- Email: [email protected]
Abundance Biomass Comparison Method
Ecological Indicators | Abundance Biomass Comparison Method 11
Abundance Biomass Comparison Method R M Warwick, Plymouth Marine Laboratory, Plymouth, UK ª 2008 Elsevier B.V. All rights reserved.
Introduction The Method Applications
Problems and Their Solutions Further Reading
Introduction
biomasses on the same graph and comparing the forms of the two curves relative to each other. The species are ranked in order of importance in terms of abundance or biomass on the x-axis on a logarithmic scale, with percentage dominance on the y-axis on a cumulative scale. Of course the species ordering is unlikely to be the same for abundance and biomass. In undisturbed assemblages a few large species are dominant in terms of biomass but not abundance, resulting in the elevation of the biomass curve relative to the abundance curve throughout its length (Figure 1a). Perturbed assemblages, however, have a few species with very high abundance but small body size so that they do not dominate the biomass and the abundance curve lies above the biomass curve (Figure 1c). Under moderate perturbation the large competitive dominants are eliminated but there is no population explosion of small opportunists, so that the inequality in size between the numerical and biomass dominants is reduced and the biomass and abundance curves are closely coincident and may cross over each other one or more times (Figure 1b). The contention is that these three conditions (unperturbed, moderately perturbed, or grossly perturbed) should be recognizable without reference control samples in time or space, the two curves acting as an internal control against each other and providing a snapshot of the condition of the assemblage at any one time or place.
The ‘abundance biomass comparison’ (ABC) method is a means of detecting the effects of anthropogenic perturbations on assemblages of organisms that is underpinned by the r- and K-selection theory (see r-Strategist/K-Strategists). Under stable conditions of infrequent disturbance the competitive dominants in the climax community are K-selected or conservative species with a large body size and long life span, and are usually of low abundance so that they are not dominant numerically but are dominant in terms of biomass. Frequently disturbed assemblages are kept at an early successional stage and comprise r-selected or opportunistic species characterized by small body size, short life span and high abundance. The ABC method exploits the fact that when an assemblage is perturbed the conservative species are less favored in comparison with the opportunists, and the distribution of biomass among species behaves differently from the distribution of numbers of individuals among species.
The Method The ABC method as originally formulated involves the plotting of separate k-dominance curves (see k-Dominance Curves) for species abundances and species
(b)
(a)
(c)
Cumulative %
100
ss
ma
Bio
nce
un
Ab
50
ss
ma
Bio
s
as
m
ce dan
un
Ab
nda Abu
ce
n da
o Bi
Moderately perturbed
Unperturbed
Grossly perturbed
0 1
5
10
1
5
10
1
5
10
Species rank (log scale) Figure 1 Hypothetical k-dominance curves for species biomass and abundance, showing unperturbed, moderately perturbed, and grossly perturbed conditions.
12
Ecological Indicators | Abundance Biomass Comparison Method
Of course, confirmatory comparisons with spatial or temporal reference samples are still highly desirable. A prerequisite of the method is adequate sample size or replication because the large biomass dominants are often rare and liable to a higher sampling error than the numerical dominants. The evaluation of ABC curves involves their visual inspection, and can be cumbersome if many sites, times, or replicates are involved. In such cases it is convenient to reduce each plot to a single summary statistic. If the abundance (A) values are subtracted from the biomass (B) values for each species rank in the ABC curve, the sum of the B A values across the ranks will be strongly positive in the unperturbed case (Figure 1a), near zero in the case where the curves are closely coincident (Figure 1b), and strongly negative where the curves are transposed (Figure 1c). The summation needs to be standardized to a common scale so that comparisons can be made between samples with differing numbers of species (S), the most widely used form being the W (for Warwick) statistic: W ¼
S X ðBi – Ai Þ=½50ðS – 1Þ i¼1
necessary if a single species diversity measure based on the abundance distribution was used as the only criterion. Most studies suggest that the ABC curves respond to anthropogenic perturbations but are not affected by longterm natural stresses, since the organisms living in such environments have evolved adaptations to the prevailing ecological conditions. Unperturbed ABC plots may be found, for example, in estuaries where the organisms are subjected to low and fluctuating salinities, provided there are no anthropogenic disturbances. ABC plots indicated that macrobenthic communities near an oil refinery in Trinidad were grossly to moderately stressed, while those close to the Trinidad Pitch Lake (one of the largest natural oil seeps in the world) were not. There is little evidence, however, that the method can distinguish between different types of anthropogenic disturbances. Responses to organic pollution and to physical disturbance caused by demersal trawl fisheries, for example, appear to be similar. The method has been less well explored with respect to other components of the biota. However, it has been used successfully to indicate environmental impacts on marine phytoplankton, the cryptofauna and mollusks of rocky shores, invertebrates of freshwater streams, and fish assemblages in both marine and freshwater.
