014), biogeography and climate (Tonin et al, 2018), and latitude (Irons Iii et al, 1994;Tiegs et al, 2019;Webb et al, 2019). Aotearoa based CS studies have considered various spatial influences on breakdown Pingram et al, 2020) though results vary at a national scale.…”

Section: Why Organic Matter Processing?mentioning

confidence: 99%

“…In relatively cool water (≤ 12 o C), macroinvertebrate mediated breakdown has been shown to follow a large Gaussian curve where microbial breakdown is much more consistent (Chauvet et al, 2016). Some studies have considered and observed influences of season on breakdown rates (Vyšná et al, 2014;Griffiths & Tiegs, 2016;Webb et al, 2019;Pingram et al, 2020), though the true nature of the interaction is not clear across different studies. This is mainly due to confounding links between the average and range of water temperatures as well as other ecological variations due to seasonal changes.…”

Section: Why Organic Matter Processing?mentioning

confidence: 99%

“…Dissolved nutrient concentrations (predominantly phosphorus and nitrogen variants) have been demonstrated to be strong drivers in OM breakdown studies (Niyogi et al, 2003;Pascoal & Cássio, 2004;Bergfur et al, 2007;Clapcott & Young, 2008;Young et al, 2008;Imberger et al, 2010;Clapcott et al, 2012;Tolkkinen et al, 2013;Piggott et al, 2015;Tant et al, 2015;Webb et al, 2019;Pingram et al, 2020). Like temperature, this has largely been attributed to microbial activity being strongly linked to nutrient enrichment (Young et al, 1994;Brown et al, 2004;Gulis et al, 2006;Tant et al, 2015).…”

Section: Why Organic Matter Processing?mentioning

confidence: 99%

See 4 more Smart Citations

Quantifying the response of a functional indicator of ecosystem health to disturbance gradients in New Zealand riverine environments: a meta-analysis

Gault¹

View full text Add to dashboard Cite

In New Zealand, recent policy changes require freshwater managers to take more comprehensive and integrated approaches to monitoring and maintaining ecosystem health. To attempt to prevent and reverse the adverse effects of land use change on freshwater ecosystems, management decisions need to be based upon a suite of indicators each with a strong foundation of knowledge regarding the nature of responses at a national scale. Monitoring ecosystem function in addition to structural indicators has long been suggested to provide a more accurate and holistic narrative of ecosystem health, however, it has yet to be adopted in routine bioassessment. The cotton strip assay has shown promise as a consistent, relatively cheap, and repeatable method for monitoring freshwater ecosystem function, indicating the ecological processing rates of riverine microbial communities and the organic matter processing potential of riverine environments. Numerous regional-scale studies have applied the cotton strip assay in New Zealand, but these data have yet to be explored in unison. For managers to successfully monitor, manage, and restore ecological processes in river environments, a comprehensive understanding of the proximate drivers of cotton breakdown is needed. The aim of this study is to conduct a meta-analysis of cotton strip assay data to explore the relationship between river function and other measures of ecosystem health and land-use stressors at a national scale. I collated published and unpublished cotton strip data to create a meta-dataset, with measures harmonised by deployment time and temperature for more meaningful comparisons at a national scale. I sourced additional data from national databases describing water quality and physical river classification information for more comprehensive, higher resolution analyses. I then used the meta-dataset was to investigate the nature of cotton decomposition responses along varying levels of impairment across different seasonal conditions and spatial catchment attributes. I used linear mixed-effects models to determine the relationships between cotton decomposition and physicochemical predictor variables, along with any additional influence attributed to underlying spatial variation across sites. Results suggest that bioavailable nutrients and water clarity are the largest drivers in cotton breakdown rates at a national scale. Water temperature and seasonal conditions emerged as likely limiting factors on microbial activity and cotton breakdown, indicating that consistent intra-seasonal monitoring is advisable. Climate and underlying geology can also be important when looking to discriminate underlying catchment variation and should be incorporated when making larger scale comparisons. Relationships with land use were found to be non-linear and likely to have too many co-varying factors enacting influence on cotton breakdown rates to be successful predictive gradients. Breakdown responses were, however, most consistent under high levels of vegetation cover, and high variability in responses in more urban and pastoral developed catchments. The assays’ sensitivity to nutrient enrichment at a national scale could aid in informing management policies with respect to nutrient limits, and the setting of natural ecosystem processing benchmarks.

