scholarly journals Ecology of peatland testate amoebae in Svalbard and the development of transfer functions for reconstructing past water-table depth and pH

2021 ◽  
Vol 131 ◽  
pp. 108122
Author(s):  
Thomas G. Sim ◽  
Graeme T. Swindles ◽  
Paul J. Morris ◽  
Andy J. Baird ◽  
Dan J. Charman ◽  
...  
Keyword(s):  
Water Table ◽  
Transfer Functions ◽  
Testate Amoebae ◽  
Water Table Depth

Testate amoebae as non-pollen palynomorphs in pollen slides: Usefulness and application in palaeoenvironmental reconstruction

2020 ◽  
pp. SP511-2020-34
Author(s):  
L. O. Andrews ◽  
R. J. Payne ◽  
G. T. Swindles
Keyword(s):  
Water Table ◽  
Transfer Functions ◽  
Testate Amoebae ◽  
Water Table Depth ◽  
Qualitative Assessment ◽  
Distribution Data ◽  
Preparation Methods ◽  
Chemical Treatments ◽  
Wide Range ◽  
Qualitative Changes

AbstractTestate amoebae are a frequently used palaeoecological proxy for reconstructing changes in palaeohydrological conditions, particularly in studies of Sphagnum-dominated peatlands. Their use in palaeoecological studies has increased following the development of transfer functions, allowing for the quantitative reconstruction of water-table depth changes through time. Increasingly, they are included in non-pollen palynomorph (NPP) studies alongside a wide range of other proxies, representing a valuable tool, particularly in multi-proxy studies.Testate amoebae have been used for qualitative assessment of palaeohydrology in NPP studies and may aid the verification of environmental interpretations of conditions inferred from curves of NPP with unknown ecology and taxonomy. Their usefulness in such studies is limited by the destruction of tests owing to harsh chemical treatments used in pollen preparation methods. This makes community distribution data of testate amoebae derived by these methods largely unsuitable for quantitative assessment of water-table depth. Furthermore, many palynological studies combine testate amoebae as one single curve, losing further ecological detail. Patterns of change of surviving species, most commonly of Assulina, Archerella, Arcella, Hyalosphenia and Archerella flavum, remain relatively unaffected and therefore can still be useful for interpreting qualitative changes in hydrological conditions through time, particularly when coupled with other proxies.

scholarly journals Testate amoebae as a hydrological proxy for reconstructing water-table depth in the mires of south-eastern Australia

2019 ◽  
Vol 96 ◽  
pp. 701-710 ◽  
Author(s):  
Xianglin Zheng ◽  
Matthew J. Amesbury ◽  
Geoffrey Hope ◽  
Len F. Martin ◽  
Scott D. Mooney
Keyword(s):  
Water Table ◽  
Testate Amoebae ◽  
Water Table Depth ◽  
South Eastern ◽  
Eastern Australia ◽  
South Eastern Australia

Ecohydrological dynamics of a degrading subarctic peatland: Implications for Arsenic mobility

2020 ◽  
Author(s):  
Jennifer Galloway ◽  
Mariusz Gałka ◽  
Graeme Swindles ◽  
Matt Amesbury ◽  
Stephen Wolfe ◽  
...  
Keyword(s):  
Water Table ◽  
Thick Layer ◽  
Plant Macrofossils ◽  
Testate Amoebae ◽  
Water Table Depth ◽  
Permafrost Degradation ◽  
Downward Mobility ◽  
Regional Environment ◽  
Arsenic Mobility ◽  
Trophic Shift