For replicated samples, the W statistic also provides an obvious route for hypothesis testing, using standard univariate ANOVA.
Problems and Their Solutions
Applications For the most part, ABC curves have been used to indicate pollution or disturbance effects on marine and estuarine macrobenthic assemblages, which are the main target for detection and monitoring programs in these habitats. For example, ABC curves for the macrobenthos in Loch Linnhe, Scotland in response to organic pollution between 1963 and 1973 are given in Figure 2. The time course of pollution from a pulp mill, and changes in species diversity (H9), are shown top left. Moderate pollution started in 1966, and by 1968 species diversity was reduced. Prior to 1968 the ABC curves had the unpolluted configuration. From 1968 to 1970 the ABC plots indicated moderate pollution. In 1970 there was an increase in pollutant loadings and a further reduction in species diversity, reaching a minimum in 1972, and the ABC plots for 1971 and 1972 show the grossly polluted configuration. In 1972 pollution decreased and by 1973 diversity had increased, and the ABC plots again indicated the unpolluted condition. Thus, the ABC plots provide a good snapshot of the pollution status of the benthic community in any one year, without reference to the historical comparative data which would be
Very often k-dominance curves approach a cumulative frequency of 100% for a large part of their length, and in highly dominated assemblages this may be after the first two or three top-ranked species. Thus, it may be difficult to distinguish between the forms of these curves. The solution to this problem is to transform the y-axis so that the cumulative values are closer to linearity, an appropriate transformation being the modified logistic transformation: yi9 ¼ log½ð1 þ yi Þ=ð101 – yi Þ
A potentially more serious problem with the cumulative nature of ABC curves is that their form is overdependent on the single most dominant species. The unpredictable presence of large numbers of a species with small biomass, perhaps an influx of the juveniles of one species, may give a false impression of disturbance. With genuine disturbance, one might expect patterns of ABC curves to be unaffected by successive removal of the one or two most dominant species in terms of abundance or biomass, and a solution is the use of partial dominance curves, which compute the dominance of the second-ranked species over the remainder (ignoring the first-ranked species), the same with the third most dominant, etc. Thus, if ai is the absolute (or percentage) abundance of the ith species, when ranked
3
100
Decrease
Diversity (H ′ )
4
Increase
Start
Ecological Indicators | Abundance Biomass Comparison Method 13
2
80
B
B
60
A
A
40 20
1963
1964
1 64 66 68 70 72
0
100
B
B
80
B
60
A
40 20
A 1965
A 1966
1967
0
Cumulative (%)
100 80
A
A
60
B
A B
40
B 20
1968
1969
1970
0 100
A A
80
B B
60
B A
40 20
1971
1972
1973
0 1
10
1
10
1
10
Species rank Figure 2 Loch Linnhe macrofauna: Shannon diversity (H9) and ABC plots over the 11 years, 1963 to 1973. Abundance, thick line; biomass, thin line.
