In the cold semiarid Canadian prairies, groundwater recharge is focussed under numerous topographic depressions, in which snowmelt runoff converges. Agricultural land uses on the uplands surrounding the depressions affect snow accumulation, snowmelt infiltration, evapotranspiration (ET) and soil moisture dynamics, thereby influencing snowmelt runoff and depression-focussed recharge. The objective of this study is to compare the differences in hydrological processes under two common land uses in the Canadian prairies, namely grazed grass and annual crop, and examine how they affect groundwater recharge. A short-term (3 years) paired catchment study was used for detailed observation of hydrological processes in two depressions, supplemented by a longer-term (17 years) data set covering a larger scale to quantify the differences in snowmelt runoff between the two land uses. Compared to the grazed grassland, the cropland had a shorter and more intense period of ET, and root water uptake restricted to the shallower (top 0-80 cm) soil zone. The amount of snowmelt runoff was greater in the grazed grassland primarily due to a higher amount of snow accumulation, which was dictated by differences in topography. This finding was contrary to previous studies in the Canadian prairies that indicated substantially smaller snowmelt runoff in ungrazed grassland, but was consistent with the larger-scale remote sensing results, which showed only a marginal difference between grazed grasslands and croplands. Groundwater recharge rates were estimated using the chloride mass balance method for the present condition using "modern" pore water containing tritium. The rates were similar between the grazed grassland and croplands, implying similarity in snowmelt runoff characteristics.These results suggest that groundwater recharge will continue to be focussed under depressions in the future, though the amount and seasonality of recharge may be influenced by warmer winters.
The ability to measure and monitor wildlife populations is important for species management and conservation. The use of near-infrared spectroscopy (NIRS) to rapidly detect physiological traits from wildlife scat and other body materials could play an important role in the conservation of species. Previous research has demonstrated the potential for NIRS to detect diseases such as the novel COVID-19 from saliva, parasites from feces, and numerous other traits from animal skin, hair, and scat, such as cortisol metabolites, diet quality, sex, and reproductive status, that may be useful for population monitoring. Models developed from NIRS data use light reflected from a sample to relate the variation in the sample’s spectra to variation in a trait, which can then be used to predict that trait in unknown samples based on their spectra. The modelling process involves calibration, validation, and evaluation. Data sampling, pre-treatments, and the selection of training and testing datasets can impact model performance. We review the use of NIRS for measuring physiological traits in animals that may be useful for wildlife management and conservation and suggest future research to advance the application of NIRS for this purpose.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.