show abstract

Section: Motivation and Rationalementioning

confidence: 99%

Section: Why Organic Matter Processing?mentioning

confidence: 99%

Section: Why Organic Matter Processing?mentioning

confidence: 99%

Section: Why Organic Matter Processing?mentioning

confidence: 99%

Section: Why Organic Matter Processing?mentioning

confidence: 99%

See 3 more Smart Citations

Quantifying the response of a functional indicator of ecosystem health to disturbance gradients in New Zealand riverine environments: a meta-analysis

Gault¹

View full text Add to dashboard Cite

show abstract

Parsing spatial and temporal variation in stream ecosystem functioning

2022

View full text Add to dashboard Cite

The decomposition of organic matter is a fundamental ecosystem-level process that governs nutrient cycling, fuels ecosystems, and impacts our global climate. Despite the central importance of this process for ecosystems across the planet, little is known about how the capacity of ecosystems to decompose organic matter-that is, their decomposition potential-varies across time and space. Closing this gap is needed to provide baseline information on the dynamics of ecosystems, for tracking anthropogenic impacts, and for development of practical and efficient sampling procedures. For nine consecutive years during the months of July-August, we deployed an identical organic-matter decomposition assay in the same 26 temperate deciduous-forest streams (234 stream-years total) to evaluate the interannual and among-stream variation in the decomposition of organic matter. Decomposition rates (as k values) ranged widely across all stream-years (mean = 0.026, SD = 0.018, range = 0.0020-0.094). Interestingly, among-stream variation, expressed on a per-stream basis, was more than three times greater than interannual variation (expressed on a per year basis), explaining 75% and 22% of the overall variation in our dataset, respectively. Removing the effects of temperature by adjusting decomposition rates for degree days did not substantially impact this pattern (stream: 80% of variation, year: 17% of variation). Surprisingly, despite large differences in temperature among streams, temperature explained little variation in decomposition rates, pointing to the importance of other factors. When compared to the decomposition rates from stream sites across the planet, the rates presented here spanned 27.3% of this range, highlighting the diversity of decomposition rates that can be found in a relatively compact geographic area. From the perspective of using organic-matter decomposition as a bioassessment tool, this variation could limit the sensitivity of decomposition-based assays to human impacts, although study designs could be utilized to ameliorate this problem (e.g., those that stratify by geology). The results and dataset presented here are a needed step toward a more complete understanding of how ecosystem processes vary across time and space.

show abstract

Temporal and spatial variation in bacterial communities on uniform substrates in non‐wadeable rivers

et al. 2021

Self Cite

View full text Add to dashboard Cite

Undertaking environmental assessments on non‐wadeable rivers is challenging due to their size, depth, and water velocity. The cotton strip assay (CSA) is a functional indicator used in assessing the ecological health of non‐wadeable rivers by measuring cellulose decomposition potential. Enhancing knowledge on the microbial communities responsible for decomposition would assist in developing a microbial‐based biotic index that could complement the CSA. The aims of this study were to explore the temporal and spatial variability of bacterial communities on cotton strips, identify environmental drivers of differences, and detect potential indicator taxa. Cotton strips were deployed at 12 sites, spanning a range of water quality and catchment land uses in three separate months. Each site was placed into an ecological health category (EHC) from A (healthy) to D (poor). Metabarcoding (16S rRNA) was used to characterize bacterial communities. There was a significant interaction between month and site and between month and EHC. Higher temperatures and pH were identified as key drivers of differences in bacterial communities in February (summer) and higher levels of ammoniacal nitrogen, nitrate/nitrite nitrogen, and turbidity in August (winter). After removal of amplicon sequence variants (ASVs) in low abundance, 27 taxa indicative of EHCs were identified. ASVs associated with EHC‐A were generally negatively correlated with modified land use and nitrate/nitrite nitrogen. In contrast, ASVs associated with EHC‐D were positively correlated to modified land use and temperature. With further validation, a molecular microbial index could be developed to aid in assessing the health of non‐wadeable rivers.

show abstract

Exploring temporal and spatial variation in cotton tensile-strength loss to assess the ecosystem health of non-wadeable rivers

Cited by 8 publications

References 51 publications

Quantifying the response of a functional indicator of ecosystem health to disturbance gradients in New Zealand riverine environments: a meta-analysis

Quantifying the response of a functional indicator of ecosystem health to disturbance gradients in New Zealand riverine environments: a meta-analysis

Parsing spatial and temporal variation in stream ecosystem functioning

Temporal and spatial variation in bacterial communities on uniform substrates in non‐wadeable rivers

Contact Info

Product

Resources

About