<p>A peatland from subarctic Canada (Handle Lake 62°29’26.44”N, 114°23’18.23”W) is a degrading permafrost peatland chosen for detailed study due to a legacy of regional arsenic (As) contamination as a result of almost 8 decades of gold mining. The fate of permafrost peatlands and their element stores is unknown due to complex feedbacks between peat accumulation, hydrology, and vegetation that affect redox state and element mobility. We combine palynology with study of plant macrofossils, testate amoebae, organic matter composition, and bulk geochemistry preserved in a ca. 4180-4972 cal year old peat monolith retrieved from the Handle Lake peatland to reconstruct the ecohydrological dynamics to assess future trajectories of permafrost peat, and contaminant storage or release, in response to current and future warming. Sphagnum riparium macrofossils are rare in modern peat habitats and sub-fossils are rare in paleoecological records. Plant macrofossils of this taxon occur in an 11-cm thick layer together with Sphagnum angustifolium between 43 cm (ca.  3390-3239 cal BP) and 25 cm depth (ca. 2755-2378 cal BP) in the monolith. The S. riparium sub-fossils are present with the hydrophilous testate amoebae species Archerella flavum, Hyalosphenia papilio and Difflugia globulosa that are used to quantitatively reconstruct a water table depth of 0-4 cm below the peat surface. Sub-fossils of S. riparium disappear at ca. 2755-2378 cal BP, likely due to an autogenic trophic shift and succession towards more acidophilic conditions favourable to species such as Sphagnum fuscum and Sphagnum russowii. We interpret the occurrence of S. riparium as an indicator of wet and minerotrophic conditions linked to peatland development form rich fen to oligotrophic bog.  Because S. riparium is a key pioneer species of disturbed peatlands that have experienced permafrost degradation it will likely be favoured in northern regions experiencing rapid climate warming. In the palynological record the proportion of Sphagnum-type A spores increases (up to 80%) between ca.  3390-3239 cal BP and ca. 2755-2378 cal BP concurrent with a decline in other Sphagnum-type spores. A peak in micro- and macroscopic charcoal occurs between ca. 3557-3286 cal BP and ca. 3275-2771 cal BP, concurrent with a decline in Picea pollen and an increase in Alnus pollen. Regionally, between ca. 3500 and ca. 2500 cal BP Neoglacial climate prevailed with post-Neoglacial warming at ca. 2500 cal BP. It is therefore possible that regional fire occurrence stimulated permafrost degradation at ca. 3500 cal BP. Background As in the active layer monotlith is ~20-30 ppm. The upper 10 cm of the peat are impacted by aerial deposition of As from ore processing and concentrations range up to ~360 ppm. An increase in the concentration of As in the monolith from ~15-20 ppm at the base of the monolith to ~30-40 ppm during this interval may reflect water table depth dynamics that affected the mobility and fate of this redox sensitive element and/or downward mobility from layers impacted by contamination from mineral processing. Degradation of this permafrost within the Handle Lake peatland will release the currently stored As and other contaminants to the regional environment.</p>

scholarly journals Comparing and improving methods for reconstructing peatland water-table depth from testate amoebae

The Holocene ◽  
2019 ◽  
Vol 29 (8) ◽  
pp. 1350-1361
Author(s):  
Connor Nolan ◽  
John Tipton ◽  
Robert K Booth ◽  
Mevin B Hooten ◽  
Stephen T Jackson
Keyword(s):  
Water Table ◽  
Compositional Data ◽  
Testate Amoebae ◽  
Water Table Depth ◽  
Weighted Averaging ◽  
Training Dataset ◽  
Testate Amoeba ◽  
Test Case ◽  
Ecological Communities ◽  
Validation Experiment

Proxies that use changes in the composition of ecological communities to reconstruct temporal changes in an environmental covariate are commonly used in paleoclimatology and paleolimnology. Existing methods, such as weighted averaging and modern analog technique, relate compositional data to the covariate in very simple ways, and different methods are seldom compared systematically. We present a new Bayesian model that better represents the underlying data and the complexity in the relationships between species’ abundances and a paleoenvironmental covariate. Using testate amoeba–based reconstructions of water-table depth as a test case, we systematically compare new and existing models in a cross-validation experiment on a large training dataset from North America. We then apply the different models to a new 7500-year record of testate amoeba assemblages from Caribou Bog in Maine and compare the resulting water-table depth reconstructions. We find that Bayesian models represent an improvement over existing methods in three key ways: more complete use of the underlying compositional data, full and meaningful treatment of uncertainty, and clear paths toward methodological improvements. Furthermore, we highlight how developing and systematically comparing methods lead to an improved understanding of the proxy system. This paper focuses on testate amoebae and water-table depth, but the framework and ideas are widely applicable to other proxies based on compositional data.

