Microfauna Within Biological Soil Crusts

  • Brian J. DarbyEmail author
  • Deborah A. Neher
Part of the Ecological Studies book series (ECOLSTUD, volume 226)


Biocrusts serve as unique habitat for a broad range of microfauna, including protozoa, nematodes, tardigrades, rotifers, mites, collembolans, and even larger arthropods and mollusks. These microfauna feed on the bacteria, cyanobacteria, algae, fungi, bryophytes, and plant roots that are found in the biocrusts, and the consumer food web as a whole performs several important functions, such as cycling nutrients, dispersing propagules, and moderating their microbial prey populations. Many species of biocrust microfauna tolerate periods of drought in an anhydrobiotic dormant state, so they are typically active only during brief windows of time. Most microfaunal groups tend to be more abundant, species rich, and diverse in mature, late-successional stage biocrusts that are dominated by diverse microflora (such as lichens, mosses, fungi, and cyanobacteria) than in early successional stage biocrusts that are dominated by less diverse microflora (such as cyanobacteria alone). Biocrust microfauna are susceptible to the same surface disturbances that affect biocrust microflora, such as physical trampling or altered temperature and summer precipitation, but the specific ecosystem consequences of altered community composition due to surface disturbances are still largely unknown. To fully understand the ecosystem consequences of biocrust microfauna, we propose that the three main research needs in the future are to: (1) identify specific feeding behaviors of individual species, (2) increase the taxonomic resolution of ecological studies to the level of species, and (3) identify the ecologically relevant genetic and genomic aspects of microfaunal adaptations to the biocrust habitat.


Nematode Community Biological Soil Crust Filamentous Cyanobacterium Taxonomic Resolution Surface Disturbance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.University of North DakotaGrand ForksUSA
  2. 2.Department of Plant and Soil ScienceUniversity of VermontBurlingtonUSA

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