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      Perenniality drives multifunctional forage–biomass filter strips’ ability to improve water quality

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          Abstract

          Vegetative filter strip characteristics such as perenniality drive hydrology and subsequent ecosystem services. However, the extent and the potential for forage–biomass crops to improve water quality, provide fodder, and optimize nutrient cycling in multifunctional systems is unknown. We evaluated (a) how species, perenniality, and plant community composition are linked to water quality; and (b) the multiuse forage–biomass potential of filter strips. Whole plots were species [eastern gamagrass ( Tripsacum dactyloides), Kernza [or intermediate wheatgrass ( Thinopyrum intermedium)], silphium ( Silphium integrifolium), switchgrass ( Panicum virgatum), and winter wheat ( Triticum aestivum)], with split‐plots receiving 0 or 5.6 Mg ha −1 broiler litter. Rainfall simulations were conducted at 5 cm h −1 (until 30 min of continuous runoff) in summer and fall of 2019 and 2021 with dual forage and biomass harvests occurring 2019–2021. Kernza and silphium had the lowest biomass regrowth after forage harvests relative to native grasses, suggesting they would not be ideal multifunctional forage–bioenergy crops. Among all soil–plant–water variables, canonical correlations indicate poultry litter (.97), and soil phosphorus saturation (.77) were the most influential variables for water quality. Water quality score, F WQ, which is inversely related to runoff water quality, was lowest for switchgrass (0.03) and greatest ( P ≥ .05) for eastern gamagrass and wheat (1.77 and 3.33, respectively), but not different from Kernza (0.98) and silphium (0.31). Therefore, switchgrass resulted in the best water quality scores and highest forage–biomass yields, with Kernza and silphium also showing promise for reducing sediment and nutrient loads following poultry litter applications in multifunctional filter strip systems.

          Core Ideas

          • Filter strip characteristics drive surface hydrology and subsequent ecosystem services.

          • Greatest multiuse (forage–biomass filter strip) yields occurred for switchgrass.

          • Poultry litter applications and soil P saturation were most correlated with water quality.

          • Perennial crops (excluding eastern gamagrass) improved water quality.

          • Switchgrass had the highest water quality and biomass yields, indicating greatest multiuse filter strip potential.

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              Conducting and interpreting canonical correlation analysis in personality research: a user-friendly primer.

              The purpose of this article is to reduce potential statistical barriers and open doors to canonical correlation analysis (CCA) for applied behavioral scientists and personality researchers. CCA was selected for discussion, as it represents the highest level of the general linear model (GLM) and can be rather easily conceptualized as a method closely linked with the more widely understood Pearson r correlation coefficient. An understanding of CCA can lead to a more global appreciation of other univariate and multivariate methods in the GLM. We attempt to demonstrate CCA with basic language, using technical terminology only when necessary for understanding and use of the method. We present an entire example of a CCA analysis using SPSS (Version 11.0) with personality data.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Crop Science
                Crop Science
                Wiley
                0011-183X
                1435-0653
                January 2023
                December 19 2022
                January 2023
                : 63
                : 1
                : 336-348
                Affiliations
                [1 ] USDA‐ARS, Poultry Production and Product Safety Research Unit Fayetteville AR 72701 USA
                [2 ] Dep. of Poultry Science Univ. of Arkansas Fayetteville AR 72701 USA
                [3 ] USDA‐ARS, Dale Bumpers Small Farms Research Center Booneville AR 72927 USA
                Article
                10.1002/csc2.20878
                2e41b753-0f5c-4e09-9192-83067555760a
                © 2023

                http://creativecommons.org/licenses/by-nc-nd/4.0/

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