Sørensen LI, Holmstrup M, Maraldo K, Christensen S, Christensen B. 2006. Soil fauna communities and microbial respiration in high Arctic tundra soils at Zackenberg, Northeast Greenland. Polar Biology 29: 189-195.
These authors sampled soil animals from three sites at Zackenberg station, Greenland, over three days in mid-summer. Two of the sites were considered mesic heath, with a mix of Cassiope tetragona and other High Arctic species of plants, while the third site was dominated by Dryas spp. and was considered dry heath; snow melts from the dry heath up to 20 days earlier than from the mesic heaths. Soil samples ranging down to about 6cm depth were collected, stored at 5ºC for up to two weeks, and analyzed by a range of methods in the laboratories in Europe.
Different groups of soil animals were extracted by varying methods. Soil microarthropods, a diverse group dominated by Collebola and Acari, were extracted by modified MacFadyen funnels into Benzoic acid. Enchytraeids and dipteran larvae were extracted in Baermann wet funnels with heating of the samples, into tap water. Protozoa were washed from soils in water and grown on media plates in the dark at 10ºC. Nematodes were collected by the Blender-Cotton wool method of Schouten and Arp (1991). Soil microbial respiration was measured in serum bottles, with the CO2 concentration in the headspace measured at zero, 5 and 25 hours, with a fully factorial design of nutrient amendments of C, N, and P. Soil pH and soil organic matter content, but not moisture content or other nutrient concentrations were determined using methods not clearly described, though presumably these procedures were similar to standard methods.
Once abundance and biomass data was collected, comparisons between plots were made using multivariate analysis and a software package named PRIMER 5.0. My understanding is the species counts were (log+1) transformed to reduce the influence of very abundant species, then analyzed using an approach similar to Principal Components Analysis. The result of this analysis was a clear difference between the dry heath and the two mesic heaths, while the two mesic heaths were not different from each other in parameter-space. A Bray-Curtis similarity matrix was also involved, though I’m not certain I understand how.
Different taxonomic groups were identified to different taxonomic levels; 19 species of Collembola and 7 species of Enchytraeids were found, for example, but Acari were identified to suborder (Cryptostigmata (oribatids), Prostigmata, Mesostigmata) and nematodes and protozoans were counted at those high taxonomic levels. While the two mesic heath sites were only marginally significantly different from each other, there was a clear increase in abundances in the dry heath site. For collembola at least, the dry heath site was also dominated by two highly abundant species, which differed from the majority of species in the mesic sites by being unpigmented and associated with sub-surface, rather than soil-surface, regions in the soil. The higher abundance of probably bacteria-eating nematodes at the dry heath strongly suggests higher turnover of microorganisms as well as generally higher biological activity from the higher populations of most soil animals.
These authors suggest higher organic matter decomposition rates at the dry heath, which seems reasonable given the higher animal populations there. However, their attribution of higher soil pH there to higher respiration levels seems like more of a stretch, absent supporting mineralogical and soil-nutrient data.
This paper provides an excellent example of the data that can be collected and analyzed from a brief but intensive study of soil invertebrates at a High Arctic site. In addition, meaningful information about differences in biodiversity between locations can be derived from studies of organisms not identified to fine taxonomic levels.
Showing posts with label Zoology. Show all posts
Showing posts with label Zoology. Show all posts
Wednesday, March 31, 2010
O'Neill et al. 2010
O’Neill KP, Godwin HW, Jiménez-Esquilín AE, Battigelli JP. 2010. Reducing the dimensionality of soil microinvertebrate community datasets using Indicator Species Analysis: Implications for ecosystem monitoring and soil management. Soil Biology & Biochemistry 42: 145-154.
These authors used a dataset of soil microarthropods to evaluate a method for identifying indicator species for ecosystem monitoring. The method centres on the Indicator Value (IV) of a species, a number that integrates the degree of uniqueness to a place of a species and the abundance of that species within a given habitat. A high IV value indicates both high information content and a high probability of being sampled. The IV is apparently robust to differences in site number and species absolute abundances, and provides a single value for evaluating observed or expected changes in an ecosystem. Indicator species, furthermore, integrate habitat conditions over their lifespans, in contrast to measures of chemical and physical parameters that capture a snapshot of an ecosystem.