in decreasing abundance order, the partial dominance curve is a plot of pi against log i (i ¼ 1, 2, . . . , S 1), where p1 ¼ 100a1 p2 ¼ 100a2
. XS
a j ¼1 j
. XS
. a ; . . . ; p ¼ 100a ðaS – 1 þ aS Þ j S – 1 S – 1 j ¼2
Earlier values can therefore never affect later points on the curve. The partial dominance curves (ABC) for undisturbed macrobenthic communities typically look like Figures 3g and 3h, with the biomass curve (thin line) above the abundance curve (thick line) throughout its length. The abundance curve is much smoother than the biomass curve, showing a slight and steady decline before the inevitable final rise. Under polluted conditions there is still a change in position of partial dominance curves for
abundance and biomass, with the abundance curve now above the biomass curve in places, and the abundance curve becoming much more variable. This implies that pollution effects are not just seen in changes to a few dominant species but are a phenomenon which pervades the complete suite of species in the community. The time series of macrobenthos data from Loch Linnhe (Figure 3) shows that in the most polluted years, 1971 and 1972, the abundance curve is above the biomass curve for most of its length (and the abundance curve is very atypically erratic), the curves cross over in the moderately polluted years 1968 and 1970 and have an unpolluted configuration prior to the pollution impact in 1966 and 1967. Although these curves are not so smooth, and therefore not so visually appealing, as the original ABC curves, they may provide a useful alternative aid to interpretation and are certainly more
14
Ecological Indicators | Abundance Biomass Comparison Method (a)
100
(b)
(c) B A
Cumulative % dominance
90
B 70 50 30
B A
A 1966
1967
1968
10
(d)
100
(e)
(f)
B 90
A
A B
A
B
70 50 30
1971
1970
10
(g)
1972
(h)
(i)
60
B
Partial % dominance
40
B
A B
20
A
A
0
1967
1966
(j)
1968
(k)
(l)
60
A 40
A
A B
20
B
B 1971
1970
0 1
10
1
10
1972 1
10
Species rank Figure 3 Loch Linnhe macrofauna in selected years 1966–68 and 1970–72. (a–f) ABC curves (logistic transform). (g–l) Partial dominance curves for abundance (thick line) and biomass (thin line) for the same years.
robust to random fluctuations in the abundance of a smallsized, numerically dominant species. In most cases where the presence of large numbers of small-bodied macrobenthic species in unperturbed situations has given a false impression of disturbance, those species have not been polychaetes. Prior to the Amoco Cadiz oil spill off the north coast of France in 1978, small ampeliscid amphipods (Crustacea) were present at the Pierre Noire station in relatively high abundance, and their disappearance after the spill confounded the ABC plots. The erratic presence of large numbers of small amphipods (Corophium) or mollusks (Hydrobia) also confounded these plots in the Wadden Sea. These small nonpolychaetous species are not indicative of polluted conditions. A taxonomic breakdown of the ABC response has shown that it results from (1) a shift in the proportions of different phyla present in
communities, some phyla having larger-bodied species than others, and (2) a shift in the relative distributions of abundance and biomass among species within the Polychaeta but not within any of the other major phyla (Mollusca, Crustacea, Echinodermata). The shift within polychaetes reflects the substitution of larger-bodied by smaller-bodied species, and not a change in the average size of individuals within a species. In most instances the phyletic changes reinforce the trend in species substitutions within the polychaetes, to produce the overall ABC response, but in some cases they may work against each other. Indications of pollution or disturbance for marine macrobenthos detected by this method should therefore be viewed with caution if the species responsible for the perturbed configurations are not polychaetes, and the robustness of the plots should be tested using partial dominance curves.
Behavioral Ecology | Acclimation 15
Finally, a practical rather than a conceptual problem with the method is that it relies on a painstaking and timeconsuming (and hence costly) analysis of samples in which all the species must be separated, counted, and weighed. Several groups of marine organisms are taxonomically difficult, for example (in the macrobenthos), several families of polychaetes and amphipods; as much time can be spent in separating a few of these difficult groups into species as the entire remainder of the sample, even in Northern Europe where taxonomic keys for identification are most readily available. Many taxa really require the skills of specialists to separate them into species, and this is especially true in parts of the world where fauna is poorly described. Identification to some higher taxonomic level, for example, family rather than species, is considerably easier and quicker, and the ABC method has proved to be encouragingly robust to analysis at the family level for both macrobenthos and fish; very little information appears to be lost. See also: k-Dominance Curves; r-Strategist/ K-Strategists.
