text:
Converting SACFOR data for statistical analysis: validation, demonstration and further possibilities
James Asa Strong1 &
Magnus Johnson2
Marine Biodiversity Records volume 13, Article number: 2 (2020) Cite this article
Background: the context and purpose of the study
Semi-quantitative scales are often used for the rapid assessment of species composition and abundance during time-limited surveys. The semi-quantitative SACFOR abundance scale was developed to support the observation of marine habitats, communities and species and is widely used in the UK. As such, there is now a vast accumulation of SACFOR data. However, there several acknowledged limitations associated with its format that prevent re-analysis.
Methods: how the study was performed and statistical tests used
A conversion process is proposed here that allows: (i) the merging of taxa within counts or cover data sub-sets; (ii) observations, based on either counts and cover, to be unified into one matrix; (iii) counts and cover data to have an equal weighting in the final matrix; and (iv) the removal of the influence of body size and growth form from the final values. To achieve this, it is only possible to preserve the ordinal structure of the data set.
Results: the main findings
Simulations verified that the SACFOR conversion process (i) converted random cover and counts data whilst maintaining the majority of the ordinal structure and (ii) aligned abundance values regardless of whether it was recorded as a cover or count. A case study is presented, that uses real SACFOR observations, to demonstrate the conversion process and the application of statistical analyses routinely used in ecological assessments.
Conclusions: brief summary and potential implications
It is hoped that the SACFOR conversion process proposed here facilitates: (i) the quantitative re-analysis of the burgeoning SACFOR data repository; and (ii) initiates a debate on alternative methods for the conversion of SACFOR data into analysable end products.
The full quantification assessment of the seabed communities is often not possible or necessary. Investigations of marine habitats are often severely limited by the availability of survey time. For example, periodic tidal exposure, high ship costs and the limited bottom time of diving operations, all constrain the time available for the collection of information. This constraint is particularly acute when undertaking descriptive or inventory surveys of marine habitats, which requires the recording of numerous physical and biological variables (e.g. the identity and abundance of the common species present) across large areas of seabed. Habitats that are also highly heterogeneous or hard to sample (e.g. boulder-strewn shores) are also harder to assess quantitatively (Hawkins and Jones, 1992). Effective sampling using standard quantitative techniques, such as quadrats, is further hampered by, among others, a number of unknowns such as aversion of mobile species to sampling equipment, differential abilities to escape nets/traps, taxonomic uncertainty, cryptic species, differences in deployment of equipment between operators and visibility (Millier and Ambrose, 2000; Guisan et al., 2006). Thus it could be argued that even "fully quantitative" techniques are in reality often actually semi-quantitative.
When standard quantitative sampling that results in counts of individuals or measurements of cover is not practical, biologists have developed various semi-quantitative scales, also called abundance scales, for the rapid assessment of abundance and cover (e.g. the Semi-Quantitative Macroinvertebrate Community Index (Stark, 1998) and EPOS ANTARKTIS Scale (Arnaud et al., 1990). Although these scales typically contain 5 to 7 broad categories and therefore lack the precision of quantitative methods, they do allow the coarse assessment of abundance both accurately and quickly (Hawkins and Jones, 1992). These scales were originally developed for terrestrial applications, such as the six point Braun-Blanquet cover-abundance scale (Braun-Blanquet 1932, 1964), which has been used extensively in Europe. Semi-quantitative scales remain the mainstay of terrestrial vegetational surveys. For example, the Domin scale of cover and abundance (Dahl and Hadac, 1941) remains at the heart of the UK's National Vegetation Survey (Rodwell et al., 2006).
Fischer-Piette (1936), an early pioneer of semi-quantitative scales, used a selection of similar scales to assess the biogeographic range of intertidal organisms. Southward and Crisp (1954) initially developed a log-base abundance scale for rapidly assessing marine communities at a varied of geographic locations. It is likely that this later developed, by Crisp and Southward (1958), into the ACFOR scales ('Abundant Common Frequent Occasional and Rare' - which also included a 'Not Found' class), which was used extensively for mapping the geographical distribution of marine species around British and European Coasts (pers. comm. S.J.Hawkins following discussions with both Crisp and Southward). The ACFOR scale was subsequently used for other studies of vertical and horizontal patterns (Nelson-Smith, 1967) and biologically-derived wave exposure scales (Ballantine, 1961) on rocky shores. More recently, the ACFOR scale was again adopted to resurvey sites assessed in the 1950s using ACFOR under the MARCLIM (Herbert et al., 2003, 2007; Simkanin et al., 2005; and specifically Mieszkowska et al., 2006a, 2006b). Hawkins and Jones (1992) provide a table that illustrates the relationship between ACFOR and abundance scales with as many as eight categories. They lament the fact that adding more categories spoil the semi-logarithmic progression of the original scales and may create an impression of spurious accuracy.
The ACFOR scales were ultimately used as the basis for the SACFOR (Superabundant, Abundant, Common, Frequent, Occasional and Rare) abundance scales – a system developed to support the Marine Nature Conservation Review (Hiscock, 1990) in its aim to survey and describe the marine habitats, communities and species around Great Britain. The SACFOR scale was originally developed as a standardised, semi-quantitative, methodology for experienced biologists undertaking roving surveying techniques such as diving, rapid intertidal surveys and subtidal video collection (Hiscock, 1998). The SACFOR scale records species in terms of percentage cover or counts (Table 1). The assessment based on cover is modified according to the growth form of the species (i.e. 'crust/meadow' or 'massive/turf') and the counts scale is modified by body size (< 1 cm; 1–3 cm; 5–15 cm; > 15 cm). The counts and cover scales use the same six classes, namely 'Superabundant', 'Abundant', 'Common', 'Frequent', 'Occasional', 'Rare', and 'Less than rare'.
Table 1 The SACFOR abundance scales for cover and counts observations (Hiscock, 1990). SACFOR codes are: S Superabundant, A Abundant, C Common, F Frequent, O Occasional, R Rare, and L Less than rare indicated by extrapolation (which is no longer used in the modern SACFOR scale)
The cover classes are separated by a base-2 logarithmic scale, i.e. the cover doubles between increasing classes. The counts codes are on a base-10 logarithmic scale, i.e. density changes 10-fold between classes. The growth form and body size 'block-shift' the appropriate SACFOR scale class for a particular growth form or body size. For example, large solitary ascidians are likely to fall into the 3–15 cm high category. For such species, a density of 1–9 per 100 m2 would be classed as 'Occasional', while species over 15 cm high, such as a large anemone, occurring at this density would be classified as 'Frequent'. Example body size classes and growth forms for common British marine species are provided, with the SACFOR scale, in Table 1. Logarithms are commonly applied to raw, quantitative data to reduce the signal-to-noise ratio or to balance the influence of differences in relative abundance in some approaches – this process also reduces the numerical range of the data in a manner comparable to those used in many semi-quantitative scales. Raw, continuous data can be summed, divided and multiplied before having a logarithm applied. Furthermore, raw data that is log transformed is still continuous data. Scales, such as SACFOR, also have a greatly reduced range but cannot be initially changed through basic arithmetic operations.
The SACFOR scale has also beenused to define the representative communities for the biotopes listed in the UK's Marine Habitat Classification for Britain and Ireland (JNCC, 2015). As such, the SACFOR scale is now firmly established in the UK, being routinely used for undergraduate teaching (Hawkins and Jones, 1992; Gray and Elliott, 2009; Wheater et al., 2011) with the majority of the surveys relying on roving or remotely collected survey techniques. As of March 2017, a national database of marine survey data (UK Marine Recorder 'snap-shot' available from the Joint Nature Conservation CommitteeFootnote 1) listed 1874 surveys using the SACFOR scale, which has collectively generated well over 1 million SACFOR observations in this database alone.
Although widely used in the UK, the SACFOR scale has several advantages as well as some acknowledged limitations associated with both data collection and analysis. The advantages of SACFOR include:
the rapid assessment of relative community composition, especially across expansive or rugose environments that may not be compatible with the use of more time-consuming or focused methods such as quadrats.
The simultaneous assessment of species enumerated as either cover or density (counts) using the same set of scales.
As semi-quantitative scales can be applied to larger areas, they are better suited for the detection of rare species that might over wise not be detected by less extensive methods.
The SACFOR scale can be used without additional equipment, hence making it a suitable method for diver-based seabed surveys.
Although the broad cover and count classes lack precision, their breadth ensures a high level of accuracy and repeatability between users – this design feature underpins its consistent application between users and across a variety of habitats.
These benefits confirm obvious and understandable limitations associated with the collection and processing of SACFOR data, which include:
Although supported by quantitative thresholds, SACFOR classifications are often applied in a subjective manner leading to intra and inter-observer variability over space and time - this can be reduced substantially with experience, training and predefined field methods.
The incremental changes between classes are large. Although the semi-logarithmetic progression of the classes is large, the size of the increments was carefully considered to reflect the natural abundance patterns of species, and thereby aid the survey in rapidly recording and reflecting the abundance patterns present (Hawkins and Jones, 1992), i.e. the development of the ACFOR scale (Crisp and Southward, 1958), which may have built on the earlier work of Fischer-Piette (1936) and Preston (1948).
Encoded SACFOR classes cannot easily be assessed directly with quantitative statistical methods, although many sophisticated statistical assessments can be undertaken on ordinal data.
Converting SACFOR codes into a corresponding number within the class value range still does not render the entire observation suitable for quantitative analysis – this is due to the presence of 'count' and 'cover' assessments within the same set of observations that operate over different value ranges. For example, counts range from 0 to abundances in excess of 1000,000 (increasing on a base 10 logarithmic scale), whereas cover ranges from 0 to approximately 100 (increasing on a base 2 logarithmic scale). Direct conversion of mixed count and cover classes to numbers within the same sample will therefore lead to species assessed with counts to dominate the variance within the data. However, if one choses to accept that SACFOR cover and count classes are broadly aligned, it is possible to merge these observations into one ordinal outputs – this approach is the basis of the conversion process below.
Due to the inadmissibility of ordinal data for arithmetic operations, many common statistical operations are not suitable for ordinal data sets (Podani, 2006). As such, most SACFOR datasets are typically used once for descriptive purposes only (e.g. habitat classification). Hoever, some statistical methods are compatible for the analysis of ordinal data and include Mann-Whitney U tests (for comparisons differences between two independent groups) and Kruskal–Wallis H test (for comparisons between two or more independent groups). Multivariate techniques are less prevalent but include clustering methods (e.g. Ordinal Cluster Analysis described by Podani, 2006), non-metric multidimensional scaling (Digby and Kempton, 1987) and any tests allowing the similarity of objects to be based on rank values only (e.g. rank correlation, Legendre and Legendre, 2012). However, the conversion of ordinal data into continuous data, as provided by the SACFOR scale table, would greatly improve the availability of tests.
The SACFOR scale has now been in use for over 27 years and has generated a substantial quantity of observations – if the processing limitations can be overcome, this information could be suitable for other forms of analysis. This study describes a process for converting SACFOR encoded information into an ordinal scale that can be used in statistical analysis (i.e. ordinal values indicate an order or ranking between categories, but the actual distance between these orderings does not have any meaning). The conversion process (i) can combine SACFOR counts and cover information within one, data set, (ii) supports the merging of species (counts or cover) or observations during the production of the aligned data set, and (iii) allows a wide selection of quantitative statistics to be applied to the aligned data set, e.g. descriptive statistics, hypothesis testing, and multivariate analysis. A simulation study has been included to validate the conversion process and confirm the fidelity of the data during processing. The conversion has also been applied to a typical SACFOR data set to demonstrate some of the statistical methods that can be applied. SACFOR was originally designed for rapid biogeographic surveys and has been widely used since for a variety of purposes over many decades of a wide variety of marine habitats; we propose a conversion process that provides a route for exploiting this wealth of data for a wider range of analyses.
It is acknowledged that data analysts regularly replace categorical and ordinal names and numbers with appropriate numbers to facilitate analysis. The value of these substitution techniques is that they are consistently applied to the same scale across studies to allow comparisons to be made. Despite the vast amount of SACFOR data available, there are no peer-reviewed published studies that have numerically converted this data for reuse (although see Burrows et al. (2008) for an example of the use of SACFOR data in an unconverted format). This study hope to highlight the subtle yet important changes that can occur within the converted dataset that can occur in what seems to be a deceptively simple process but is significantly complicated by body size and the combination of counts and cover observations. This study also hopes to provide a standardised approach for the conversion of SACFOR data that can be accessed by other scientists, thereby allowing the consistent conversion and analysis of this valuable data set between studies.
The specific objectives of this analysis are:
To present a conversion process that translates SACFOR codes into numerical values, which allows observations to be merged (counts with other count data and cover with other cover data only).
To assess the fidelity of conversion for SACFOR count codes converted to values.
To assess the fidelity of conversion for SACFOR cover codes converted to values.
Validate the alignment of converted cover and counts observations within a single, ordinal data set.
Present a validated conversion pathway for SACFOR information and recommend statistical analyses that are suitable for converted and aligned data sets.
The first section describes the development of the conversion process. The second section details the final process used to convert SACFOR classes (counts and cover) into an aligned, numerical dataset. The third section describes the simulation tests (random data) and case study (real data) used to validate the conversion process.
Development of the conversion process
The desired attributes for the conversion process were as follows:
The conversion merges the observations, based on counts and cover, into one, unified community matrix;
The influence of body size and growth form are removed from the data set so that changes in absolute abundance (as measured as counts or cover) is the only factor generating change in the data set;
Where possible, as much relative information between classes should be maintained in the final matrix;
The final expression of the counts and cover observations must be on the same value range; and
Converted values are distributed in a similar pattern across the value range regardless of source (counts or cover).
Attributes 4 and 5 were considered particularly important to prevent the type of observation (counts or cover) weighting or biasing the final matrix i.e., the larger value range for species assessed with the counts scale translates to a greater influence within the community matrix when examined with univariate and multivariate statistical analyses. Without alignment, the results from these analyses will, in part, be driven by changes in the proportion of species assessed with either the counts or cover scales rather than underlying changes in abundance. As such, it was necessary to fit both counts and cover observations onto the same value range.
The primary requirement to prevent artefacts appearing in the unified community matrix required that most of the relative information between classes was removed, thereby compromising point 4. As the SACFOR count scale has increments based on a power of 10 but the cover scale is based on a power of 2, it was not possible to maintain this relative information without introducing artefacts into the community matrix (and compromising point 6). During the development of the conversion process, several other methods were examined – these included:
Processes that used body size to estimate the area occupied by individuals and thereby derive cover for taxa enumerated with the counts scale. This system allowed us to understand the relationships between abundance and cover for different body sizes. However, the resulting value range for cover values converted using body size and counts, was very different to the existing cover value range. Attempts to align the existing cover values with them compromised the counts data. The conversion process posited here conversely aligns cover data to values derived from the counts scale.
Processes that retained the power of 10 and 2 increments for the counts and cover data respectively. However, attempts to keep the relative information for the counts and cover classes within one value range resulted in count data over-powering the variance within the unified data set. As stated earlier, discrepancies in the final representation of counts and cover observations in the community matrix compromised subsequent analyses, i.e. differences between communities could be driven simply by the ratio of counts and cover observations in within a data set.
Standardized conversions that attempted to align counts and cover yet maintain the different relative step changes for counts and cover were all unable to prevent significant artefacts appearing in the final community matrix.
Ultimately, the objective for the conversion process is to allow some basic statistical analysis of count and cover data merged into one data set. As such, the conversion process selected for use here removes the majority of the relative information and aligns the count and cover observations within an unified, ordinal value range. Based on the incompatibility of the original units used for cover and counts (i.e. density verses percentages), it is not possible to merge the two types of data into a completely ordered set. However, if the ordering of merged count and cover observations purely relies on the merging of information at the categorical level (i.e. 'Common' refers to the same level of abundance regardless of whether it is derived from counts or cover) information, then the creation of a totally ordered set it possible. It is acknowledged that this represents a significant simplification of the data. However, the benefit of being able to perform statistical analyses on a larger, unified dataset representing the entire community, potentially outweighs the loss of information inherent in the original cover and counts units. This conversion meets all but one (point 4) of the desired attributes, and provides a reliable and unified community matrix for subsequent analysis. Certain statistical limitations are imposed through the use of ordinal data – these are described in more detail in the discussion. Alternative methods were examined that convert cover to counts based on the average body size (and areal footprint estimated) of 'cover' species. Unfortunately, the body size/areal footprint was not available for all of the species assessed using cover, hence it could not be implemented here. The authors are continuing to collate information on body size in the hope that it can be incorporated into a more robust merging of cover and counts in future iterations of this process.
Process for the numerical conversion of SACFOR data
Step 1) Attribution of observations with species body size (counts) and growth form (cover)
Each species observation must be attributed according to whether it has been assessed according to cover or counts. Species encoded with the counts scale must be attributed according to the body size scale used. Species using the cover scale must also be attributed according to the growth form scale used. The growth form and body size information is usually provided as survey metadata or can be estimated using biological information from online sources e.g. BIOTIC - Biological Traits Information Catalogue.Footnote 2 An overview of the conversion process is provided in Fig. 1.
Step 2) Numeric conversion of counts and cover
Workflow for the conversion of SACFOR classes via numerical values, into ordinal data that aligns count and cover observations
The conversion values for the counts are based on the lowest possible density for each class. A constant of 0.1 was added to each conversion value to ensure that all of the values can be log transformed correctly (i.e. to avoid the log transformation of 1 returning 0) – the resulting values are the 'numerical conversion values for counts'. The lowest possible density was selected to numerically represent each class because the mid and upper values cannot be defined for the superabundance class of any size class. The numerical conversion values for the cover classes are based on the conversion value for count classes. To derive the conversion values for the cover classes, the numerical conversion values for the counts were log transformed (base 10) before being antilog transformed (base 2). All of the final conversion values for counts and cover are shown in Table 2.
Table 2 Numerical conversion values for SACFOR cover and counts classes. SACFOR classes are S Superabundant, A Abundant, C Common, F Frequent, O Occasional, R Rare; and L Less than rare indicated by extrapolation (which is no longer used in the modern SACFOR scale)
To convert SACFOR counts information, each class should be substituted with the corresponding 'numerical conversion values for counts' - each body size has a specific set of numerical conversion values (Table 2). To covert SACFOR cover information, each class should be substituted with the corresponding 'numerical conversion values for cover' - once again, each growth form has a specific set of numerical conversion values for cover (Table 2). These conversion values should not be interpreted as abundances or cover values - they are conversion numbers that will align with the converted cover and count values onto an ordinal scale after transformation (step 3).
Step 3) Alignment of the numerically converted counts and cover through transformation
The final step aligns the numerical count and cover values along an ordinal value range. To achieve this, the conversion values for counts are log transformed (base 10). The conversion values for the cover information are log transformed (base 2). This step unifies the count and cover information within a single range of values, i.e. the transformed value for a species assessed as 'Common' using counts is the same as another species assessed as 'Common' using cover. The final values are: (i) adjusted to remove the influence of body size and growth form; (ii) merged with similar taxonomic/morphological entries when required; (iii) numerically aligned to prevent offsets between those measured with counts and those as a cover; and (iv) log transformed (appropriate for observations spanning multiple orders of magnitude). As mentioned earlier, it was not possible to maintain the relative information separating classes – as such, the aligned values are ordinal in nature.
Validation of the process for the conversion of SACFOR data
Simulations using randomly generated data were used to test the fidelity of the conversion process. In addition, a case study converted real SACFOR data to demonstrate the validated conversion process and the potential analyses that can be applied. The three simulations and the case study used R (R Core Team, 2013) - the scripts are available within the supplementary information. The linkages between the simulations are shown in Fig. 2. The simulation and demonstration steps are:
Simulation 1 - assess the fidelity of the conversion of a random count-based SACFOR data set into numerical values and comparison with a basic rank value conversion;
Simulation 2 - assess the fidelity of the conversion of a random cover-based SACFOR data set into numerical values and comparison with a basic rank value conversion;
Simulation 3 - assess the alignment of numerical count and cover values within an unified ordinal data set; and
Case study 1 - demonstrate the conversion of a real data set, containing both count and cover observations, as well as some standard statistics for the detection of changes between sites
A flow diagram of the three simulations used to test the SACFOR conversion process
Simulation 1: comparison between random counts values with numerically converted and transformed count values.
Hypothesis: there is no appreciable difference between randomly generated count data and the numerically converted, log10 transformed, counts data.
A random set of count data was generated using R. The 'rnorm' function in R generated random values using a multivariate lognormal distribution (mean = 0, variance = 2). The random count data set was designed to reflect a typical SACFOR data set. The Marine Recorder database contains the majority of the UK's SACFOR surveys. Microsoft Access was used to establish the average number of observations collected by a survey using SACFOR (a mean of 560 observations based on 1874 surveys) and the average number of species encoded within a survey (a mean of 119 species based on 1874 surveys). The data frame dimensions were therefore 119 species variables (columns) and 560 observations (rows). The L code (Less than rare indicated by extrapolation) was not used as it not included in the vast majority of marine data sets.
The random count observations were then classified into SACFOR classes using the standard SACFOR thresholds provided in Table 1 (based on a body size of 1–3 cm). The SACFOR classes were then substituted with the 'numerical conversion values for counts' appropriate for each SACFOR class (Table 2). As a comparison, SACFOR values were also substituted with their ranked values, i.e. S = 6, A = 5, C = 4, F = 3, O = 2, R = 1, absent = 0. Finally, the random count data set and numerically converted count data set were both log transformed (based 10). Tests conducted on the two data sets were correlation between paired samples using Spearman rank rho. PERMANOVA, using default options in the ADONIS function in the 'vegan' R package, was used on both the numerical conversion values and the rank value substitutions. Simulation 1 was repeated ten times and the mean of each statistic was reported with the standard deviation.
Simulation 2: comparison between random cover values with numerically converted and transformed count values.
Hypothesis: there is no appreciable difference between randomly generated cover data and the numerically converted, log2 transformed, cover data.
A random cover data set was generated using R. For each observations, a random species is selected and given a random cover value from between 0 and 100. A loop is used to: (i) then calculate the remaining area; (ii) randomly select a species not already allocated a cover value; and (iii) randomly allocate a cover value within the remaining range of available cover – this continues until there is no remaining cover within an observations. Once again, the 'less than rare indicated by extrapolation' L code was not used.
The data frame dimensions were 119 species variables (columns) and 560 observations (rows). The random cover observations were then classified into SACFOR classes using the standard SACFOR thresholds provided in Table 1. The SACFOR classes were then substituted with the 'numerical conversion values for cover' appropriate for each class (Table 2). As a comparison, SACFOR values were also substituted with their ranked values, i.e. S = 6, A = 5, C = 4, F = 3, O = 2, R = 1, absent = 0. Finally, both the random cover values and the numerically converted cover values were log2 transformed. Tests conducted on the two data sets were correlation between paired samples using Spearman rank rho and PERMANOVA, using default options in the ADONIS function in the 'vegan' R package, was used on both the numerical conversion values and the rank value substitutions. Simulation 2 was repeated ten times and the mean of each statistic was reported with the standard deviation.
Simulation 3: assessment of the alignment of cover and counts values on an ordinal scale following the numerical conversion and transformation process.