The basic evaluation approach here was to identify indicator species along a clear environmental gradient from meadow to forest in West Virginia. The habitat was divided into three zones, with an edge patch between the open meadows and closed-canopy forest. Near-surface soil cores were collected from each zone every month from April 2004 to April 2005 (n = 180), using the top of the mineral soil as the reference depth. Microarthropods were extracted in a modified Macfadyen funnel with a strong and increasing temperature gradient, into 70% ethanol.
Diversity measures, including Simpson’s and Shannon indices, were based on counts of individuals identified to family level (suborder for Acari). Differences between sites were analyzed by 2-way repeated measures ANOVA and Principle Components Analysis, after rare taxa (those that occurred in less than 10% of samples) were removed; rare taxa are extremely unlikely to be identified as indicator species.
Calculating IV for each taxon, regardless of the taxonomic resolution, provides large advantages in labour time and taxonomic expertise, as many microfauna are very difficult to identify to genus or species. These authors state that enumeration of a single sample required more than 1 hour of a trained taxonomist’s time. In studies such as this one, there are further advantages of IV associated with its robustness in the face of many zero measurements (i.e. taxa absent from samples) and the general messiness of these kinds of datasets. However, the ISA approach is intended for 2-stage studies, where an intensive initial survey identifies indicator species (taxa), and later long-term monitoring ignores other species. For studies specificially designed to address biodiversity, such as my own, excluding rare taxa would not be beneficial, and there may be no easy escape from time-consuming morphotaxa sorting.
I have spoken with Dr. Battigelli, the trained taxonomist in this study. He has indicated that while this IV-based approach may not be appropriate for my own work, it nonetheless demonstrates the types of analyses that can be conducted with soil invertebrates identified to middle taxonomic levels. He has assured me I could probably be trained to identify Collembola to Family and Acari to Suborder in a matter of a few days, and he would be interested in futher studies of collected soil invertebrates based on interesting patterns that emerge at these taxonomic levels.
These authors used a dataset of soil microarthropods to evaluate a method for identifying indicator species for ecosystem monitoring. The method centres on the Indicator Value (IV) of a species, a number that integrates the degree of uniqueness to a place of a species and the abundance of that species within a given habitat. A high IV value indicates both high information content and a high probability of being sampled. The IV is apparently robust to differences in site number and species absolute abundances, and provides a single value for evaluating observed or expected changes in an ecosystem. Indicator species, furthermore, integrate habitat conditions over their lifespans, in contrast to measures of chemical and physical parameters that capture a snapshot of an ecosystem.
The basic evaluation approach here was to identify indicator species along a clear environmental gradient from meadow to forest in West Virginia. The habitat was divided into three zones, with an edge patch between the open meadows and closed-canopy forest. Near-surface soil cores were collected from each zone every month from April 2004 to April 2005 (n = 180), using the top of the mineral soil as the reference depth. Microarthropods were extracted in a modified Macfadyen funnel with a strong and increasing temperature gradient, into 70% ethanol.
Diversity measures, including Simpson’s and Shannon indices, were based on counts of individuals identified to family level (suborder for Acari). Differences between sites were analyzed by 2-way repeated measures ANOVA and Principle Components Analysis, after rare taxa (those that occurred in less than 10% of samples) were removed; rare taxa are extremely unlikely to be identified as indicator species.
Calculating IV for each taxon, regardless of the taxonomic resolution, provides large advantages in labour time and taxonomic expertise, as many microfauna are very difficult to identify to genus or species. These authors state that enumeration of a single sample required more than 1 hour of a trained taxonomist’s time. In studies such as this one, there are further advantages of IV associated with its robustness in the face of many zero measurements (i.e. taxa absent from samples) and the general messiness of these kinds of datasets. However, the ISA approach is intended for 2-stage studies, where an intensive initial survey identifies indicator species (taxa), and later long-term monitoring ignores other species. For studies specificially designed to address biodiversity, such as my own, excluding rare taxa would not be beneficial, and there may be no easy escape from time-consuming morphotaxa sorting.
I have spoken with Dr. Battigelli, the trained taxonomist in this study. He has indicated that while this IV-based approach may not be appropriate for my own work, it nonetheless demonstrates the types of analyses that can be conducted with soil invertebrates identified to middle taxonomic levels. He has assured me I could probably be trained to identify Collembola to Family and Acari to Suborder in a matter of a few days, and he would be interested in futher studies of collected soil invertebrates based on interesting patterns that emerge at these taxonomic levels.
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