Further Reading Agard JBR, Gobin J, and Warwick RM (1993) Analysis of marine macrobenthic community structure in relation to oil pollution, natural oil seepage, and seasonal disturbance in a tropical environment (Trinidad, West Indies). Marine Ecology Progress Series 92: 233–243. Beukema JJ (1988) An evaluation of the ABC-method (abundance/ biomass comparison) as applied to macrozoobenthic communities
living on tidal flats in the Dutch Wadden Sea. Marine Biology 99: 425–433. Blanchard F, LeLoc’h F, Hily C, and Boucher J (2004) Fishing effects on diversity, size, and community structure of the benthic invertebrate and fish megafauna on the Bay of Biscay coast of France. Marine Ecology Progress Series 280: 249–260. Clarke KR (1990) Comparisons of dominance curves. Journal of Experimental Marine Biology and Ecology 138: 143–157. Dauer DM, Luckenbach MW, and Rodi AJ (1993) Abundance biomass comparison (ABC method) – Effects of an estuarine gradient, anoxic hypoxic events and contaminated sediments. Marine Biology 116: 507–518. Ismael AA and Dorgham MM (2003) Ecological indices as a tool for assessing pollution in El-Dekhaila Harbour (Alexandria, Egypt). Oceanologia 45: 121–131. Jouffre D and Inejih CA (2005) Assessing the impact of fisheries on demersal fish assemblages of the Mauritanian continental; shelf, 1987–1999, using dominance curves. ICES Journal of Marine Science 62: 380–383. Lasiak T (1999) The putative impact of exploitation on rocky infratidal macrofaunal assemblages: A multiple area comparison. Journal of the Marine Biological Association of the United Kingdom 79: 23–34. Magurran AE (2004) Measuring Biological Diversity. Oxford: Blackwell. Penczak T and Kruk A (1999) Applicability of the abundance/biomass comparison method for detecting human impacts on fish populations in the Pilica River, Poland. Fisheries Research 39: 229–240. Warwick RM (1986) A new method for detecting pollution effects on marine macrobenthic communities. Marine Biology 92: 557–562. Warwick RM and Clarke KR (1994) Relearning the ABC: Taxonomic changes and abundance/biomass relationships in disturbed benthic communities. Marine Biology 118: 739–744. Warwick RM, Pearson TH, and Ruswahyuni (1987) Detection of pollution effects on marine macrobenthos: Further evaluation of the species abundance/biomass method. Marine Biology 95: 193–200. Yemane D, Field JG, and Leslie RW (2005) Exploring the effects of fishing on fish assemblages using abundance biomass comparison (ABC) curves. ICES Journal of Marine Science 62: 374–379.
Acclimation B Demmig-Adams, M R Dumlao, M K Herzenach, and W W Adams III, University of Colorado, Boulder, CO, USA ª 2008 Elsevier B.V. All rights reserved.
Acclimation versus Adaptation Do Plants Have a Particularly High Potential for Acclimation? Acclimation Patterns Depend on Species and the Severity of the Environment
Principal Types of Adjustments: Plant Form, Function, and Lifecycle Acclimation Responses to Specific Environmental Factors Oxidative Stress and Redox Signaling as Common Denominators in Stress Perception and Response Further Reading
Acclimation versus Adaptation
constrained by the genome of the individual. In turn, adaptation involves the acquisition or recombination of genetic traits that improve performance or survival over multiple generations. For example, all plants have the ability to adjust their form and function to acclimate to some extent to, for example, warmer versus cooler
Acclimation involves physiological, anatomical, or morphological adjustments within a single organism that improve performance or survival in response to environmental change. The extent of this acclimation is
Abundance Biomass Comparison Method R M Warwick, Plymouth Marine Laboratory, Plymouth, UK ª 2008 Elsevier B.V. All rights reserved.