Hypothesis: for a randomly generated data set of SACFOR classes, there is no appreciable difference between the final ordinal values regardless of whether the counts or cover conversion processing route is followed.
The SACFOR scale for count-based scale is structured on base 10 increments. The SACFOR cover scale has base 2 increments. Real SACFOR data is always a mix of both count and cover observations. A primary objective of the numerical conversion process is that the conversion should result in the same transformed value for each class, regardless of whether it was recorded as cover or counts, i.e. an 'Abundant' count should have the same value as an 'Abundant' cover after transformation. Simulation 3 used the SACFOR classes generated from the randomly generated counts (Simulation 1). These classes were then converted with the cover conversion process. The converted counts values from the counts conversion route (simulation 1) and counts values from the cover conversion route (simulation 3) were compared statistically with PERMANOVA (relative abundances and using default adonis options). Simulation 3 was iterated ten times and the mean of each statistic was reported with a standard deviation. It was not necessary to run Simulation 3 to confirm that the rank value substitution method would align counts and cover observations.
Case study 1: community comparison between two sublittoral rock sites using real SACFOR data (containing a mix of both count and cover values) after applying the conversion and transformation process.
Hypothesis: a significant community different is apparent between two sublittoral sites and this can be detected following the conversion and transformation of SACFOR classes.
SACFOR data for two sublittoral rock outcrops (East of Haig Fras SAC and Wyville Thomson Ridge SAC - Table 3) were extracted from Marine Recorder.Footnote 3 SACFOR observations were obtained from drop-down camera observations (comparable equipment used on both surveys). Both sites are in UK waters and contain sublittoral rock substrata dominated by epifaunal species. Survey data from both sites were merged into one species matrix. Different taxonomic levels and labels had been used for many of the species and groups. After numerical conversion, taxa were merged into a higher, unifying taxonomic identifiers, e.g. records for (i) Caryophyllia smithii (ii) Caryophyllia sp., and (iii) Caryophyllia, were merged into 'Caryophyllia' to improve the consistency between sites for these species. Taxonomic entries higher than a family were removed from the matrix, e.g. porifera.
Table 3 Data source and composition for the two sites containing sublittoral rock
The SACFOR classes were converted numerically using the numerical conversion values for counts and cover. Log transformed using base 10 and base 2 were used to align the counts and cover data sets respectively. Multivariate statistics suitable for ordinal data was used to test for (i) differences between the communities at the two sites using PERMANOVA (relative abundance and using default adonis options) and (ii) the influence of environmental variables on the communities using Correspondence Analysis and Redundancy Analysis (vegan package) in R. Although initially controversial (Sullivan & Artino, 2013), it is now accepted that both parametric (requiring an adequate sample size and data that are normally distributed) and non-parametric tests are appropriate for the analysis of ordinal (i.e. Likert scales) data dependent variables (Norman, 2010). Descriptive statistics should use the median as a measure of central tendency rather than means (Jamieson, 2004).
Simulation 1: the fidelity of the conversion process for SACFOR count classes converted to numerical values
Simulation 1 generates a random counts dataset, encodes using the SACFOR scale, and then applies the numerical conversion process to these codes. For a comparison, a basic ranked value has also been used to substitute the SACFOR codes. Statistical testing was used subsequently to detect relative changes between: (i) the original random dataset (log transformed) and the converted values (log transformed); and (ii) the original random dataset (log transformed) and the ranked values.
There was a significant difference between the transformed (mean) abundance before the conversion process and the numerical values used to represent abundance after conversion (Table 4 and Fig. 3). This difference was also apparent for the rank value substitution. The numerical value is substantially smaller than the original abundance. However, the conversion process, and the numerical conversion values used, are not designed to provide an absolute match with the abundances but rather to capture the relative differences between classes. As such, both the descriptive statistics indicate a substantial difference (also tested with a Wilcoxon rank sum test but not shown).
Table 4 Descriptive statistics and correlation coefficients for randomly generated count data sets (i) before and (ii) after the SACFOR encoding and numeric conversion. Both before and after data sets are transformed (log10). Values are based on 10 iterations of the simulation
Converted counts for random counts (log10 transformed) against SACFOR converted counts (log10 transformed). The fitted line was obtained from linear regression.Example from a single iteration of simulation 1 (run 1)
The Spearman rank test has been included to examine maintenance of relative sorting before and after the conversion process. This indicates that the majority of the relative order has been maintained during the conversion process. The process of classifying the abundance using SACFOR removes a large amount of quantitative information (i.e. the full value range is reduced to just six classes). This simplification of the data is highlighted by the increase in tied values post-conversion. Tied values disrupt the ranking process and may explain some of the decline in rho statistic from an ideal value of 1.
Analysis using PERMANOVA found that there was a significant difference between the numerically converted data set and the original as well as between the ranked values and the original dataset (Table 5). Multidimensional scaling plots for the raw, converted count observations and rank value substitution are provided in Fig. 4. Comparisons of the transformed data sets (the final product of the conversion process) generates no patterns to artefact structures within the plots, suggesting that the entire conversion process does not impart any structure or artefacts within the data. Equally no artefacts were observed in the MDS plot for the rank value substitution (Fig. 4c).
Table 5 PERMANOVA comparison of randomly generated count data sets (i) before and (ii) after the SACFOR encoding and numeric conversion. Both before and after data sets are transformed (log10) before analysis and converted to: (i) relative abundances; and (ii) rank of abundances. Values are based on 10 iterations of the simulation. Number of permutations: 999
a, b, and c Multidimensional scaling plot of transformed (log10 transformed) raw counts (left), transformed (log base 10 transformed) converted counts (middle) and the rank value substitutions (right). Example from a single iteration of simulation 1 (run 1)
Simulation 2: comparison between random (raw) cover values and converted SACFOR cover values
Simulation 2 generates a random cover dataset, encodes using the SACFOR scale, and then applies the conversion process to these codes. Statistical testing was subsequently used to detect relative changes between the original raw dataset and the converted values. The descriptive statistics indicated significant differences between the raw (random) and converted cover values for the converted/numerical values (Fig. 5) but not for the number species (Table 6). Once again, it is expected that the pre-conversion 'cover' and post-conversion 'numerical conversion value' does not match - the conversion process, and the numerical conversion values used, are not designed to provide an absolute match with the abundances but rather to capture the relative differences between classes. Despite a change in the absolute values, the relative ordering of the observations appears, as captured by the Spearman rank tests, are similar before and after the conversion process. Any changes in the ordering may be related to the increase in frequency of tied values following the encoding of values with the SACFOR scale (paired cover values increases from 2.6 to 19.2% during the encoding phase.
Converted counts for random cover (log10 transformed) against SACFOR converted cover (log2 transformed). The fitted line was obtained from linear regression. Example from a single iteration of simulation 1 (run 1)
Table 6 Descriptive statistics and correlation coefficients for randomly generated cover data sets (i) before and (ii) after the SACFOR encoding and numeric conversion. Both before and after data sets are transformed (log2) and converted to relative abundances. Values are based on 10 iterations of the simulation
Analysis using PERMANOVA found that there was a significant difference between the numerically converted data set and the original as well as between the ranked values and the original dataset (Table 7). Multidimensional scaling plots for the raw, numerically converted cover and the rank value substitutions observations (both untransformed and transformed) are provided in Fig. 6. The figures are all similar and plot the observations in a loose circle. This structure is similar both before (Fig. 6) and after numerical conversion and transformation (Fig. 6b) as well as in the plot for the rank value substation (Fig. 6c).
a, b, and c Multidimensional scaling plot of transformed (log2 transformed) raw cover (left), transformed (log base 2 transformed) converted cover (middle) and the rank value substitutions (right). Example from a single iteration of simulation 1 (run 1)
Table 7 PERMANOVA comparison of randomly generated cover data sets (i) before and (ii) after the SACFOR encoding and numeric conversion. Both before and after data sets are transformed (log2) before analysis and converted to: (i) relative abundances; and (ii) rank of abundances. Values are based on 10 iterations of the simulation. Number of permutations: 999
Simulation 3: confirmation of the alignment of cover values and counts after transformation
Simulation 3 converted randomly generated SACFOR class (letters not values) data sets (10 iterations) using both the cover and then counts conversion processes. The converted data sets from both processes were then compared statistically, using PERMANOVA, to confirm the similarity, and hence alignment, of the cover and counts conversion processes. The small F statistic and a p value greater than 0.05 suggest that the transformed values produced by the cover and counts conversion processes are the same (Table 8).
Table 8 PERMANOVA comparison of randomly generated SACFOR cover classes converted using (i) the counts conversion and transformation (log10) process and (ii) the cover conversion and transformation (log2) process and converted to relative abundances. Values are based on 10 iterations of the simulation. Number of permutations: 999
Case study: detection of difference between two sites, within a real SACFOR dataset, containing a mix of both count and cover values (transformed), after conversion
The case study is based on two real SACFOR surveys (both containing a typical mixture of cover and count observations, as well as a range of body sizes and growth forms). The conversion processes have been applied to both surveys to demonstrate its application for real data and that a typical suite of statistical tests can be applied.
Species richness was similar between sites (Table 9). The F and p values returned by the PERMANOVA indicate a large and significant difference between the relative abundances of the epifaunal communities at the two sites (Table 10). This difference is apparent as a low level of overlap between the site point clouds displayed in the Multi-dimensional plot below (Fig. 7). Correspondence analysis has been used to highlight environmental variables that co-vary with the epifaunal community. The suite of environmental variables included did not explain much of the variance (inertia) present in the epifaunal data (Table 11). Co-varying environmental variables include depth, mud/boulder content and surface rugosity (Fig. 8).
Table 9 Descriptive statistics for East of Haig Fras and Wyville Thompson Ridge SACFOR epifaunal data (relative abundance) following SACFOR conversion and log transformation
Table 10 PERMANOVA comparison of SACFOR epifaunal data (relative abundance) from: (i) East of Haig Fras; and (ii) Wyville Thompson Ridge, following SACFOR conversion and transformation. Number of permutations: 999
Multi-dimensional scaling plot of observations from East of Haig Fras (circles) and Wyville Thompson Ridge (triangles)
Table 11 Correspondence analysis of SACFOR epifaunal data (relative abundance) from East of Haig Fras and Wyville Thompson Ridge with depth, seabed rugosity, seabed aspect, seabed curvature and substrata (mud, sand, boulder and bedrock)
A plot of the correspondence analysis for observations from East of Haig Fras and Wyville Thompson Ridge with vectors showing the relative trajectory and importance of the environmental variables (the site factor is shown as 'X'). Labels are rug = rugosity, asp = aspect, cur = curvature, bou = boulder and bed = bedrock)
The SACFOR conversion process advocated here allows: (i) the merging of taxa within counts or cover data sub-sets; (ii) observations, based on either counts and cover, to be unified into one matrix; (iii) counts and cover data to have an equal weighting in the final matrix; and (iv) the removal of the influence of body size and growth form from the final values. To achieve this, it is only possible to preserve the ordinal structure of the data set i.e., while the order of the variable has been retained, the spacing of the original classes (base 2 for cover and base 10 for counts) variable has been removed. At no point within the conversion process do the numerical values attempt to correspond to the cover or abundance values presented by the SACFOR scale. Once transformed, the relative differences between classes for counts and cover are effectively lost. If it is more important for the user to analyse relative change, it is advised that step 3 (transformation) is not undertaken and the counts and cover observations are not merged but analysed separately. Equally, it is likely that comparisons made within SACFOR data are likely to be more powerful when factors that introduce variance, such data sets containing both cover and counts or those comprising multiple body sizes, are minimised. It is likely that more power might be obtained by extracting and using data sets confined to a single growth form.
Simulations 1 and 2 verified that the SACFOR conversion process can convert random cover and counts data to numerical values (allowing the merging of taxa) and then to transformed values whilst maintaining the majority of the ordinal structure. A small loss of relative sorting associated with simulations 1 and 2 were associated with paired values, which themselves are a product of the full value range present in the random data sets being reduced to 7 classes during the SACFOR encoding phase i.e., a step within the data collection phased and not the numerical conversion process itself. The agreement between the scale classes and the numerical equivalents is an obvious reflection of the careful structuring and design of the SACFOR, and also its precursor, the ACFOR scale. Interestingly, a similar result was obtained by simply substituting SACFOR codes with a rank value. Despite this, the numerical conversion provides two important advantages of the rank value substitution method. These advantages are firstly the ability to merge observations together because the numerical conversion process as an intermediate step that approximates the absolute abundance values (i.e. the ability to merge taxa into higher taxonomic levels) and secondly the ability to incorporate quantitative observations with the converted SACFOR observations. The latter step is also possible, in a coarser manner, with the rank value substitution method. Simulation 3 confirmed that the numerical alignment of abundance values regardless of whether it was recorded as a cover or count, and also means that data sets containing both types of information can be safely analysed as one combined package of observations. Clearly the use of the same rank value scale for counts and cover will also allow the alignment of the two different abundance types.
A case study has been presented that uses real SACFOR observations, i.e. a matrix including species encoded according to counts (multiple body sizes) and cover (both growth forms). The real SACFOR observations within the case study were converted and presented as one species matrix. Common tests, such as PERMANOVA and Canonical correspondence analysis, were used to demonstrate that the converted data are compatible with statistical analyses routinely used in ecological assessments. Indeed, it is recognised that semi-quantitative data such as SACFOR are compatible with a broad suite of non-parametric statistical methods including simple (e.g. difference tests, correlation and concordance, and ANOVA analogues) and complex (multidimensional scaling and Permanova) techniques (Legendre & Legendre, 2012). Most non-parametric tests are as powerful as their parametric equivalents, and if there is any doubt about equality of variances or divergence from normal distributions, then this small advantage provided by parametric approaches breaks down quickly (Field et al., 2012).
If the objective of the analysis is to assess the response of the whole community in relation to treatments or environmental variables, multivariate approaches (e.g. the mvabund package by Wang et al., 2012) provide an alternative to the conversion process suggested here. For example, the mvabund package (Wang et al., 2012) fits individual generalised linear models to species in a multispecies data set but summarise the models collectively to make conclusions on the influence of treatments and variables. The benefit of this approach is that each model can be based on differing scales and units of 'abundance' for each species, hence allowing the simultaneous utilisation of cover and counts class data sets without an initial merging step (as required in the process proposed here).
In order to better reflect reality it may be necessary to refine the method used in this study for each particular situation. It is acknowledged that the method to generate the random data set used in the simulations assumes that the distribution of abundance for each species is both identical and independent of all other species. However, actual marine communities have relatively few common species and a higher proportion of rare species, leading to a species abundance distribution following a lognormal distribution (Connolly et al., 2014). Equally, biotic processes can be linked to the abundance of co-occurring species thereby tempering the assumption of independence used here. Inclusion of a log normal function to better structure the random abundances between species could provide a more realistic representation of a typical marine community. Furthermore, the use of a more realistic community structure, through the inclusion of a log normal distribution across the simulated species, could highlight other characteristics intrinsic to the SACFOR scale, such as how important levels of information are captured between common and rare species at the point of classification.
Much of the variance within the biological data could not be explained by the environmental data - it is possible that aspects of the SACFOR coding (reducing abundance to a seven-point scale), taxonomic aggregation and possible variations in the survey design, apparatus or conditions experienced (e.g. visibility) between sites and stations introduced variation that obfuscates the environmental variables included in the analysis. Categorical data of species abundance has also been used to produce species distribution models, e.g. Mieszkowska et al. (2013) use of ACFOR observations to produce predicted species distributions for the trochid gastropods Phorcus lineatus and Gibbula umbilicalis at several points in time.
The SACFOR scale purposely lacks precision in order to provide accuracy for rapid surveys where species identification, access and time are issues. It is also better suited when the investigator is more interested in documenting rarer species (i.e. inventory surveys) rather than the quantitative analysis of commoner species, which is often conducted with quadrats through a stratified random approach, but more likely to miss rarer species unless heavily replicated. Eleftheriou & McIntyre (2005) suggest that SACFOR is inappropriate as a tool for monitoring as it is not sufficiently quantitative. However, we suggest that SACFOR data, that includes information on multiple taxa, in well replicated surveys from large areas of marine habitat, provides sufficient power that these data sets should be considered useful for monitoring studies in areas lacking quantitative observations. Despite this, the conversion of data generated from descriptive to analysable ordinal scales does not improve its precision, and its accuracy remains the same. Bearing this in mind we suggest that anyone adopting our methodology (or similar) should resist the temptation to over-analyse the data that it makes available and be mindful of the inherent limitations of the underlying data collection methodology. Indeed, as most marine ecological data collection techniques are only semi-quantitative, we should be ever mindful of the limitations of all data collected and wary of attributing unjustifiable accuracy when interpreting imprecise data.
It is hoped that the SACFOR conversion process proposed here facilitates: (i) the quantitative re-analysis of the burgeoning SACFOR data repository; and (ii) initiates a debate on alternative methods for the conversion of SACFOR data into analysable end products. The repository of existing SACFOR observations is vast and generally under-utilised. Equally, this repository contains repeated observations for several locations and an extensive array of habitat types and geographic locations. It is hoped that the conversion of historical SACFOR data into a format available for statistical analysis opens up a plethora of new re-analysis possibilities including temporal analysis, broad-scale spatial analysis as well as modelling and regression analyses. The objectives and content of this paper are simple and intuitive, i.e. that ordinal data can be substituted with numerical values. It is hoped that this study highlights the basic operations required to access and analyse a wealth of biological information that has accumulated over 27 years of survey work. The conversion presented here, if repeated, also provided consistent and objective conversion of SACFOR data, thereby allowing comparisons between studies and over time.
Please contact author for access to R scripts and the data used in the analysis derived from Marine Recorder.
http://jncc.defra.gov.uk/page-1599
http://www.marlin.ac.uk/biotic/
Arnaud PM, Galeron J, Arntz W, Petersen GH. Semi-quantitative study of macrobenthic assemblages on the Weddell Sea shelf and slope using trawl catch subsamples. In: Arntz W, Ernst W, Hempel I, editors. The expedition ANTARKTIS VII/4 (EPOS leg 3) and VII/5 of RV Polarstern in 1989, Ber Polarforsch, vol. 68; 1990. p. 98–104.
Ballantine WJ. A biologically-defined exposure scale for the comparative description of rocky shores; 1961. p. 1–19.
Braun-Blanquet J. Plant Socoilogy. Mcgraw-Hill book company, Inc; New York; London; 1932.
Braun-Blanquet J. Pflanzensociologie: Grundzüge der Vegetationskunde. 3rd ed. Springer Verlag: Vienna; 1964.
Burrows MT, Harvey R, Robb L. Wave exposure indices from digital coastlines and the prediction of rocky shore community structure. Marine Ecology Progress Series. 2008;353:1–12.
Connolly SR, MacNeil MA, Caley MJ, Knowlton N, Cripps E, Hisano M, Thibaut LM, Bhattacharya BD, Benedetti-Cecchi L, Brainard RE, Brandt A. Commonness and rarity in the marine biosphere. Proc Natl Acad Sci. 2014;111:8524–9.
Crisp DJ, Southward AJ. The distribution of intertidal organisms along the coasts of the English Channel. J Mar Biol Assoc U K. 1958;37(1):157–203.
Dahl E, Hadac E. Strandgesellschaften der Insel Ostøy im Oslofjord. Eine pflanzensoziologische studie. Nytt Magasin for Naturvidenskapene B. 1941;82:251–312.
Digby PGN, Kempton RA. Multivariate analysis of ecological communities. London: Chapman and Hall; 1987.
Eleftheriou A, McIntyre A. Methods for the study of marine benthos: Blackwell Publishing; 2005.
Fischer-Piette J (1936) Etudes sur la biogeographie intercotidale des deux rives de La Manche, J. Linnean Society (Zoology), XL: 181-272.
Field A, Miles J, Field Z. Discovering statistics using R: Sage, London; 2012. p. 958.
Gray, J.S. & Elliott, M. (2009) Ecology of marine sediments: from science to management. OUP Oxford.
Guisan A, Broennimann O, Engler R, Vust M, Yoccoz NG, Lehmann A, Zimmermann NE. Using niche-based models to improve the sampling of rare species. Conserv Biol. 2006;20:501–11.
Hawkins SJ, Jones HD. Rocky shores (Vol. 1). Sea challengers; 1992.
Herbert RJH, Hawkins SJ, Sheader M, Southward AJ. Range extension and reproduction of the barnacle Balanus perforatus in the eastern English Channel. J Mar Biol Assoc U K. 2003;83:73–82.
Herbert RJH, Southward AJ, Sheader M, Hawkins SJ. Influence of recruitment and temperature on distribution of intertidal barnacles in the English Channel. J Mar Biol Assoc U K. 2007;87:487–99.
Hiscock K. In situ survey of intertidal biotopes using abundance scales and checklists at exact locations (ACE surveys). Version 1 of 23 March 1998. In Biological monitoring of marine Special Areas of Conservation: a hand book of methods for detecting change. Part 2. Procedural guidelines (ed. K Hiscock), 3 pp. Peterborough, Joint Nature Conservation Committee. 1998.
Hiscock K. Marine Nature Conservation Review: methods. Joint Nature Conservation Committee, Peterborough, Nature Conservancy Council, CSD Report, No. 1072. (Marine Nature Conservation Review Report, No. MNCR/OR/5). 1990.
Jamieson S. Likert scales: how to (ab) use them. Med Educ. 2004;38:1217–8.
JNCC. The Marine Habitat Classification for Britain and Ireland Version 15.03. [15/01/2020]. 2015. https://mhc.jncc.gov.uk/
Legendre P, Legendre LFJ. Numerical Ecology: Elsevier; 2012.
Mieszkowska N, Kendall MA, Hawkins SJ, Leaper R, Williamson P, Hardman-Mountford NJ, Southward AJ. Changes in the range of some common rocky shore species in Britain—a response to climate change? Marine Biodiversity. Dordrecht: Springer; 2006a. p. 241–51.
Mieszkowska N, Leaper R, Moore P, Kendall MA, Burrows MT, Lear D, Poloczanska ES, Hiscock K, Moschella P, Thompson RC, Herbert RJH. Marine biodiversity and climate change: assessing and predicting the influence of climatic change using intertidal rocky shore biota. Occasional Publication of the Marine Biological Association. 2006b;20.
Mieszkowska N, Milligan G, Burrows MT, Freckleton R, Spencer M. Dynamic species distribution models from categorical survey data. J Anim Ecol. 2013;82:1215–26.
Miller AW, Ambrose RF. Sampling patchy distributions: comparison of sampling designs in rocky intertidal habitats. Mar Ecol Prog Ser. 2000;196:1–14.
Nelson-Smith A. Marine biology of Milford Haven: the physical environment: Field studies council; 1967.
Norman G. Likert scales, levels of measurement and the "laws" of statistics. Adv Health Sci Educ. 2010;15:625–32.
Podani J. Braun-Blanquet's legacy and data analysis in vegetation science. J Veg Sci. 2006;17:113–7.
Preston FW. The commonness, and rarity, of species. Ecology. 1948;29:254–83.
R Core Team. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2013. URL http://www.R-project.org/
Rodwell, J.S. & Joint Nature Conservation Committee (2006). National vegetation classification: Users' handbook. Peterborough: Joint nature conservation committee. Available at: http://archive.jncc.gov.uk/pdf/pub06_NVCusershandbook2006.pdf (last Accessed 24/09/2019).
Stark JD. SQMCI: A biotic index for freshwater macroinvertebrate coded-abundance data. N Z J Mar Freshw Res. 1998;32:55–66.
Simkanin C, Power AM, Myers A, McGrath D, Southward A, Mieszkowska N, Leaper R, O'Riordan R. Using historical data to detect temporal changes in the abundances of intertidal species on Irish shores. J Mar Biol Assoc U K. 2005;85:1329–40.
Southward AJ, Crisp DJ. The distribution of certain intertidal animals around the Irish coast. In: In Proceedings of the Royal Irish Academy. Section B: Biological, Geological, and Chemical Science, vol. 57: Royal Irish Academy; 1954. p. 1–29.
Sullivan GM, Artino AR Jr. Analyzing and interpreting data from Likert-type scales. J Grad Med Educ. 2013;5:541–2.
Wang YI, Naumann U, Wright ST, Warton DI. mvabund–an R package for model‐based analysis of multivariate abundance data. Methods in Ecology and Evolution. 2012;3(3):471–4.
Wheater CP, Bell JR, Cook PA. Practical Field ecology: A project guide: Wiley; 2011.
The authors wish to thank Dr. Cristina Hebron and Gemma Singleton for their input into the development of the SACFOR conversion. We also wish to thank the anonymous referees for their helpful advice during the review process.
The final development of the concepts in this paper where funded by the Natural Environment Research Council as part of the Climate Linked Atlantic Sector Science (CLASS) National Capability project. The funding body did not influence the design, analysis, or interpretation of the study, or to the writing of the manuscript.
National Oceanography Centre, University of Southampton Waterfront Campus, European Way, Southampton, SO14 3ZH, UK
James Asa Strong
Biology and Marine Science, University of Hull, Cottingham Road, Hull, HU6 7RX, UK
Magnus Johnson
JS and MJ contributed equally to all sections of the analysis and manuscript preparation. Both authors read and approved the final manuscript.
Correspondence to James Asa Strong.
Strong, J.A., Johnson, M. Converting SACFOR data for statistical analysis: validation, demonstration and further possibilities. Mar Biodivers Rec 13, 2 (2020). https://doi.org/10.1186/s41200-020-0184-3
SACFOR scale
Conversion process
Semi-quantitative data analysis
Marine data reanalysis
Ordinal data


