E&S Environmental Chemistry collaborated with scientists from the U.S. Geological Survey and U.S. Forest Service to assess the effects of acidic deposition on the current growth, health, and regeneration of sugar maple trees, and to determine the extent to which sugar maple response is associated with soil conditions in small upland watersheds within the Oswegatchie and Black river basins of the southwestern Adirondack Mountains in New York. Specific objectives are to 1) assess the visible health of dominant and codominant sugar maple trees through systematic evaluation of canopy condition, 2) analyze historical growth trends through dendrochronology, 3) assess regeneration as reflected in seedling and sapling density, 4) assess soil chemistry, 5) determine relationships among sugar maple health, soil chemistry, and stream chemistry, 6) evaluate the extent to which poor soil base cation status and/or vegetative health can be inferred from existing streamwater chemistry data in low-order stream watersheds, and 7) develop an integrated ecosystem assessment of soil, stream water, and sugar maple condition that can be applied to the regional population of 565 southwestern Adirondack watersheds. We found essentially zero sugar maple regeneration at sites that had soil BS < 12%. Follow-on research, together with State University of New York at Syracuse, is investigating effects of soil acidification on understory plant biodiversity on these plots.
This project represents a critical step in the assessment of chemical and biological acidification impacts and recovery responses of Adirondack terrestrial resources in response to changing levels of acidic deposition. The timing of past sugar maple growth declines in the western Adirondack Mountains is determined relative to known trends in atmospheric sulfur deposition. The relationships between chemical indicators of soil acid-base chemistry (e.g., base saturation, exchangeable calcium and magnesium) and biological indicators of acidification effect on sugar maple (e.g., growth, health, regeneration) are quantified for use in critical loads modeling.