Modern influences on chironomid distribution in western Ireland: potential for palaeoenvironmental reconstruction

Abstract

Ireland provides a unique setting for the study of past climates, as its climate is dominated by westerly airflow from the North Atlantic and readily responsive to changes in North Atlantic circulation patterns. Although there has been substantial research on Ireland's past environments, quantitative palaeolimnological research, especially chironomid-based research, has been lacking. In order to further develop chironomid-based palaeolimnological investigations, a calibration set was constructed to determine the dominant environmental controls on modern chironomids in western Ireland. Chironomid subfossils were collected from surface sediments of 50 lakes. The lakes were characterised with 36 environmental variables, including physical attributes, lake water characteristics, lake sediment characteristics and land cover within each catchment. In this exploratory study, no specific environmental variable was targeted and lakes were chosen to span gradients of latitude, elevation, depth and trophic status. Redundancy analysis showed that six environmental variablesmean July air temperature, lake depth, dissolved organic carbon, and percentage catchment land cover of agriculture, peat bog and scrubland-captured a large and statistically significant portion of the variance in the chironomid data. July temperature and agricultural land cover were the most dominant environmental variables, with July temperature proving the most suitable for inference model development. A classical weighted-averaging model was developed to estimate July air temperature, with a coefficient of determination (r jack 2 ) of 0.60 and root mean square error of prediction (RMSEP) of 0.57°C. Results suggest that summer temperature is the dominant influence on chironomid distribution across a wide variety of lake types, and the relatively small RMSEP should allow for more accurate reconstructions of Ireland's relatively subdued Holocene temperature fluctuations.

A chironomid-based mean July temperature inference model from the south-east margin of the Tibetan Plateau, China

“…The training set has a MJT gradient of 16.6 • C and the RMSEP represents 13.8 % of the scalar length of the MJT gradient. This is comparable with most chironomid-based transfer function models including those developed from northern Sweden with 100 lakes (r 2 = 0.65, Larocque et al, 2001), western Ireland with 50 lakes (r 2 = 0.60, Potito et al, 2014) and Finland with 77 lakes (r 2 = 0.78, Luoto, 2009) representing 14.7, 15 and 12.5 % of the scalar length of the temperature gradient, respectively, but less robust than the combined 274-lake transfer function developed from Europe (r 2 = 0.84, RMSEP representing 10.4 % of the scalar length of the MJT gradient) (Heiri et al, 2011). Despite of the relatively lower model coefficient (r boot = 0.63), we observe that by having a large number of lakes in the calibration set, the distribution of the sites along the MJT gradient is relatively even (Fig.…”

Development and application of subfossil chironomid-based methods for late Quaternary climate reconstructions in eastern Australia

“…of the scalar length and this is comparable with most other transfer functions (e.g. Potito et al, 2014). It has been observed that data sets with large temperature gradients naturally have larger errors but this in no way diminishes the value of the reconstruction.…”

Assessing recent climatic and human influences on chironomid communities from two moderately impacted lakes in western Ireland

“…For the last 6000 years, human settlement and active farming has been a prominent feature on the Irish landscape and, as a result, lakes on the island are rarely isolated from such impacts. In order to confidently reconstruct Irish temperatures through the Holocene, it must first be determined if Irish-based temperature inference models (Potito et al, 2014) can adequately reconstruct temperature at sites with low to moderate human influences.…”

“…Even removed from prehistoric settlement, reconstructions of relatively modest Holocene temperature change in this maritime region would prove difficult using extra-regional training sets with large temperature ranges and relatively large associated error ranges. A recent chironomid-based inference model developed from 50 lakes in western Ireland (r 2 jack = 0.60, RMSEP = 0.57°C, maximum bias = 0.63°C) may help to overcome these past difficulties in Holocene temperature reconstruction (Potito et al, 2014). The relatively small temperature range in the training set, and the accompanying small RMSEP, lends the inference model greater applicability for reconstructing Ireland's subdued Holocene temperature fluctuations (Potito et al, 2014).…”

“…A recent chironomid-based inference model developed from 50 lakes in western Ireland (r 2 jack = 0.60, RMSEP = 0.57°C, maximum bias = 0.63°C) may help to overcome these past difficulties in Holocene temperature reconstruction (Potito et al, 2014). The relatively small temperature range in the training set, and the accompanying small RMSEP, lends the inference model greater applicability for reconstructing Ireland's subdued Holocene temperature fluctuations (Potito et al, 2014). Furthermore, the inclusion of lakes with low to moderate agricultural impacts makes this training set more applicable to reconstructing mid to late Holocene Irish environments.…”