Cross-site comparisons of state-change dynamics

TitleCross-site comparisons of state-change dynamics
Publication TypeBook Chapter
Year of Publication2013
AuthorsPeters DC, Fraser WR, Kratz T, Ohman MD, Rassweiler A, Holbrook SJ, Schmitt RJ
Book TitleLong-Term Trends in Ecological Systems: A Basis for Understanding Responses to Global Change
Chapter4
Pagination36-41
PublisherNational Technical Information Services
CitySpringfield, Virginia
Accession NumberJRN52664
ARIS Log Number256277
Keywordsatmospheric chemistry, climate change, cross-site comparisons, disturbance, ecological response, ecology, ecosystem, EcoTrends, experimental forests, global change, human demography, human population growth, Long Term Ecological Research (LTER), long-term datasets, precipitation, rangeland, rangeland research stations, surface water chemistry
Abstract

Changes in the state of a system, for example from grasslands to shrublands or from dominance by one fish species to another species, with associated changes in other parts of the system, are often irreversible. Most of these state changes bring forth negative impacts on ecosystem, resulting in altered levels of biodiversity, rates of nutrient cycling, changes in air and water quality, and increased losses of soil and nutrients by wind and water erosion.  This chapter illustrated six examples of state changes in various types of ecosystems: vegetation state changes in deserts, penguin dynamics in Antarctica, fish dynamics in Wisconsin lakes, plankton dynamics in the Pacific Ocean, subtidal dynamics off Pacific Coast, and shifts in coastal fish assemblages in the Pacific Ocean.  These examples clearly show the impact of global environmental change (warming, invasive species, altered trophic structure) on the abundance and distribution of dominant and subordinate species in aquatic, marine, and terrestrial systems. Because this era of rapid environmental change is only beginning to be manifest in species responses, long-term data will continue to be needed to quantify and predict the non-linear system responses that are likely to occur in the future.

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