Ecological controls on biogeochemical fluxes in the western Antarctic Peninsula studied with an inverse foodweb model

Sea ice in the western Antarctic Peninsula (WAP) region is both highly variable and rapidly changing. In the Palmer Station region, the ice season duration has decreased by 92 d since 1978. The sea-ice changes affect ocean stratification and freshwater balance and in turn impact every component of the polar marine ecosystem. Long-term observations from the WAP nearshore and offshore regions show a pattern of chlorophyll (Chl) variability with three to five years of negative Chl anomalies interrupted by one or two years of positive anomalies (high and low Chl regimes). Both field observations and results from an inverse food-web model show that these high and low Chl regimes differed significantly from each other, with high primary productivity and net community production (NCP) and other rates associated with the high Chl years and low rates with low Chl years. Gross primary production rates (GPP) averaged 30 mmolC.m-2.d-1 in the low Chl years and 100 mmolC.m-2.d-1 in the high Chl years. Both large and small phytoplankton were more abundant and more productive in high Chl years than in low Chl years. Similarly, krill were more important as grazers in high Chl years, but did not differ from microzooplankton in high or low Chl years. Microzooplankton did not differ between high and low Chl years. Net community production differed significantly between high and low Chl years, but mobilized a similar proportion of GPP in both high and low Chl years. The composition of the NCP was uniform in high and low Chl years. These results mphasize the importance of microbial components in the WAP plankton system and suggest that food webs dominated by small phytoplankton can have pathways that funnel production into NCP, and likely, export.

Conceptual Ecological Modelling of Sublittoral Rock Habitats to Inform Indicator Selection