Chris Calvey Headmaster of Great Walstead School, West Sussex, talks about the balancing act of meeting academic rigor whilst maintaining pupils' excitement and enthusiasm.
School League tables are now very much a part of our lives and pre-testing for schools is creeping in at a younger and younger age. Now, take into account the not insignificant amount of money that private schools charge. You can see the rising pressure on both teachers and the Head to ensure that pupils achieve the highest results. The safest way to do this sees the classroom take on a more teacher lead approach where pupils are told the information they need to learn, guided in how to answer questions by rehearsing past papers and even have timetabled lessons on verbal and nonverbal reasoning tests. Such an approach generally ensures that pupils pass their tests but at the cost of genuine enjoyment, pleasure and natural wonderment of school.
I believe there is an alternative way in which children can foster their love of learning. By understanding there is more to the process of education than just working to pass a test, they are able to develop a set of skills that enables them to tackle challenges without a fear of failure. Inspired by the book " Educating Ruby – what our children really need to learn" written by Guy Claxton and Bill Lucas, all the staff at Great Walstead School explored a variety of definitions for the seven aspects that the book identified as developing confidence and character. At Great Walstead we refer to these as our 7Cs – Confidence, Curiosity, Collaboration, Communication, Creativity, Commitment and Craftsmanship.
Each "C" has an age appropriate definition for the sections of our school and children are rewarded when they demonstrate these attributes. They see confidence as the ability to tackle difficult tasks and challenges whilst not being afraid to make mistakes. Curiosity is about developing wonder and awe, while collaboration helps pupils see the benefits of working in a successful team. Communication encourages children to share their ideas and thinking whilst understanding the importance of listening to each other. Creativity is not just for the Arts, but is to be developed with problem solving challenges and alternative thinking. Commitment recognises those times when pupils show determination and resilience even if they find tasks challenging. Finally, craftsmanship celebrates the sheer joy and pride of completing something which has taken time, care and love to produce. By rewarding these skills, every child is able to achieve and none are limited by their cognitive ability. It leads to an "I can" culture rather than a fixed mind set where pupils feel limited by the scores they achieve.
Since focusing on the 7Cs, we have seen children become far more engaged in their learning process, take responsibility and, as a result, make impressive levels of academic progress where they not only know things, but genuinely understand them – there is a distinct difference.
Children only get one chance at their schooling and I believe it is so important that we look to develop the whole person – not just focus on exam results and entry testing. Working in several prep schools, I have seen and promoted many "learning profiles" from school ethos based principles to International Baccalaureate inspired systems. All offer something more than just a "teacher led" approach to learning, but in the 7Cs I have found a set of values and attributes that really inspires the girls and boys in our school and prepares them for the challenges that lie ahead.


