Geology topics

Robert A. Shuchman

Publications and source records attributed to Robert A. Shuchman.

4 recordsLinked to original sources

USGS2018

Assessing the influence of watershed characteristics on chlorophyll a in waterbodies at global and regional scales

Prediction of primary production of lentic water bodies (i.e., lakes and reservoirs) is valuable to researchers and resource managers alike, but is very rarely done at the global scale. With the development of remote sensing technologies, it is now feasible to gather large amounts of data across the world, including understudied and remote regions. To determine which factors were most important in explaining the variation of chlorophyll a (Chl- a ), an indicator of primary production in water bodies, at global and regional scales, we first developed a geospatial database of 227 water bodies and watersheds with corresponding Chl- a , nutrient, hydrogeomorphic, and climate data. Then we used a generalized additive modeling approach and developed model selection criteria to select models that most parsimoniously related Chl- a to predictor variables for all 227 water bodies and for 51 lakes in the Laurentian Great Lakes region in the data set. Our best global model contained two hydrogeomorphic variables (water body surface area and the ratio of watershed to water body surface area) and a climate variable (average temperature in the warmest model selection criteria to select models that most parsimoniously related Chl- a to predictor variables quarter) and explained ~ 30% of variation in Chl- a . Our regional model contained one hydrogeomorphic variable (flow accumulation) and the same climate variable, but explained substantially more variation (58%). Our results indicate that a regional approach to watershed modeling may be more informative to predicting Chl- a , and that nearly a third of global variability in Chl- a may be explained using hydrogeomorphic and climate variables.

Inland Waters↗

USGS2017

The contribution of lakes to global inland fisheries harvest

Freshwater ecosystems provide numerous services for communities worldwide, including irrigation, hydropower, and municipal water; however, the services provided by inland fisheries – nourishment, employment, and recreational opportunities – are often comparatively undervalued. We provide an independent estimate of global lake harvest to improve biological and socioeconomic assessments of inland fisheries. On the basis of satellite-derived estimates of chlorophyll concentration from 80,012 globally distributed lakes, lake-specific fishing effort based on human population, and output from a Bayesian hierarchical model, we estimated that the global lake fishery harvest in the year 2011 was 8.4 million tons (mt). Our calculations excluded harvests from highly productive rivers, wetlands, and very small lakes; therefore, the true cumulative global fishery harvest from all freshwater sources likely exceeded 11 mt as reported by the Food and Agriculture Organization of the United Nations (FAO). This putative underestimate by the FAO could diminish the perceived importance of inland fisheries and perpetuate decisions that adversely affect these fisheries and millions of people.

Frontiers in Ecology and the Environment↗

USGS2016

Identification of lake trout Salvelinus namaycush spawning habitat in northern Lake Huron using high-resolution satellite imagery

The availability and quality of spawning habitat may limit lake trout recovery in the Great Lakes, but little is known about the location and characteristics of current spawning habitats. Current methods used to identify lake trout spawning locations are time- and labor-intensive and spatially limited. Due to the observation that some lake trout spawning sites are relatively clean of overlaying algae compared to areas not used for spawning, we suspected that spawning sites could be identified using satellite imagery. Satellite imagery collected just before and after the spawning season in 2013 was used to assess whether lake trout spawning habitat could be identified based on its spectral characteristics. Results indicated that Pléiades high-resolution multispectral satellite imagery can be successfully used to estimate algal coverage of substrates and temporal changes in algal coverage, and that models developed from processed imagery can be used to identify potential lake trout spawning sites based on comparison of sites where lake trout eggs were and were not observed after spawning. Satellite imagery is a potential new tool for identifying lake trout spawning habitat at large scales in shallow nearshore areas of the Great Lakes.

Lake Huron↗

USGS2015

A new method to generate a high-resolution global distribution map of lake chlorophyll

A new method was developed, evaluated, and applied to generate a global dataset of growing-season chlorophyll- a (chl) concentrations in 2011 for freshwater lakes. Chl observations from freshwater lakes are valuable for estimating lake productivity as well as assessing the role that these lakes play in carbon budgets. The standard 4 km NASA OceanColor L3 chlorophyll concentration products generated from MODIS and MERIS sensor data are not sufficiently representative of global chl values because these can only resolve larger lakes, which generally have lower chl concentrations than lakes of smaller surface area. Our new methodology utilizes the 300 m-resolution MERIS full-resolution full-swath (FRS) global dataset as input and does not rely on the land mask used to generate standard NASA products, which masks many lakes that are otherwise resolvable in MERIS imagery. The new method produced chl concentration values for 78,938 and 1,074 lakes in the northern and southern hemispheres, respectively. The mean chl for lakes visible in the MERIS composite was 19.2 ± 19.2, the median was 13.3, and the interquartile range was 3.90–28.6 mg m −3 . The accuracy of the MERIS-derived values was assessed by comparison with temporally near-coincident and globally distributed in situ measurements from the literature ( n = 185, RMSE = 9.39, R 2 = 0.72). This represents the first global-scale dataset of satellite-derived chl estimates for medium to large lakes.

International Journal of Remote Sensing↗