The purpose of this study is to produce a series of Conceptual Ecological Models (CEMs) that represent sublittoral rock habitats in the UK. CEMs are diagrammatic representations of the influences and processes that occur within an ecosystem. They can be used to identify critical aspects of an ecosystem that may be studied further, or serve as the basis for the selection of indicators for environmental monitoring purposes. The models produced by this project are control diagrams, representing the unimpacted state of the environment free from anthropogenic pressures. It is intended that the models produced by this project will be used to guide indicator selection for the monitoring of this habitat in UK waters. CEMs may eventually be produced for a range of habitat types defined under the UK Marine Biodiversity Monitoring R&D Programme (UKMBMP), which, along with stressor models, are designed to show the interactions within impacted habitats, would form the basis of a robust method for indicator selection. This project builds on the work to develop CEMs for shallow sublittoral coarse sediment habitats (Alexander et al 2014). The project scope included those habitats defined as ‘sublittoral rock’. This definition includes those habitats that fall into the EUNIS Level 3 classifications A3.1 Atlantic and Mediterranean high energy infralittoral rock, A3.2 Atlantic and Mediterranean moderate energy infralittoral rock, A3.3 Atlantic and Mediterranean low energy infralittoral rock, A4.1 Atlantic and Mediterranean high energy circalittoral rock, A4.2 Atlantic and Mediterranean moderate energy circalittoral rock, and A4.3 Atlantic and Mediterranean low energy circalittoral rock as well as the constituent Level 4 and 5 biotopes that are relevant to UK waters. A species list of characterising fauna to be included within the scope of the models was identified using an iterative process to refine the full list of species found within the relevant Level 5 biotopes. A literature review was conducted using a pragmatic and iterative approach to gather evidence regarding species traits and information that would be used to inform the models and characterise the interactions that occur within the sublittoral rock habitat. All information gathered during the literature review was entered into a data logging pro-forma spreadsheet that accompanies this report. Wherever possible, attempts were made to collect information from UK-specific peer-reviewed studies, although other sources were used where necessary. All data gathered was subject to a detailed confidence assessment. Expert judgement by the project team was utilised to provide information for aspects of the models for which references could not be sourced within the project timeframe. A multivariate analysis approach was adopted to assess ecologically similar groups (based on ecological and life history traits) of fauna from the identified species to form the basis of the models. A model hierarchy was developed based on these ecological groups. One general control model was produced that indicated the high-level drivers, inputs, biological assemblages, ecosystem processes and outputs that occur in sublittoral rock habitats. In addition to this, seven detailed sub-models were produced, which each focussed on a particular ecological group of fauna within the habitat: ‘macroalgae’, ‘temporarily or permanently attached active filter feeders’, ‘temporarily or permanently attached passive filter feeders’, ‘bivalves, brachiopods and other encrusting filter feeders’, ‘tube building fauna’, ‘scavengers and predatory fauna’, and ‘non-predatory mobile fauna’. Each sub-model is accompanied by an associated confidence model that presents confidence in the links between each model component. The models are split into seven levels and take spatial and temporal scale into account through their design, as well as magnitude and direction of influence. The seven levels include regional to global drivers, water column processes, local inputs/processes at the seabed, habitat and biological assemblage, output processes, local ecosystem functions, and regional to global ecosystem functions. The models indicate that whilst the high level drivers that affect each ecological group are largely similar, the output processes performed by the biota and the resulting ecosystem functions vary both in number and importance between groups. Confidence within the models as a whole is generally high, reflecting the level of information gathered during the literature review. Physical drivers which influence the ecosystem were found to be of high importance for the sublittoral rock habitat, with factors such as wave exposure, water depth and water currents noted to be crucial in defining the biological assemblages. Other important factors such as recruitment/propagule supply, and those which affect primary production, such as suspended sediments, light attenuation and water chemistry and temperature, were also noted to be key and act to influence the food sources consumed by the biological assemblages of the habitat, and the biological assemblages themselves. Output processes performed by the biological assemblages are variable between ecological groups depending on the specific flora and fauna present and the role they perform within the ecosystem. Of particular importance are the outputs performed by the macroalgae group, which are diverse in nature and exert influence over other ecological groups in the habitat. Important output processes from the habitat as a whole include primary and secondary production, bioengineering, biodeposition (in mixed sediment habitats) and the supply of propagules; these in turn influence ecosystem functions at the local scale such as nutrient and biogeochemical cycling, supply of food resources, sediment stability (in mixed sediment habitats), habitat provision and population and algae control. The export of biodiversity and organic matter, biodiversity enhancement and biotope stability are the resulting ecosystem functions that occur at the regional to global scale. Features within the models that are most useful for monitoring habitat status and change due to natural variation have been identified, as have those that may be useful for monitoring to identify anthropogenic causes of change within the ecosystem. Biological, physical and chemical features of the ecosystem have been identified as potential indicators to monitor natural variation, whereas biological factors and those physical /chemical factors most likely to affect primary production have predominantly been identified as most likely to indicate change due to anthropogenic pressures.

Assessing the sensitivity of subtidal sedimentary habitats to pressures associated with marine activities. Phase 1 Report: Rationale and proposed ecological groupings for Level 5 biotopes against which sensitivity assessments would be best undertaken.