Nisichawayasi Nehetho Culture and Education Authority Inc is based in Nelson House, Manitoba, about 800 kilometres north of Winnipeg and 80 kilometres west of Thompson.
The community is part of the reserve lands of the Nisichawayasihk Cree Nation - pronounced Nissy chaw why-ah seek.
Around 2,900 of NCN's approximately 5,000 members live in Nelson House. Other members live in South Indian Lake, Leaf Rapids, Thompson, Brandon and Winnipeg. More than 60 percent of NCN members are between 13 and 30 years of age.
In 2006, NCN signed the historic Wuskwatim Project Development Agreement with Manitoba Hydro to build the Wuskwatim hydroelectric generation project, estimated to cost $1.3 billion including the required transmission line.
The agreement provides for NCN to own up to 33 per cent of the project and related revenues once project loans are repaid, along with job opportunities for qualified NCN members and business opportunities for NCN businesses and joint-venture business partnerships during construction.
The 200-megawatt hydroelectric generating station is currently under construction at Taskinigahp Falls, about 40 kilometres downstream of Nelson House in NCN's traditional territory and is expected to be completed around 2011.
NCN has been training members for jobs on the Wuskwatim Project at the newly-constructed, $8.6-million, Atoskiwin Training and Employment Centre, located near O.K. School.
community infrastructure programs, in keeping with NCN's vision to sustain a prosperous socio-economic future for the First Nation.
These developments include new housing, the NCN Personal Care Home, the NCN Family and Community Wellness Centre, the RCMP detachment, roads and investments in NCN-owned businesses.
To learn more about NCN's community, please visit the First Nation's website, www.ncncree.com.


