The Importance of Qualitative Sampling Methods: Examining Species Abundance
and Diversity in a Kelp Forest
Brett Banka
Abstract
Kelp forest ecosystems are highly dynamic in which they experience continuous
temporal and spatial changes at various magnitudes. An important topic in kelp forest
ecology involves examining the responses and recovery of these systems in the event of
environmental disturbances. The magnitude and impact of these environmental
disturbances vary from small-scale disturbances to large-scale El Nino Southern
Oscillation (ENSO) events that can affect the proper function and persistence of kelp
forest ecosystems (Edwards 2003). The patterns and variability in the distribution and
abundance of species in these systems are indicators of ecosystem function and overall
health (Edwards 2003). Qualitative sampling methods were used in this study to obtain
species abundance and diversity in a sub-tidal habitat of Hopkins Reef in Monterey Bay,
CA. The objective of this survey was to determine the effectiveness and accuracy of
qualitative sampling by measuring species abundance and diversity in a sub-tidal
environment. This study exemplifies that qualitative surveys are subject to high
variability but are often necessary when conducting research with parameters such as
time constraints and limited sampling methods when conducted in sub-tidal
environments.
Introduction
Kelp forest ecosystems are highly dynamic in which they experience continuous
temporal and spatial changes at various magnitudes. An important topic in kelp forest
ecology involves examining the responses and recovery of these systems in the event of
environmental disturbances. The magnitude and impact of these environmental
disturbances vary from small-scale disturbances to large-scale El Nino Southern
Oscillation (ENSO) events that can affect the proper function and persistence of kelp
forest ecosystems (Edwards 2003). Species diversity, coupled with species redundancy is
important in enabling marine sub-tidal communities to resist and recover from such
disturbance (Palumbi et al 2008). Kelp forests are among the most productive ecosystems
in the world and provide valuable habitat and resources that promote high species
abundance and diversity (Edwards 2003). Kelp forests are composed of spatially
heterogeneous mosaics of habitat-forming species that can support entire ecosystems
(Gorman and Connell 2009). The patterns and variability in the distribution and
abundance of species in these systems are indicators of ecosystem function and overall
health (Edwards 2003).
Species abundance and diversity can be measured using quantitative or qualitative
methods. Quantitative sampling involves methods of analysis that uses numeric
representations, whereas, qualitative sampling analyzes non-numeric representations
(Yoshikawa et al 2008). These methods are often used to determine taxonomic
composition and species richness and diversity (Garcia-Criado and Trigal 2005).
Qualitative samples are often smaller than quantitative because they are often more
difficult to obtain due to time and collection constraints (Yoshikawa et al 2008).
Qualitative sampling methods were used in this study to obtain species abundance and
diversity in a sub-tidal habitat of Hopkins Reef in Monterey Bay, CA. The objective of
this survey was to determine the effectiveness and accuracy of qualitative sampling by
measuring species abundance and diversity in a sub-tidal environment.
The accuracy in qualitative sampling methods are prone to differences due to
conflicting analysis based on a subjective (1-5) scale ranging from absent, rare, present,
common, and abundant. This level of measurement can seem arbitrary and may be
interpreted in various ways. Therefore, we expected to observe a difference in qualitative
sampling results of species abundance and diversity between and among buddy pairs.
Variance component analysis determined the accuracy of this qualitative survey with
respect to species abundance and diversity in relation to: depth (shallow versus deep
transect), buddy (difference between buddy pairs), and meter (distance along transect
cable).
There are some characteristics of certain species and taxonomy that may be
beneficial in using qualitative sampling methods. The behavior, morphology, and spatial
distribution of organisms can influence the effectiveness and accuracy of qualitative
sampling. Good candidates for qualitative sampling include organisms that are sessile,
less mobile, non-cryptic, and easily visible. Poor candidates are those that are highly
mobile, reclusive, cryptic, and not readily visible. Of the three taxonomic groups
surveyed in this study, we hypothesize that qualitative sampling methods would favor
algae over invertebrates and then fish.
Methods
Study Area
This qualitative sampling survey was conducted in the sub-tidal kelp forest of Hopkins
Reef at Hopkins Marine Station in Monterey, CA (36°37'16.15"N Latitude,
121°54'6.28"W Longitude). This survey was conducted to determine the species diversity
and distribution along the transect cable on the deep-offshore and shallow-near shore area
using qualitative sampling methods. Data was collected between 0900 and 1100 on
September 27, 2011.
Image 1) Map of Hopkins Reef transect cable
Qualitative Survey
Observational qualitative surveys were conducted by 14 dive teams on SCUBA to
estimate the species diversity of 6 species of algae, 9 species of fish, and 13 species of
invertebrates at Hopkins Reef (Table 1).
