Search for: All records

Increases in the concentration of dissolved organic matter (DOM) have been documented in many inland waters in recent decades, a process known as “browning”. Previous studies have often used space‐for‐time substitution to examine the direct consequences of increased DOM on lake ecosystems. However, browning often occurs concomitant with other ecologically important water chemistry changes that may interact with or overwhelm any potential ecological response to browning itself. Here we examine a long‐term (~20 year) dataset of 28 lakes in the Adirondack Park, New York, USA, that have undergone strong browning in response to recovery from acidification. With these data, we explored how primary producer and zooplankton consumer populations changed during this time and what physical and chemical changes best predicted these long‐term ecosystem changes. Our results indicate that changes in primary producers are likely driven by reduced water clarity due to browning, independent of changes in nutrients, counter to previously hypothesized primary producer response to browning. In contrast, declines in calcium concomitant with browning play an important role in driving long‐term declines in zooplankton biomass. Our results indicate that responses to browning at different trophic levels are decoupled from one another. Concomitant chemical changes have important implications for our understanding of the response of aquatic ecosystems to browning.

 

The attenuation of solar radiation controls many processes and characteristics of aquatic ecosystems and is a sentinel of larger‐scale environmental change. While light attenuation is often characterized with a single broadband diffuse attenuation coefficient of photosynthetically active radiation (K_dPAR), attenuation can exhibit substantial variability across the solar spectrum and through time and space. Understanding this variability and its proximate causes may provide information to characterize large‐scale environmental change. We implemented a semi‐analyticalK_dmodel in four segments of the Rhode River sub‐estuary of the Chesapeake Bay to examine spectral, spatial, and temporal variability inK_dacross the ultraviolet (UV) to PAR wavelengths (290–710 nm) over the period 1986–2014. We used this model to identify wavelengths most sensitive to long‐term change, the seasonal phenology of long‐term change, and the optical constituents driving changes. The model included contributions by phytoplankton,non‐algal particulates,chromophoric dissolved organic matter (CDOM), and water. Over the period of record,K_dincreased (water transparency decreased) in both UV and PAR wavelengths, with the largest increases at the most upstream site, during summer months, and at short UV wavelengths. These increases were due primarily to an increase in non‐algal particulates, and particularly since year 2005, however there was substantial seasonality inK_d. The model reveals how different changes in water quality have a differential effect on UV and PAR attenuation, and enables insight into what types of long‐term change in transparency have occurred over the long period of human impacts in the Chesapeake Bay watershed.

 

Addressing continental scale challenges affecting inland aquatic systems requires data at comparable scales. Critically, local in-situ observations for both lotic and lentic ecosystems are frequently fragmented across federal, state and local agencies, and nonprofit or academic organizations and must be linked to other geospatial data to be useful. To advance macro-scale aquatic ecosystem science, better tools are needed to facilitate dataset integration. Key to integration of aquatic data is the linking of spatial data to the hydrologic network. This integration step is challenging as hydrologic network data are large and cumbersome to manage. Here we develop a new R package, hydrolinks, to ease linking aquatic data to the hydrologic network. We use hydrolinks to evaluate the spatial data quality for all lake and stream sites available through the U.S. Water Quality Portal. We find that 76.5% of lake sites and 13.9% of stream sites do not correspond with mapped waterbodies.