Introduction The Method Applications
Problems and Their Solutions Further Reading
Introduction
biomasses on the same graph and comparing the forms of the two curves relative to each other. The species are ranked in order of importance in terms of abundance or biomass on the x-axis on a logarithmic scale, with percentage dominance on the y-axis on a cumulative scale. Of course the species ordering is unlikely to be the same for abundance and biomass. In undisturbed assemblages a few large species are dominant in terms of biomass but not abundance, resulting in the elevation of the biomass curve relative to the abundance curve throughout its length (Figure 1a). Perturbed assemblages, however, have a few species with very high abundance but small body size so that they do not dominate the biomass and the abundance curve lies above the biomass curve (Figure 1c). Under moderate perturbation the large competitive dominants are eliminated but there is no population explosion of small opportunists, so that the inequality in size between the numerical and biomass dominants is reduced and the biomass and abundance curves are closely coincident and may cross over each other one or more times (Figure 1b). The contention is that these three conditions (unperturbed, moderately perturbed, or grossly perturbed) should be recognizable without reference control samples in time or space, the two curves acting as an internal control against each other and providing a snapshot of the condition of the assemblage at any one time or place.
The ‘abundance biomass comparison’ (ABC) method is a means of detecting the effects of anthropogenic perturbations on assemblages of organisms that is underpinned by the r- and K-selection theory (see r-Strategist/K-Strategists). Under stable conditions of infrequent disturbance the competitive dominants in the climax community are K-selected or conservative species with a large body size and long life span, and are usually of low abundance so that they are not dominant numerically but are dominant in terms of biomass. Frequently disturbed assemblages are kept at an early successional stage and comprise r-selected or opportunistic species characterized by small body size, short life span and high abundance. The ABC method exploits the fact that when an assemblage is perturbed the conservative species are less favored in comparison with the opportunists, and the distribution of biomass among species behaves differently from the distribution of numbers of individuals among species.
The Method The ABC method as originally formulated involves the plotting of separate k-dominance curves (see k-Dominance Curves) for species abundances and species
(b)
(a)
(c)
Cumulative %
100
ss
ma
Bio
nce
un
Ab
50
ss
ma
Bio
s
as
m
ce dan
un
Ab
nda Abu
ce
n da
o Bi
Moderately perturbed
Unperturbed
Grossly perturbed
0 1
5
10
1
5
10
1
5
10
Species rank (log scale) Figure 1 Hypothetical k-dominance curves for species biomass and abundance, showing unperturbed, moderately perturbed, and grossly perturbed conditions.
12
Ecological Indicators | Abundance Biomass Comparison Method
Of course, confirmatory comparisons with spatial or temporal reference samples are still highly desirable. A prerequisite of the method is adequate sample size or replication because the large biomass dominants are often rare and liable to a higher sampling error than the numerical dominants. The evaluation of ABC curves involves their visual inspection, and can be cumbersome if many sites, times, or replicates are involved. In such cases it is convenient to reduce each plot to a single summary statistic. If the abundance (A) values are subtracted from the biomass (B) values for each species rank in the ABC curve, the sum of the B A values across the ranks will be strongly positive in the unperturbed case (Figure 1a), near zero in the case where the curves are closely coincident (Figure 1b), and strongly negative where the curves are transposed (Figure 1c). The summation needs to be standardized to a common scale so that comparisons can be made between samples with differing numbers of species (S), the most widely used form being the W (for Warwick) statistic: W ¼
S X ðBi – Ai Þ=½50ðS – 1Þ i¼1
necessary if a single species diversity measure based on the abundance distribution was used as the only criterion. Most studies suggest that the ABC curves respond to anthropogenic perturbations but are not affected by longterm natural stresses, since the organisms living in such environments have evolved adaptations to the prevailing ecological conditions. Unperturbed ABC plots may be found, for example, in estuaries where the organisms are subjected to low and fluctuating salinities, provided there are no anthropogenic disturbances. ABC plots indicated that macrobenthic communities near an oil refinery in Trinidad were grossly to moderately stressed, while those close to the Trinidad Pitch Lake (one of the largest natural oil seeps in the world) were not. There is little evidence, however, that the method can distinguish between different types of anthropogenic disturbances. Responses to organic pollution and to physical disturbance caused by demersal trawl fisheries, for example, appear to be similar. The method has been less well explored with respect to other components of the biota. However, it has been used successfully to indicate environmental impacts on marine phytoplankton, the cryptofauna and mollusks of rocky shores, invertebrates of freshwater streams, and fish assemblages in both marine and freshwater.