scholarly journals Testing peatland water-table depth transfer functions using high-resolution hydrological monitoring data

2015 ◽  
Vol 120 ◽  
pp. 107-117 ◽  
Author(s):  
Graeme T. Swindles ◽  
Joseph Holden ◽  
Cassandra L. Raby ◽  
T. Edward Turner ◽  
Antony Blundell ◽  
...  
Keyword(s):  
High Resolution ◽  
Water Table ◽  
Transfer Functions ◽  
Water Table Depth ◽  
Monitoring Data ◽  
Hydrological Monitoring

scholarly journals Temporal and Local Heterogeneities of Water Table Depth under Different Agricultural Water Management Conditions

Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2148
Author(s):  
Jonathan A. Lafond ◽  
Silvio J. Gumiere ◽  
Virginie Vanlandeghem ◽  
Jacques Gallichand ◽  
Alain N. Rousseau ◽  
...  
Keyword(s):  
Water Management ◽  
Water Table ◽  
Cropping Systems ◽  
Irrigation Management ◽  
Sprinkler Irrigation ◽  
Water Table Depth ◽  
Management Systems ◽  
Integrated Water Management ◽  
Growing Seasons ◽  
Good Drainage

Integrated water management has become a priority for cropping systems where subirrigation is possible. Compared to conventional sprinkler irrigation, the controlling water table can lead to a substantial increase in yield and water use efficiency with less pumping energy requirements. Knowing the spatiotemporal distribution of water table depth (WTD) and soil properties should help perform intelligent, integrated water management. Observation wells were installed in cranberry fields with different water management systems: Bottom, with good drainage and controlled WTD management; Surface, with good drainage and sprinkler irrigation management; Natural, without drainage, or with imperfectly drained and conventional sprinkler irrigation. During the 2017–2020 growing seasons, WTD was monitored on an hourly basis, while precipitation was measured at each site. Multi-frequential periodogram analysis revealed a dominant periodic component of 40 days each year in WTD fluctuations for the Bottom and Surface systems; for the Natural system, periodicity was heterogeneous and ranged from 2 to 6 weeks. Temporal cross correlations with precipitation show that for almost all the sites, there is a 3 to 9 h lag before WTD rises; one exception is a subirrigation site. These results indicate that automatic water table management based on continuously updated knowledge could contribute to integrated water management systems, by using precipitation-based models to predict WTD.

Modelling response of infiltration loss toward water table depth using RBFN, RNN, ANFIS techniques

2021 ◽  
Vol 25 (2) ◽  
pp. 227-234
Author(s):  
Sandeep Samantaray ◽  
Abinash Sahoo
Keyword(s):  
Neural Network ◽  
Mean Square Error ◽  
Water Table ◽  
Environmental Sustainability ◽  
Model Development ◽  
Water Table Depth ◽  
Water Levels ◽  
Coefficient Of Determination ◽  
Mean Square ◽  
Inference System

Accurate prediction of water table depth over long-term in arid agricultural areas are very much important for maintaining environmental sustainability. Because of intricate and diverse hydrogeological features, boundary conditions, and human activities researchers face enormous difficulties for predicting water table depth. A virtual study on forecast of water table depth using various neural networks is employed in this paper. Hybrid neural network approach like Adaptive Neuro Fuzzy Inference System (ANFIS), Recurrent Neural Network (RNN), Radial Basis Function Neural Network (RBFN) is employed here to appraisal water levels as a function of average temperature, precipitation, humidity, evapotranspiration and infiltration loss data. Coefficient of determination (R2), Root mean square error (RMSE), and Mean square error (MSE) are used to evaluate performance of model development. While ANFIS algorithm is used, Gbell function gives best value of performance for model development. Whole outcomes establish that, ANFIS accomplishes finest as related to RNN and RBFN for predicting water table depth in watershed.

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