my daughter is growing up at an alarming rate. it seems like yesterday i was walking her into preschool & now she is in jr. high. it's crazy! i know everyone says 'they grow so fast, cherish each moment'. wow it's crazy how fast it goes… looking back on these past 11 years, they fly! it seems like you will never get a break when they are little & you're just hoping to get a shower or a solid night sleep, heck if you brush your hair it's a good day. but looking back at those simple days, those will forever be some of my most cherished times with my kids. sometimes you don't know the best years until they are past. it seems like the years leading to kinder last a lifetime when you are in those times & then once they finish kinder it just moves past at lighning speed. now i look onto even more of the best years ahead as being a mom to these kids. they may be a different kind of best, a different kind of challenge but i still want to hold on as long as i can, anyway i can. for me that's thru pictures. and lately i find myself taking lots & lots of pictures of my kids thinking: how much longer do i have of them actually liking me & wanting to spend time with me lol. mother hood is crazy like that, when we have them all the time we need a break & when we see them slipping into independence we try to hold on tighter.
here are a few of my fav shots off my contax 645 camera shot on kodak porta 400 film. my daughter & i took a walk out to one of our favorite kauai beaches. we were not dressed for pictures in mind. we just wanted to go & have a little time together & since i always have a camera rollin along everywhere we go….. we had fun, we had laughs, we got sand in our eyes, we got wet from waves, i stubbed my toe….they may not be perfect but i will cherish these for a lifetime.