For replicated samples, the W statistic also provides an obvious route for hypothesis testing, using standard univariate ANOVA.
Problems and Their Solutions
Applications For the most part, ABC curves have been used to indicate pollution or disturbance effects on marine and estuarine macrobenthic assemblages, which are the main target for detection and monitoring programs in these habitats. For example, ABC curves for the macrobenthos in Loch Linnhe, Scotland in response to organic pollution between 1963 and 1973 are given in Figure 2. The time course of pollution from a pulp mill, and changes in species diversity (H9), are shown top left. Moderate pollution started in 1966, and by 1968 species diversity was reduced. Prior to 1968 the ABC curves had the unpolluted configuration. From 1968 to 1970 the ABC plots indicated moderate pollution. In 1970 there was an increase in pollutant loadings and a further reduction in species diversity, reaching a minimum in 1972, and the ABC plots for 1971 and 1972 show the grossly polluted configuration. In 1972 pollution decreased and by 1973 diversity had increased, and the ABC plots again indicated the unpolluted condition. Thus, the ABC plots provide a good snapshot of the pollution status of the benthic community in any one year, without reference to the historical comparative data which would be
Very often k-dominance curves approach a cumulative frequency of 100% for a large part of their length, and in highly dominated assemblages this may be after the first two or three top-ranked species. Thus, it may be difficult to distinguish between the forms of these curves. The solution to this problem is to transform the y-axis so that the cumulative values are closer to linearity, an appropriate transformation being the modified logistic transformation: yi9 ¼ log½ð1 þ yi Þ=ð101 – yi Þ
A potentially more serious problem with the cumulative nature of ABC curves is that their form is overdependent on the single most dominant species. The unpredictable presence of large numbers of a species with small biomass, perhaps an influx of the juveniles of one species, may give a false impression of disturbance. With genuine disturbance, one might expect patterns of ABC curves to be unaffected by successive removal of the one or two most dominant species in terms of abundance or biomass, and a solution is the use of partial dominance curves, which compute the dominance of the second-ranked species over the remainder (ignoring the first-ranked species), the same with the third most dominant, etc. Thus, if ai is the absolute (or percentage) abundance of the ith species, when ranked
3
100
Decrease
Diversity (H ′ )
4
Increase
Start
Ecological Indicators | Abundance Biomass Comparison Method 13
2
80
B
B
60
A
A
40 20
1963
1964
1 64 66 68 70 72
0
100
B
B
80
B
60
A
40 20
A 1965
A 1966
1967
0
Cumulative (%)
100 80
A
A
60
B
A B
40
B 20
1968
1969
1970
0 100
A A
80
B B
60
B A
40 20
1971
1972
1973
0 1
10
1
10
1
10
Species rank Figure 2 Loch Linnhe macrofauna: Shannon diversity (H9) and ABC plots over the 11 years, 1963 to 1973. Abundance, thick line; biomass, thin line.