Algae and Plants
1) Cystoseira osmundacea
2) Gigartina corymbifera
3) Dictyoneurum californicum
4) Macrocystis pyrifera
5) Dictyonueropsis reticulata
6) Phyllospadix spp. (sea grass)
Fishes
1) Oxylebius pictus (painted greenling)
2) Hexagrammos decagrammus (kelp greenling)
3) Sebastes mystinus (blue rockfish)
4) Sebastes carnatus (gopher rockfish)
5) Sebastes chrysomelas (blk/ylw rockfish)
6) Sebastes atrovirens (kelp rockfish)
7) Embiotoca jacksoni (black surfperch)
8) Embiotoca lateralis (striped surfperch)
9) Damalichthys vacca (pile perch)
Invertebrates
1) Asterina miniata (bat star)
2) Pycnopodia helianthoides (sun star)
3) Pisaster brevispinus (short spined star)
4) Pisaster giganteus (great spined star)
5) Urticina picivora (fish eating anemone)
6) Urticina lofotensis (white-spotted anem.)
7) Pachycerianthus fimbriatus (sand anem.)
8) Balanophyllia elegans (cup coral)
9) Tethya aurantia (ball sponge)
10) Calliostoma ligatum (ring topped snail)
11) Loxorhynchus grandis (sheep crab)
12) Haliotis rufescens (red abalone)
13) Strongylocentrotus fransiscanus
Table 1) Target Species List
Each dive team collected data at a designated survey marker at 5m intervals along a 70m
transect. At each marker, dive teams used meter tapes to deploy two 30m transects, one
on the deep-off shore (heading 90o) and one on the shallow-near shore (heading 270o).
Data was collected at each out and in leg of the 30m transect for both deep-off shore and
shallow-near shore surveys. Data was collected by each diver in a (1m wide x 2m length
x 1m high) volume of water on each side of the transect tape. The relative abundance of
each target species was assessed on a 1-5 scale (1=absent, 2=rare, 3=present, 4=common,
and 5=abundant). Each member of each buddy team collected data independently.
Variance components analysis was used to compare results among the 14 dive teams to
determine the process of variability introduced at each level including: depth, buddy pair,
and distance along the transect cable.
Results
Figure 1: Percentage of variance associated with: depth (deep versus shallow transect),
buddy (between buddy pair), and meter (distance along transect cable). Percentage of
variance was 23% for depth, 37% for buddy, and 40% for meter.
What is the variance from?
Figure 2: Variance components by taxonomy (algae, fish, and invertebrates) associated
with: depth (deep versus shallow transect), buddy (between buddy pair), and meter
(distance along transect cable). Percentage of variance of taxonomy: algae (40% buddy,
10% depth, and 50% meter); fish (18% buddy, 22% depth, and 60% meter); invertebrates
(50% buddy and 50% depth).
Figure 3) Mean abundance for all species (fishes, algae, and invertebrates). Mean
abundance of taxonomy: fishes ~1.8; algae ~2.8; and invertebrates ~2.5.
Figure 4) Relative difference between buddies (%) based on rank data (1-5).
Figure 5) Percent disagreement between buddies based on presence and absence data.
Figure 6) Relative difference (%) between buddy pairs as a function of mean abundance
of species.
Discussion
This qualitative survey was conducted to measure the effectiveness and accuracy
of qualitative sampling methods in determining species abundance and diversity. Our
results agree with our hypothesis that our results differed among buddy pairs. Our results
in figure 1 demonstrate that percentage variance is associated with differences in depth,
buddy pair, and distance along the transect cable. The factors of depth and meter were
expected to account for larger proportions of variance based on differences between
locations. The percentage of variance associated with the buddy factor accounted for
approximately 37% of variance. Factors responsible for this variance may be due to
different interpretations of the (1-5) abundance scale between buddy pairs. Other factors
may be due to inconsistency in sampling methods conducted by different buddy pairs
(clarify this…how is this different than the last statement) Don’t be vague. Overall, the
buddy factor had a substantial effect on our sampling methods.
The percentage of variance components by taxonomy associated with depth,
buddy, and meter displayed that percentage of variance was responsible for 50% variance
for algae with respect to distance along the cable, as well as 60% for variance in fish;
whereas, variance in invertebrates had no effect with respect to distance along the cable.
Reasons for no variance in invertebrate abundance and diversity (you keep talking about
diversity…but did you analyze diversity??)is due to the 50% variance in the buddy factor
and 50% variance with respect to depth. Again, the buddy factor is responsible for a
substantial amount of variance.