french armoire for sale painted cottage chic shabby romantic french french armoire for sale ireland.
water softener size calculator clack x water softener water softener capacity calculator by tank size and hardness level.
nostalgia refrigerator retro nostalgia refrigerator parts.
overhead door south bend new model c overhead door co south bend.
5 ton ac compressor 5 ton ac air conditioning installation is a ton ac the right size for your home 5 ton ac 5 ton hvac compressor cost.
plastic folding step stool wish plastic step stool chair camping fishing kids children folding seat collapsible step stool random color x x cm folding plastic step stool large.
how to get glue off concrete floor cleaning carpet glue off concrete floors.
anchor decor wooden anchor wall decor anchor decor wood anchor with rope anchor ideas for baby shower.
woven trunk view larger woven trunk storage.
laser cut design striking laser cut peacock invitation card design laser cut design vector free download.


text:
Almost Famous' Stillwater Go to Rock School in New Behind the Scenes Footage: Exclusive
Cameron Crowe, Nancy Wilson, and Jason Lee discuss finding the fictional band's sound in special feature from the new 4K Ultra HD release.
Almost Famous Soundtrack Reissued As Massive 102-Song Box Set
Across five CDs and seven LPs, the deluxe reissue marks the first all of the music featured in the film will be released together in one package.
First Women-Only Rock 'n' Roll Fantasy Camp to Feature Melissa Etheridge, Heart's Nancy Wilson, and More
The four-day camp takes place January 27th through 30th, 2022, in Los Angeles.
Beyond the Boys' Club: Nancy Wilson of Heart
Wilson discusses her new solo album, her experience as a woman in the music industry, and why she's grateful for younger artists like Phoebe Bridgers and Billie Eilish.
Aly & AJ on Channeling Classic Laurel Canyon Vibes
The two sisters join Kyle Meredith to talk about their first album in 14 years, A Touch of the Beat Gets You Up On Your Feet Gets You Out and Then Into the Sun.
Heart's Nancy Wilson Details Debut Solo Album You and Me
Duff McKagan and Foo Fighters' Taylor Hawkins guest contribute to the project.
Heart's Nancy Wilson and Epiphone Announce New "Fanatic" Electric Guitar
The guitar is Nancy Wilson's second collaboration with Gibson Brands and her first Epiphone design.
Heart's Nancy Wilson Shares Cover of Bruce Springsteen's "The Rising": Stream
From her forthcoming debut solo album.
Heart's Nancy Wilson Announces Debut Solo Album
The first single is a cover of Bruce Springsteen's "The Rising".

