A. Prestigiacomo, S. June, R. Gorney, A. J. Smith, A. Clinkhammer
{"title":"用于监测纽约州湖泊叶绿素a的光谱荧光计的评估","authors":"A. Prestigiacomo, S. June, R. Gorney, A. J. Smith, A. Clinkhammer","doi":"10.1080/10402381.2022.2129525","DOIUrl":null,"url":null,"abstract":"Abstract Prestigiacomo AR, June SG, Gorney RM, Smith AJ, Clinkhammer AC. 2022. An evaluation of a spectral fluorometer for monitoring chlorophyll a in New York State lakes. Lake Reserv Manage. 38:318–333. The quantification of chlorophyll a in surface waters through sampling and laboratory extraction methods has limitations, including the lack of phytoplankton composition analysis and delayed analysis time. Recently, automated instruments have been developed to quickly provide estimation of total chlorophyll a and characterize phytoplankton composition into functional groups. Here, we analyzed a dataset of paired, laboratory-extracted chlorophyll a samples (Chl-a) and chlorophyll a estimated from a spectrofluorometer (FluoroProbe, bbe Moldaenke; FPChl-a) for comparability at several time scales. We found that FPChl-a was highly correlated to Chl-a (r > 0.8) but overestimated Chl-a by 1.5–2 times on average. Summer average FPChl-a was higher than summer average Chl-a, resulting in incorrect lake evaluations against selected thresholds. Linear least squares regression of Chl-a/FPChl-a was highly significant (P < 0.01) and demonstrated a good fit (r2 > 0.75) but had high variability, consistent with FPChl-a performance values reported in the scientific literature. Factors such as FPChl-a magnitude and algal dominance were statistically important factors affecting the Chl-a/FPChl-a relationship. We developed a multiple linear regression method for postcalibrating FPChl-a to equivalent Chl-a values (adjusted FPChl-a) and applied it to the FPChl-a dataset. Adjusted FPChl-a values were unbiased and compared well with Chl-a (mean residual equal to 0 µg/L). Adjusted FPChl-a summer averages resulted in correct waterbody evaluation in more than 90% of lakes. We propose that the FluoroProbe, properly postcalibrated to adjusted FPChl-a, can be used as a surrogate of Chl-a in open water monitoring applications, reducing the need for traditional laboratory Chl-a samples for lake monitoring and management.","PeriodicalId":18017,"journal":{"name":"Lake and Reservoir Management","volume":"38 1","pages":"318 - 333"},"PeriodicalIF":1.1000,"publicationDate":"2022-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An evaluation of a spectral fluorometer for monitoring chlorophyll a in New York State lakes\",\"authors\":\"A. Prestigiacomo, S. June, R. Gorney, A. J. Smith, A. Clinkhammer\",\"doi\":\"10.1080/10402381.2022.2129525\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Prestigiacomo AR, June SG, Gorney RM, Smith AJ, Clinkhammer AC. 2022. An evaluation of a spectral fluorometer for monitoring chlorophyll a in New York State lakes. Lake Reserv Manage. 38:318–333. The quantification of chlorophyll a in surface waters through sampling and laboratory extraction methods has limitations, including the lack of phytoplankton composition analysis and delayed analysis time. Recently, automated instruments have been developed to quickly provide estimation of total chlorophyll a and characterize phytoplankton composition into functional groups. Here, we analyzed a dataset of paired, laboratory-extracted chlorophyll a samples (Chl-a) and chlorophyll a estimated from a spectrofluorometer (FluoroProbe, bbe Moldaenke; FPChl-a) for comparability at several time scales. We found that FPChl-a was highly correlated to Chl-a (r > 0.8) but overestimated Chl-a by 1.5–2 times on average. Summer average FPChl-a was higher than summer average Chl-a, resulting in incorrect lake evaluations against selected thresholds. Linear least squares regression of Chl-a/FPChl-a was highly significant (P < 0.01) and demonstrated a good fit (r2 > 0.75) but had high variability, consistent with FPChl-a performance values reported in the scientific literature. Factors such as FPChl-a magnitude and algal dominance were statistically important factors affecting the Chl-a/FPChl-a relationship. We developed a multiple linear regression method for postcalibrating FPChl-a to equivalent Chl-a values (adjusted FPChl-a) and applied it to the FPChl-a dataset. Adjusted FPChl-a values were unbiased and compared well with Chl-a (mean residual equal to 0 µg/L). Adjusted FPChl-a summer averages resulted in correct waterbody evaluation in more than 90% of lakes. 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An evaluation of a spectral fluorometer for monitoring chlorophyll a in New York State lakes
Abstract Prestigiacomo AR, June SG, Gorney RM, Smith AJ, Clinkhammer AC. 2022. An evaluation of a spectral fluorometer for monitoring chlorophyll a in New York State lakes. Lake Reserv Manage. 38:318–333. The quantification of chlorophyll a in surface waters through sampling and laboratory extraction methods has limitations, including the lack of phytoplankton composition analysis and delayed analysis time. Recently, automated instruments have been developed to quickly provide estimation of total chlorophyll a and characterize phytoplankton composition into functional groups. Here, we analyzed a dataset of paired, laboratory-extracted chlorophyll a samples (Chl-a) and chlorophyll a estimated from a spectrofluorometer (FluoroProbe, bbe Moldaenke; FPChl-a) for comparability at several time scales. We found that FPChl-a was highly correlated to Chl-a (r > 0.8) but overestimated Chl-a by 1.5–2 times on average. Summer average FPChl-a was higher than summer average Chl-a, resulting in incorrect lake evaluations against selected thresholds. Linear least squares regression of Chl-a/FPChl-a was highly significant (P < 0.01) and demonstrated a good fit (r2 > 0.75) but had high variability, consistent with FPChl-a performance values reported in the scientific literature. Factors such as FPChl-a magnitude and algal dominance were statistically important factors affecting the Chl-a/FPChl-a relationship. We developed a multiple linear regression method for postcalibrating FPChl-a to equivalent Chl-a values (adjusted FPChl-a) and applied it to the FPChl-a dataset. Adjusted FPChl-a values were unbiased and compared well with Chl-a (mean residual equal to 0 µg/L). Adjusted FPChl-a summer averages resulted in correct waterbody evaluation in more than 90% of lakes. We propose that the FluoroProbe, properly postcalibrated to adjusted FPChl-a, can be used as a surrogate of Chl-a in open water monitoring applications, reducing the need for traditional laboratory Chl-a samples for lake monitoring and management.
期刊介绍:
Lake and Reservoir Management (LRM) publishes original, previously unpublished studies relevant to lake and reservoir management. Papers address the management of lakes and reservoirs, their watersheds and tributaries, along with the limnology and ecology needed for sound management of these systems. Case studies that advance the science of lake management or confirm important management concepts are appropriate as long as there is clearly described management significance. Papers on economic, social, regulatory and policy aspects of lake management are also welcome with appropriate supporting data and management implications. Literature syntheses and papers developing a conceptual foundation of lake and watershed ecology will be considered for publication, but there needs to be clear emphasis on management implications. Modeling papers will be considered where the model is properly verified but it is also highly preferable that management based on the model has been taken and results have been documented. Application of known models to yet another system without a clear advance in resultant management are unlikely to be accepted. Shorter notes that convey important early results of long-term studies or provide data relating to causative agents or management approaches that warrant further study are acceptable even if the story is not yet complete. All submissions are subject to peer review to assure relevance and reliability for management application.