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The eddy covariance (EC) method was used in a 30-month study to quantify evapotranspiration (ET) and vegetation coefficient (K CW ) for a wetland on a ranch in subtropical south Florida. To evaluate the errors in ET estimates, the EC-based ET (ET C-EC ) and the Food and Agricultural Organization (FAO) Penman-Monteith (PM) based ET (ET C-PM ) estimates (with literature crop coefficient, K C ) were compared with each other. The ET C-EC and FAO-PM reference ET were used to develop K CW . Regression models were developed to estimate K CW using climatic and hydrologic variables. Annual and daily ET C-EC values were 1152 and 3.27 mm, respectively. The FAO-PM model underestimated ET by 25% with ET C-EC being statistically higher than ET C-PM . The K CW varied from 0.79 (December) to 1.06 (November). The mean K CW for the dry (November-April) season (0.95) was much higher than values reported for wetlands in literature; whereas for the wet (May-October) season, K CW (0.97) was closer to literature values. Higher than expected K CW values during the dry season were due to higher temperature, lower humidity and perennial wetland vegetation. Regression analyses showed that factors affecting the K CW were different during the dry (soil moisture, temperature and relative humidity) and wet (net radiation, inundation and wind speed) seasons. Separate regression models for the dry and wet seasons were developed. Evapotranspiration and K CW from this study, one of the first for the agricultural wetlands in subtropical environment, will help improve the ET estimates for similar wetlands. Figure 3. (a) Monthly total precipitation (mm); and monthly average of climatic variables: (b) incoming solar radiation (W/m 2 ), (c) vapour pressure deficit (kPa), (d) temperature (°C), (e) relative humidity (%) and (f) wind speed (2 m height, m/s) during the study period (Figure 10. Comparisons: (a) the trends of weekly average EC-based ET and PM-based ET for the study period and (b) weekly average EC-based ET and PM-based ET, and the solid line is 1 : 1 5891 ET FOR AN AGRICULTURAL WETLAND

No abstract

While ecotoxicology has long recognised the importance of identifying levels at which contaminants pose threats to biota, most estimates of species responses to toxicants are derived from controlled laboratory studies and may hold limited relevance to natural systems. However, designing appropriate field‐based studies investigating contaminant induced changes in assemblages has been challenging, partially due to the difficulty in identifying comparable uncontaminated reference sites. The aim of this study is to characterise the effects of heavy metal contamination on natural fish assemblages using an ecologically relevant catchment‐scale design. We hypothesise that environmental variables, including discharge, sediment, and landscape variables, can be used to characterise differences in fish species richness and abundances between sites contaminated with heavy metals and uncontaminated reference sites. We apply a geographic information systems approach that uses assemblage–environment relationships developed using hydrologic model outputs, land cover, and topographic data from uncontaminated reference sites to predict expected fish species richness and abundance at sites contaminated with heavy‐metals within the Big River catchment in south‐eastern Missouri, U.S.A. These predicted levels of richness and abundance are then compared to observed assemblages at contaminated sites to estimate the potential impacts of historical lead mining activities on freshwater taxa. We developed models that characterised variation in Centrarchidae (bass and sunfish) richness and abundance, Cyprinidae (minnows) abundance, and Percidae (darters) richness using variables including streamflow regime, suspended sediment concentration, and land cover at uncontaminated sites. Using these relationships, we predicted expected fish species richness and abundance at heavy metal contaminated sites across the Big River catchment and found a significant reduction in centrarchid abundance from field‐collected data compared to predicted estimates. Our results suggest that centrarchids, which tend to occupy a higher trophic level than cyprinids and percids, have lower abundances at sites contaminated with heavy metals than predicted by assemblage–environment relationships. These decreases in abundance are not associated with decreases in centrarchid species richness, cyprinid abundance, or percid richness. This geographic information systems‐based approach provides a useful and ecologically relevant framework for understanding the response of taxa to the presence of contaminants without assuming habitat equivalence across sites. Our findings also suggest the need for further research regarding how heavy metals impact fishes of varying trophic levels in natural settings.