redpajama_set_name: RedPajamaCommonCrawl


text:
A Psalm for giving thanks. Make a joyful noise to the Lord, all the earth! Serve the Lord with gladness! Come into his presence with singing! Know that the Lord, he is God! It is he who made us, and we are his; we are his people, and the sheep of his pasture. Enter his gates with thanksgiving, and his courts with praise! Give thanks to him; bless his name! For the Lord is good; his steadfast love endures forever, and his faithfulness to all generations. ... Christian Art and Gifts
In the four hundred and eightieth year after the people of Israel came out of the land of Egypt, in the fourth year of Solomon's reign over Israel, in the month of Ziv, which is the second month, he began to build the house of the Lord. The house that King Solomon built for the Lord was sixty cubits long, twenty cubits wide, and thirty cubits high. The vestibule in front of the nave of the house was twenty cubits long, equal to the width of the house, and ten cubits deep in front of the house. And he made for the house windows with recessed frames. He also built a structure against the wall of the house, running around the walls of the house, both the nave and the inner sanctuary. And he made side chambers all around. ... Bible Scripture Verse Art
"See, I have called by name Bezalel the son of Uri, son of Hur, of the tribe of Judah, and I have filled him with the Spirit of God, with ability and intelligence, with knowledge and all craftsmanship, to devise artistic designs, to work in gold, silver, and bronze, in cutting stones for setting, and in carving wood, to work in every craft. And behold, I have appointed with him Oholiab, the son of Ahisamach, of the tribe of Dan. And I have given to all able men ability, that they may make all that I have commanded you: ... Christian Canvas Art
Now there were four supports at the four corners of each stand; its supports were part of the stand itself. On the top of the stand there was a circular form half a cubit high, and on the top of the stand its stays and its borders were part of it. He engraved on the plates of its stays and on its borders, cherubim, lions and palm trees, according to the clear space on each, with wreaths all around.read more. Christian Art and Gifts
"Come, everyone who thirsts, come to the waters; and he who has no money, come, buy and eat! Come, buy wine and milk without money and without price. Why do you spend your money for that which is not bread, and your labor for that which does not satisfy? Listen diligently to me, and eat what is good, and delight yourselves in rich food. Incline your ear, and come to me; hear, that your soul may live; and I will make with you an everlasting covenant, my steadfast, sure love for David. Behold, I made him a witness to the peoples, a leader and commander for the peoples. Behold, you shall call a nation that you do not know, and a nation that did not know you shall run to you, because of the Lord your God, and of the Holy One of Israel, for he has glorified you. ... Share Your Faith Products Canvas Art
The Lord said to Moses, "See, I have called by name Bezalel the son of Uri, son of Hur, of the tribe of Judah, and I have filled him with the Spirit of God, with ability and intelligence, with knowledge and all craftsmanship, to devise artistic designs, to work in gold, silver, and bronze, in cutting stones for setting, and in carving wood, to work in every craft. ... Christian Art and Gifts
My son, do not forget my teaching, but let your heart keep my commandments, for length of days and years of life and peace they will add to you. Let not steadfast love and faithfulness forsake you; bind them around your neck; write them on the tablet of your heart. So you will find favor and good success in the sight of God and man. Trust in the Lord with all your heart, and do not lean on your own understanding. ... Christian Canvas Art
Unless otherwise indicated, all content is licensed under a Creative Commons Attribution License. All Scripture quotations, unless otherwise indicated, are taken from The Holy Bible, English Standard Version. Copyright ©2001 by Crossway Bibles, a publishing ministry of Good News Publishers. Contact me: openbibleinfo (at) gmail.com. Cite this page: Editor: Stephen Smith. Publication date: Jun 18, 2019. Publisher: OpenBible.info.
Being one of the industry leaders for over a decade, we know more about vinyl wall decal than most companies out there. We have learned by trial and error and from amazing feedback from our awesome customers. We are Amazon Professional Sellers, Ebay Power Sellers, and Ebay Top Sellers, and sell through at least 15 other sites online. However, you will typically get our best pricing here at our website plus it is definitely easier to find specific wall arts here than at most sites. Christian Canvas Art
I like to have a few areas in my house that I change out when the mood strikes me. The kitchen message board I have is one of those places and adding a new bible verse here always brightens my day. Maybe you have a spot that could use something new? You can visit any of the sites below to download a FREE piece of scripture art!!! I suggest downloading the pieces you like and having them printed on heavy cardstock. Go ahead and print a few at a time, then you have them on hand to change out. If you are a frequent visitor to the blog you know I provide a new free printable scripture download every month, so be sure to get yours here! Now on to some more freebies from some of my favorites bloggers on the internet (plus a few more from me!)! Christian Canvas Art
and in the cutting of stones for settings and in the carving of wood, so as to perform in every inventive work. "He also has put in his heart to teach, both he and Oholiab, the son of Ahisamach, of the tribe of Dan. "He has filled them with skill to perform every work of an engraver and of a designer and of an embroiderer, in blue and in purple and in scarlet material, and in fine linen, and of a weaver, as performers of every work and makers of designs. Bible Scripture Verse Art
From the very first verse of Scripture, God reveals himself as the Creator, an Artist. Everything within the universe is a magnificent element of the Great Artist's masterpiece. As works of art created in God's own image (Gen 1:27), people are endowed with the ability to create as well. We can choose to join the Master Artist by being artists ourselves. Christian Art and Gifts
Moses assembled all the congregation of the people of Israel and said to them, "These are the things that the Lord has commanded you to do. Six days work shall be done, but on the seventh day you shall have a Sabbath of solemn rest, holy to the Lord. Whoever does any work on it shall be put to death. You shall kindle no fire in all your dwelling places on the Sabbath day." Moses said to all the congregation of the people of Israel, "This is the thing that the Lord has commanded. Take from among you a contribution to the Lord. Whoever is of a generous heart, let him bring the Lord's contribution: gold, silver, and bronze; ... Christian Canvas Art
The word that came to Jeremiah from the Lord: "Arise, and go down to the potter's house, and there I will let you hear my words." So I went down to the potter's house, and there he was working at his wheel. And the vessel he was making of clay was spoiled in the potter's hand, and he reworked it into another vessel, as it seemed good to the potter to do. Then the word of the Lord came to me: ... Christian Art and Gifts
"Now I am sending Huram-abi, a skilled man, endowed with understanding, the son of a Danite woman and a Tyrian father, who knows how to work in gold, silver, bronze, iron, stone and wood, and in purple, violet, linen and crimson fabrics, and who knows how to make all kinds of engravings and to execute any design which may be assigned to him, to work with your skilled men and with those of my lord David your father.
To the choirmaster: with stringed instruments. A Psalm of Asaph. A Song. In Judah God is known; his name is great in Israel. His abode has been established in Salem, his dwelling place in Zion. There he broke the flashing arrows, the shield, the sword, and the weapons of war. Selah Glorious are you, more majestic than the mountains of prey. The stouthearted were stripped of their spoil; they sank into sleep; all the men of war were unable to use their hands. ... Bible Scripture Verse Art
"You saw, O king, and behold, a great image. This image, mighty and of exceeding brightness, stood before you, and its appearance was frightening. The head of this image was of fine gold, its chest and arms of silver, its middle and thighs of bronze, its legs of iron, its feet partly of iron and partly of clay. As you looked, a stone was cut out by no human hand, and it struck the image on its feet of iron and clay, and broke them in pieces. Then the iron, the clay, the bronze, the silver, and the gold, all together were broken in pieces, and became like the chaff of the summer threshing floors; and the wind carried them away, so that not a trace of them could be found. But the stone that struck the image became a great mountain and filled the whole earth. Christian Canvas Art
"You shall make two cherubim of gold, make them of hammered work at the two ends of the mercy seat. "Make one cherub at one end and one cherub at the other end; you shall make the cherubim of one piece with the mercy seat at its two ends. "The cherubim shall have their wings spread upward, covering the mercy seat with their wings and facing one another; the faces of the cherubim are to be turned toward the mercy seat.read more. Bible Scripture Verse Art
"Bezalel and Oholiab and every craftsman in whom the Lord has put skill and intelligence to know how to do any work in the construction of the sanctuary shall work in accordance with all that the Lord has commanded." And Moses called Bezalel and Oholiab and every craftsman in whose mind the Lord had put skill, everyone whose heart stirred him up to come to do the work. And they received from Moses all the contribution that the people of Israel had brought for doing the work on the sanctuary. They still kept bringing him freewill offerings every morning, so that all the craftsmen who were doing every sort of task on the sanctuary came, each from the task that he was doing, and said to Moses, "The people bring much more than enough for doing the work that the Lord has commanded us to do." ... Share Your Faith Products Canvas Art
What does the Bible say about creativity? The very first verse of Scripture actually describes a creative act as "God created the heavens and the earth." Additionally, from Genesis, the Bible says, "God created man in his own image." This could be interpreted as we are creators just as God created us. We create relationships, art, homes, cities, nations and many more things including inventions even yet to be known! The creative spirit is certainly favored by God and our fellow man. Learn more from the collection of Bible verses about creativity below! Christian Art and Gifts
"Now I am sending Huram-abi, a skilled man, endowed with understanding, the son of a Danite woman and a Tyrian father, who knows how to work in gold, silver, bronze, iron, stone and wood, and in purple, violet, linen and crimson fabrics, and who knows how to make all kinds of engravings and to execute any design which may be assigned to him, to work with your skilled men and with those of my lord David your father. Christian Canvas Art
Throughout history, many artists have acknowledged God's sovereignty and position as the ultimate Creator depicting in their work the accounts and truths which God has given to his people through the Bible. Virtually every biblical account has been visually portrayed at least once and usually many times throughout history and across cultures. In museums, galleries, churches, cathedrals, and homes around the world, such works of art are helping people gain a deeper understanding of the Scriptures. Christian Art and Gifts
"Now I am sending Huram-abi, a skilled man, endowed with understanding, the son of a Danite woman and a Tyrian father, who knows how to work in gold, silver, bronze, iron, stone and wood, and in purple, violet, linen and crimson fabrics, and who knows how to make all kinds of engravings and to execute any design which may be assigned to him, to work with your skilled men and with those of my lord David your father. Christian Art and Gifts
For I want you to know how great a struggle I have for you and for those at Laodicea and for all who have not seen me face to face, that their hearts may be encouraged, being knit together in love, to reach all the riches of full assurance of understanding and the knowledge of God's mystery, which is Christ, in whom are hidden all the treasures of wisdom and knowledge. I say this in order that no one may delude you with plausible arguments. For though I am absent in body, yet I am with you in spirit, rejoicing to see your good order and the firmness of your faith in Christ. ... Share Your Faith Products Canvas Art
Now when the wall had been built and I had set up the doors, and the gatekeepers, the singers, and the Levites had been appointed, I gave my brother Hanani and Hananiah the governor of the castle charge over Jerusalem, for he was a more faithful and God-fearing man than many. And I said to them, "Let not the gates of Jerusalem be opened until the sun is hot. And while they are still standing guard, let them shut and bar the doors. Appoint guards from among the inhabitants of Jerusalem, some at their guard posts and some in front of their own homes." The city was wide and large, but the people within it were few, and no houses had been rebuilt. Then my God put it into my heart to assemble the nobles and the officials and the people to be enrolled by genealogy. And I found the book of the genealogy of those who came up at the first, and I found written in it: ... Bible Scripture Verse Art
and in the cutting of stones for settings, and in the carving of wood, that he may work in all kinds of craftsmanship. "And behold, I Myself have appointed with him Oholiab, the son of Ahisamach, of the tribe of Dan; and in the hearts of all who are skillful I have put skill, that they may make all that I have commanded you: the tent of meeting, and the ark of testimony, and the mercy seat upon it, and all the furniture of the tent, the table also and its utensils, and the pure gold lampstand with all its utensils, and the altar of incense, the altar of burnt offering also with all its utensils, and the laver and its stand,
Now King Solomon sent and brought Hiram from Tyre. He was a widow's son from the tribe of Naphtali, and his father was a man of Tyre, a worker in bronze; and he was filled with wisdom and understanding and skill for doing any work in bronze So he came to King Solomon and performed all his work. He fashioned the two pillars of bronze; eighteen cubits was the height of one pillar, and a line of twelve cubits measured the circumference of both. read more. Christian Canvas Art
"You shall take two onyx stones and engrave on them the names of the sons of Israel, six of their names on the one stone and the names of the remaining six on the other stone, according to their birth. "As a jeweler engraves a signet, you shall engrave the two stones according to the names of the sons of Israel; you shall set them in filigree settings of gold.read more. Christian Canvas Art
For the entrance of the inner sanctuary he made doors of olive wood, the lintel and five-sided doorposts. So he made two doors of olive wood, and he carved on them carvings of cherubim, palm trees, and open flowers, and overlaid them with gold; and he spread the gold on the cherubim and on the palm trees. So also he made for the entrance of the nave four-sided doorposts of olive woodread more. Bible Scripture Verse Art
Remember that biblical art, as a visual representation of the Bible, is not always rated "G." The Bible is not a children's story, so some biblical art contains nudity or bloody depictions of violence. Not all things in the Bible are beautiful and calming; many times biblical stories are full of distortion and dissonance. As such, biblical artwork will tell the full Story of God that includes creation, fall, and redemption, with each of its harsh realities. As in all of life, the believer is called to be discerning.
It was carved with cherubim and palm trees; and a palm tree was between cherub and cherub, and every cherub had two faces, a man's face toward the palm tree on one side and a young lion's face toward the palm tree on the other side; they were carved on all the house all around. From the ground to above the entrance cherubim and palm trees were carved, as well as on the wall of the nave. The doorposts of the nave were square; as for the front of the sanctuary, the appearance of one doorpost was like that of the other. The altar was of wood, three cubits high and its length two cubits; its corners, its base and its sides were of wood And he said to me, "This is the table that is before the LORD." The nave and the sanctuary each had a double door. Each of the doors had two leaves, two swinging leaves; two leaves for one door and two leaves for the other. Also there were carved on them, on the doors of the nave, cherubim and palm trees like those carved on the walls; and there was a threshold of wood on the front of the porch outside. There were latticed windows and palm trees on one side and on the other, on the sides of the porch; thus were the side chambers of the house and the thresholds. Bible Scripture Verse Art
A Psalm of David. The Lord is my shepherd; I shall not want. He makes me lie down in green pastures. He leads me beside still waters. He restores my soul. He leads me in paths of righteousness for his name's sake. Even though I walk through the valley of the shadow of death, I will fear no evil, for you are with me; your rod and your staff, they comfort me. You prepare a table before me in the presence of my enemies; you anoint my head with oil; my cup overflows. ...
He made two cherubim of gold; he made them of hammered work at the two ends of the mercy seat; one cherub at the one end and one cherub at the other end; he made the cherubim of one piece with the mercy seat at the two ends. The cherubim had their wings spread upward, covering the mercy seat with their wings, with their faces toward each other; the faces of the cherubim were toward the mercy seat. Bible Scripture Verse Art
Bible Scripture Verse Art Here Contact us at [email protected] | Sitemap xml | Sitemap txt | Sitemap