in decreasing abundance order, the partial dominance curve is a plot of pi against log i (i ¼ 1, 2, . . . , S 1), where p1 ¼ 100a1 p2 ¼ 100a2
. XS
a j ¼1 j
. XS
. a ; . . . ; p ¼ 100a ðaS – 1 þ aS Þ j S – 1 S – 1 j ¼2
Earlier values can therefore never affect later points on the curve. The partial dominance curves (ABC) for undisturbed macrobenthic communities typically look like Figures 3g and 3h, with the biomass curve (thin line) above the abundance curve (thick line) throughout its length. The abundance curve is much smoother than the biomass curve, showing a slight and steady decline before the inevitable final rise. Under polluted conditions there is still a change in position of partial dominance curves for
abundance and biomass, with the abundance curve now above the biomass curve in places, and the abundance curve becoming much more variable. This implies that pollution effects are not just seen in changes to a few dominant species but are a phenomenon which pervades the complete suite of species in the community. The time series of macrobenthos data from Loch Linnhe (Figure 3) shows that in the most polluted years, 1971 and 1972, the abundance curve is above the biomass curve for most of its length (and the abundance curve is very atypically erratic), the curves cross over in the moderately polluted years 1968 and 1970 and have an unpolluted configuration prior to the pollution impact in 1966 and 1967. Although these curves are not so smooth, and therefore not so visually appealing, as the original ABC curves, they may provide a useful alternative aid to interpretation and are certainly more
14
Ecological Indicators | Abundance Biomass Comparison Method (a)
100
(b)
(c) B A
Cumulative % dominance
90
B 70 50 30
B A
A 1966
1967
1968
10
(d)
100
(e)
(f)
B 90
A
A B
A
B
70 50 30
1971
1970
10
(g)
1972
(h)
(i)
60
B
Partial % dominance
40
B
A B
20
A
A
0
1967
1966
(j)
1968
(k)
(l)
60
A 40
A
A B
20
B
B 1971
1970
0 1
10
1
10
1972 1
10
Species rank Figure 3 Loch Linnhe macrofauna in selected years 1966–68 and 1970–72. (a–f) ABC curves (logistic transform). (g–l) Partial dominance curves for abundance (thick line) and biomass (thin line) for the same years.
robust to random fluctuations in the abundance of a smallsized, numerically dominant species. In most cases where the presence of large numbers of small-bodied macrobenthic species in unperturbed situations has given a false impression of disturbance, those species have not been polychaetes. Prior to the Amoco Cadiz oil spill off the north coast of France in 1978, small ampeliscid amphipods (Crustacea) were present at the Pierre Noire station in relatively high abundance, and their disappearance after the spill confounded the ABC plots. The erratic presence of large numbers of small amphipods (Corophium) or mollusks (Hydrobia) also confounded these plots in the Wadden Sea. These small nonpolychaetous species are not indicative of polluted conditions. A taxonomic breakdown of the ABC response has shown that it results from (1) a shift in the proportions of different phyla present in
communities, some phyla having larger-bodied species than others, and (2) a shift in the relative distributions of abundance and biomass among species within the Polychaeta but not within any of the other major phyla (Mollusca, Crustacea, Echinodermata). The shift within polychaetes reflects the substitution of larger-bodied by smaller-bodied species, and not a change in the average size of individuals within a species. In most instances the phyletic changes reinforce the trend in species substitutions within the polychaetes, to produce the overall ABC response, but in some cases they may work against each other. Indications of pollution or disturbance for marine macrobenthos detected by this method should therefore be viewed with caution if the species responsible for the perturbed configurations are not polychaetes, and the robustness of the plots should be tested using partial dominance curves.
Behavioral Ecology | Acclimation 15
Finally, a practical rather than a conceptual problem with the method is that it relies on a painstaking and timeconsuming (and hence costly) analysis of samples in which all the species must be separated, counted, and weighed. Several groups of marine organisms are taxonomically difficult, for example (in the macrobenthos), several families of polychaetes and amphipods; as much time can be spent in separating a few of these difficult groups into species as the entire remainder of the sample, even in Northern Europe where taxonomic keys for identification are most readily available. Many taxa really require the skills of specialists to separate them into species, and this is especially true in parts of the world where fauna is poorly described. Identification to some higher taxonomic level, for example, family rather than species, is considerably easier and quicker, and the ABC method has proved to be encouragingly robust to analysis at the family level for both macrobenthos and fish; very little information appears to be lost. See also: k-Dominance Curves; r-Strategist/ K-Strategists.