The mean abundance for all species was separated into taxonomy (figure 3).
Mean abundance increased in taxonomic order of fish (~1.8) to invertebrates (~2.5) to
algae (~2.8) as we expected in our hypothesis. This result could be heavily influenced by
ability to sample organisms based on their level of assessment difficulty. Therefore, fish
being highly mobile makes it more difficult to sample, in contrast to algae that are sessile
and non-mobile.
The relative difference between buddies was assessed based on percentage of
difference and rank data scale (1-5) (figure 4). All results indicated a consistent
difference between buddies for all taxonomic groups. This result supports our hypothesis
that there is a difference between buddy pairs when assessing species on a qualitative
scale from absent, rare, present, common, and abundant. Differences in this assessment
may be due to difference in the interpretation of abundances of organisms based on the
(1-5) scale. The (1-5) scale was not discussed between or among buddy pairs prior to the
survey, therefore, leaving a broad gap for various personal interpretations.
Percent disagreement between buddies was also assessed based on presence and
absence data, which was analyzed and sorted into species and taxonomic groups (figure
5). Only two of the 28 species assessed had no disagreement based on presence and
absence. These species were giant kelp Macrocystis pyrifera and the bat star Asterina
miniata. Percent disagreement for these species could be low due to their assessment
characteristics that make them easier to identify and survey than other species.
The percentage of relative difference between buddy pairs was assessed with
respect to mean abundance of species (figure 6). The difference in disagreement peaked
at nearly ~80% at mean abundance level 2 (rare). Different assessment of whether a
species is rare or not can be highly variable based on personal interpretation.
This study demonstrates that qualitative surveys are subject to high variability but
are often necessary when conducting research with parameters such as time constraints
and limited sampling methods when conducted in sub-tidal environments. Qualitative
sampling is often used to measure the abundance of species to determine the qualitative
composition of a community. The assessment of the composition of species abundance
and diversity is often useful in indicating the structure of an ecosystem. Ecosystem
structure can indicate the stability of a system and it’s ability to respond to disturbance.
Not only are kelp forests vulnerable to environmental disturbance; they are also sensitive
to destructive anthropogenic influences. Human-induced disturbances can lead to altered
productivity and structure of kelp forest habitats resulting in regime-shifts that can wipe
out entire kelp forest communities (Gorman and Connell 2009). Kelp forest systems and
the species abundance and diversity they support are important indicators of the health of
temperate sub-tidal marine environments. Careful here. Keep your assessment and
conclusion to what you were discussing in the paper….the effectiveness of qualitative
surveys to measure the abundance of species. These points would be better lead into why
we need to monitor kelp forests.
References
Edwards, M. (2004). Estimating Scale-Dependency in Disturbance Impacts: El Niños and
Giant Kelp Forests in the Northeast Pacific. International Association for Ecology
138:436-447
Garcia-Criado, F. and Trigal, C. (2005). Comparison of several techniques for sampling
macroinvertebrates in different habitats of a North Iberian pond. Hydrobiologia
545:103-115
Gorman, D., and Connell, S. (2009) Recovering subtidal forests in human-dominated
landscapes. Journal of Applied Ecology 46:1258-1265
Palumbi, S. et al (2008). Ecosystems in action: lessons from marine ecology about
recovery, resistance, and reversibility. Bioscience 58:33-42
Yoshikawa, H. et al (2008). Mixing qualitative and quantitative research in
developmental science: uses and methodological choices. Developmental
Psycology 44:344-354
Results (25)
__4__/4 Figure legends Accurate
_3___/4 Figure Legends well composed (complete and concise)
__0__/5 Results organized according to questions
__1__/4 Graphs presented in a logical order, case made for the order
__0__/4 Grammar, sentence structure and spelling
__0__/4 Clarity and conciseness of writing
Discussion (25)
____/9 How well did they answer the questions they present in the Intro?
1) __3__/3 Discuss the results from the specific to the general.
2) __3__/3 Do these results surprise you? In other words, is the qualitative method more or less
reliable than you thought it would be, and do you think that degree of reliability (which can be
assessed based on relative difference between buddies) implies anything about accuracy?
3) __2__/3 Do you think the qualitative sampling approach is appropriate for describing trends
of species abundances through time? Explain your answer
__3__/3 Grammar and Spelling
__2__/2 General Thoughtfulness
__3__/3 Clarity and conciseness
__4__/5 Organization of discussion
__3__/3 Context and Bigger Picture
General Notes: A results section is not just graphs. You need to provide text to make logical linkages and
present data that might not be in the graphs.