text:
Томас Фрэнсис Баярд () — американский политик-демократ, сенатор, 30-й Госсекретарь США.

Молодость и семья
Томас Баярд родился в Уилмингтоне, Делавэр, в семье сенатора Джеймса Баярда-младшего и Энн Фрэнсис. Его дед, Джеймс Баярд-старший, также был сенатором. Томас тоже будет избран в сенат, от Бурбонных демократов.

После окончания учёбы в 1851 году Баярд был принят в коллегию адвокатов, и стал работать помощником своего отца. В 1853—1854 был прокурором США по округу Делавэр. В 1854—1858 вместе с другом Уильямом Шиппеном вёл адвокатскую практику в Филадельфии. После этого снова вернулся на работу к отцу.

В 1856 году женился на Луизе Ли (ум. в 1886). В 1889 женился снова, на Мэри Климер.

Гражданская война
Как и отец, Томас Баярд выступал против политики предотвращения раскола государства, но после начала войны выступил сторонником США. Был обвинён в сотрудничестве с КША, так как в Делавэре существовали сторонники сецессии. Подозрение пало именно на него потому, что в его полку, известному как «Делавэрская охрана», были проюжане, да и на счёт лояльности самого Баярда у многих возникали сомнения. Арестован, но вскоре освобождён, так как его полк был расформирован. Также он известен тем, что 2 января 1861 года окончательно убедил Генеральную ассамблею Делавэр остаться в составе США.

Сенатор
4 марта 1869 года Баярд занял отцовское кресло в Сенате США. Неоднократно был председателем разных сенатских комитетов, в том числе по финансам и по частной собственности. Входил в комитет, который определил победителем на президентских выборах 1876 года Ратерфорда Хейса. В 1876, 1880, и 1884 выставлял свою кандидатуру на выдвижение на пост президента США, но в результате внутрипартийных выборов всегда оказывался на втором месте.

Государственный секретарь
С 7 марта 1885 по 4 марта 1889 год Баярд занимал пост Госсекретаря США в администрации Гровера Кливленда. В этой должности он заключил договор о рыболовстве с Великобританией, который уладил противоречия между США и Канадой в Северной Атлантике. Также при его участии был урегулировано противоречие Великобритании и Германии касательно Самоа. Кроме того, было достигнуто соглашение с Испанией, отменявшее некоторые торговые тарифы.

Посол в Великобритании
В 1889—1893 гг. занимался адвокатской практикой, а после возвращения Гровера Кливленда на пост президента был назначен послом в Великобритании. В период с 1893 по 1897 год укреплял связи между двумя государствами, однако и успел раскритиковать политику протекционизма в торговле у себя на родине. Был уж очень неравнодушен к Великобритании, и в 1895 Палата представителей собиралась снять его с должности. Английская сторона, наоборот, была очень довольна его работой.

Смерть и память
28 сентября 1898 года Томас Фрэнсис Баярд умер в доме своей дочери в Дедхэме, Массачусетс. Похоронен на кладбище Old Swedes в Уилмингтоне. Его сын, Томас Фрэнсис Баярд-младший продолжил семейную традицию, и в 1922—1929 заседал в Сенате. В родном городе Баярда его именем названа начальная школа, а также возведён памятник.

Ссылки
 Biographical Directory of the United States Congress
 Find a Grave
 The Political Graveyard
 Thomas F. Bayard papers, 1780—1899 (Library of Congress)

Члены Демократической партии США
Государственные секретари США
Послы США в Великобритании
Юристы США
Временные президенты Сената США
Политики США XIX века
Почётные доктора Йельского университета

redpajama_set_name: RedPajamaWikipedia


text:
Empowering communities, illuminating the energy industry
Our members stand ready to respond to outages in times of need. This showed true last summer when 4,000 crew members worked endless hours to restore power to thousands of Iowans. This season, I am giving my thanks and appreciation to those dedicated workers.
On behalf of the IUA, I wish everyone a happy holiday and a healthy new year.
— Chaz Allen, executive director of the Iowa Utility Association
Rendering utility relief for small businesses
The small businesses and storefronts that make our main streets vibrant have faced innumerable challenges this year. We wanted to help alleviate at least one stressor: utility payments. In partnership with the Iowa Economic Development Authority, we assisted in the creation of the Small Business Utility Disruption Prevention program, made possible through federal pandemic relief funds.
Nearly 1,000 small business across the state have benefitted from the program, which provides funds for small business owners who needed assistance in paying utilities. To date, more than $2.6 million in financial assistance was administered to program applicants. Some recipients say the funds have helped them stay in business during the last several months. We're pleased to lend a helping hand to business owners fighting to stay open to provide necessary jobs, products and services for their communities.
Shining light on our members
Recently, Alliant Energy introduced a plan that creates jobs, helps the environment and saves Iowans millions of dollars over the next three decades.
The plan, known as the Clean Energy Blueprint, includes adding up to 400 megawatts of solar energy by 2023, eliminating the use of coal and reducing emissions by retiring the Lansing Generating Station and transitioning the Burlington Generating Station to natural gas. Their plan will also include adding battery storage and more connected energy to the network. By 2023, nearly half of Alliant Energy's Iowa portfolio will be from renewables.
Cindy Tomlinson, manager of external communications for Alliant Energy, said this plan has great long-term benefits for Iowans. The Clean Energy Blueprint will save Iowans $300 million throughout the next 35 years, according to the company's projections.
Many of Alliant Energy's other efforts align with the Clean Energy Blueprint. Earlier this year, Alliant Energy opened a solar garden in Marshalltown and a battery storage project in Decorah.
Providers awarded for restoring Iowa's infrastructure
Iowans count on the electricity and gas our member utility companies provide to live their daily lives, conduct business and grow communities. Utility providers know how vital their services are, and they're not used to being honored for these amenities. That's what makes the Infrastructure award Alliant Energy, MidAmerican Energy and ITC Midwest received from The Gazette in Cedar Rapids all the more special.
Alliant Energy, MidAmerican Energy and ITC Midwest received the honor as part of The Gazette's business awards for their incredible work restoring and maintaining the state's infrastructure after the August derecho tore across the state. The Iowa Utility Association could not be more proud of our member companies' responses.
Of course, all our member utility providers are accustomed to wading into damage to restore service after storms, but the derecho and its widespread, devastating impact on the state brought never-before-seen challenges. Despite the destruction, utility companies restored power and gas to nearly half a million Iowans in approximately two weeks.
The key to success? Collaboration. The interconnectivity of the utility providers and the relationships they have with their communities are integral to the industry that powers lives and businesses, ITC Midwest President Dusky Terry said in an interview with The Gazette.
Alliant Energy, MidAmerican Energy and ITC Midwest not only coordinated to rebuild damaged infrastructure — lending each other equipment, employees and support crews, but they also provided humanitarian relief to communities by immediately deploying mobile generators, procuring supplies residents and cities needed to rebuild and donating funds to restoration efforts.
"We (utility providers) have the ability to stand up, and we stand up together," Kathryn Kunert, vice president of economic connections and integration at MidAmerican Energy, noted in an interview with The Gazette.
And while efficient communication and coordination clearly paid off in speedy restoration, utility providers aren't resting. They continue to assess how to improve disaster responses. Our utility providers know our state's economy and development opportunities are only as strong as our infrastructure.
"Building stronger communities is our purpose," said Joel Schmidt, Alliant Energy's vice president of business development.
All of Iowa's utility providers continue to work together to ensure Iowan's have the energy and infrastructure they need day and night, rain or shine.
Thank you for pushing us to power our communities.
Learn more about our latest work at IowaUtility.org and on LinkedIn, Facebook and Twitter.
Iowa Utility Association
400 East Court Ave., Suite 120
IUAstaff@iowautility.org