Further Reading Agard JBR, Gobin J, and Warwick RM (1993) Analysis of marine macrobenthic community structure in relation to oil pollution, natural oil seepage, and seasonal disturbance in a tropical environment (Trinidad, West Indies). Marine Ecology Progress Series 92: 233–243. Beukema JJ (1988) An evaluation of the ABC-method (abundance/ biomass comparison) as applied to macrozoobenthic communities
living on tidal flats in the Dutch Wadden Sea. Marine Biology 99: 425–433. Blanchard F, LeLoc’h F, Hily C, and Boucher J (2004) Fishing effects on diversity, size, and community structure of the benthic invertebrate and fish megafauna on the Bay of Biscay coast of France. Marine Ecology Progress Series 280: 249–260. Clarke KR (1990) Comparisons of dominance curves. Journal of Experimental Marine Biology and Ecology 138: 143–157. Dauer DM, Luckenbach MW, and Rodi AJ (1993) Abundance biomass comparison (ABC method) – Effects of an estuarine gradient, anoxic hypoxic events and contaminated sediments. Marine Biology 116: 507–518. Ismael AA and Dorgham MM (2003) Ecological indices as a tool for assessing pollution in El-Dekhaila Harbour (Alexandria, Egypt). Oceanologia 45: 121–131. Jouffre D and Inejih CA (2005) Assessing the impact of fisheries on demersal fish assemblages of the Mauritanian continental; shelf, 1987–1999, using dominance curves. ICES Journal of Marine Science 62: 380–383. Lasiak T (1999) The putative impact of exploitation on rocky infratidal macrofaunal assemblages: A multiple area comparison. Journal of the Marine Biological Association of the United Kingdom 79: 23–34. Magurran AE (2004) Measuring Biological Diversity. Oxford: Blackwell. Penczak T and Kruk A (1999) Applicability of the abundance/biomass comparison method for detecting human impacts on fish populations in the Pilica River, Poland. Fisheries Research 39: 229–240. Warwick RM (1986) A new method for detecting pollution effects on marine macrobenthic communities. Marine Biology 92: 557–562. Warwick RM and Clarke KR (1994) Relearning the ABC: Taxonomic changes and abundance/biomass relationships in disturbed benthic communities. Marine Biology 118: 739–744. Warwick RM, Pearson TH, and Ruswahyuni (1987) Detection of pollution effects on marine macrobenthos: Further evaluation of the species abundance/biomass method. Marine Biology 95: 193–200. Yemane D, Field JG, and Leslie RW (2005) Exploring the effects of fishing on fish assemblages using abundance biomass comparison (ABC) curves. ICES Journal of Marine Science 62: 374–379.
Acclimation B Demmig-Adams, M R Dumlao, M K Herzenach, and W W Adams III, University of Colorado, Boulder, CO, USA ª 2008 Elsevier B.V. All rights reserved.
Acclimation versus Adaptation Do Plants Have a Particularly High Potential for Acclimation? Acclimation Patterns Depend on Species and the Severity of the Environment
Principal Types of Adjustments: Plant Form, Function, and Lifecycle Acclimation Responses to Specific Environmental Factors Oxidative Stress and Redox Signaling as Common Denominators in Stress Perception and Response Further Reading
Acclimation versus Adaptation
constrained by the genome of the individual. In turn, adaptation involves the acquisition or recombination of genetic traits that improve performance or survival over multiple generations. For example, all plants have the ability to adjust their form and function to acclimate to some extent to, for example, warmer versus cooler
Acclimation involves physiological, anatomical, or morphological adjustments within a single organism that improve performance or survival in response to environmental change. The extent of this acclimation is