The purpose of this study is to produce a series of Conceptual Ecological Models (CEMs) that represent sublittoral rock habitats in the UK. CEMs are diagrammatic representations of the influences and processes that occur within an ecosystem. They can be used to identify critical aspects of an ecosystem that may be studied further, or serve as the basis for the selection of indicators for environmental monitoring purposes. The models produced by this project are control diagrams, representing the unimpacted state of the environment free from anthropogenic pressures. It is intended that the models produced by this project will be used to guide indicator selection for the monitoring of this habitat in UK waters. CEMs may eventually be produced for a range of habitat types defined under the UK Marine Biodiversity Monitoring R&D Programme (UKMBMP), which, along with stressor models, are designed to show the interactions within impacted habitats, would form the basis of a robust method for indicator selection. This project builds on the work to develop CEMs for shallow sublittoral coarse sediment habitats (Alexander et al 2014). The project scope included those habitats defined as ‘sublittoral rock’. This definition includes those habitats that fall into the EUNIS Level 3 classifications A3.1 Atlantic and Mediterranean high energy infralittoral rock, A3.2 Atlantic and Mediterranean moderate energy infralittoral rock, A3.3 Atlantic and Mediterranean low energy infralittoral rock, A4.1 Atlantic and Mediterranean high energy circalittoral rock, A4.2 Atlantic and Mediterranean moderate energy circalittoral rock, and A4.3 Atlantic and Mediterranean low energy circalittoral rock as well as the constituent Level 4 and 5 biotopes that are relevant to UK waters. A species list of characterising fauna to be included within the scope of the models was identified using an iterative process to refine the full list of species found within the relevant Level 5 biotopes. A literature review was conducted using a pragmatic and iterative approach to gather evidence regarding species traits and information that would be used to inform the models and characterise the interactions that occur within the sublittoral rock habitat. All information gathered during the literature review was entered into a data logging pro-forma spreadsheet that accompanies this report. Wherever possible, attempts were made to collect information from UK-specific peer-reviewed studies, although other sources were used where necessary. All data gathered was subject to a detailed confidence assessment. Expert judgement by the project team was utilised to provide information for aspects of the models for which references could not be sourced within the project timeframe. A multivariate analysis approach was adopted to assess ecologically similar groups (based on ecological and life history traits) of fauna from the identified species to form the basis of the models. A model hierarchy was developed based on these ecological groups. One general control model was produced that indicated the high-level drivers, inputs, biological assemblages, ecosystem processes and outputs that occur in sublittoral rock habitats. In addition to this, seven detailed sub-models were produced, which each focussed on a particular ecological group of fauna within the habitat: ‘macroalgae’, ‘temporarily or permanently attached active filter feeders’, ‘temporarily or permanently attached passive filter feeders’, ‘bivalves, brachiopods and other encrusting filter feeders’, ‘tube building fauna’, ‘scavengers and predatory fauna’, and ‘non-predatory mobile fauna’. Each sub-model is accompanied by an associated confidence model that presents confidence in the links between each model component. The models are split into seven levels and take spatial and temporal scale into account through their design, as well as magnitude and direction of influence. The seven levels include regional to global drivers, water column processes, local inputs/processes at the seabed, habitat and biological assemblage, output processes, local ecosystem functions, and regional to global ecosystem functions. The models indicate that whilst the high level drivers that affect each ecological group are largely similar, the output processes performed by the biota and the resulting ecosystem functions vary both in number and importance between groups. Confidence within the models as a whole is generally high, reflecting the level of information gathered during the literature review. Physical drivers which influence the ecosystem were found to be of high importance for the sublittoral rock habitat, with factors such as wave exposure, water depth and water currents noted to be crucial in defining the biological assemblages. Other important factors such as recruitment/propagule supply, and those which affect primary production, such as suspended sediments, light attenuation and water chemistry and temperature, were also noted to be key and act to influence the food sources consumed by the biological assemblages of the habitat, and the biological assemblages themselves. Output processes performed by the biological assemblages are variable between ecological groups depending on the specific flora and fauna present and the role they perform within the ecosystem. Of particular importance are the outputs performed by the macroalgae group, which are diverse in nature and exert influence over other ecological groups in the habitat. Important output processes from the habitat as a whole include primary and secondary production, bioengineering, biodeposition (in mixed sediment habitats) and the supply of propagules; these in turn influence ecosystem functions at the local scale such as nutrient and biogeochemical cycling, supply of food resources, sediment stability (in mixed sediment habitats), habitat provision and population and algae control. The export of biodiversity and organic matter, biodiversity enhancement and biotope stability are the resulting ecosystem functions that occur at the regional to global scale. Features within the models that are most useful for monitoring habitat status and change due to natural variation have been identified, as have those that may be useful for monitoring to identify anthropogenic causes of change within the ecosystem. Biological, physical and chemical features of the ecosystem have been identified as potential indicators to monitor natural variation, whereas biological factors and those physical /chemical factors most likely to affect primary production have predominantly been identified as most likely to indicate change due to anthropogenic pressures.

Tillin, H. & Tyler-Walters, H., 2014. Assessing the sensitivity of subtidal sedimentary habitats to pressures associated with marine activities. Phase 2 Report – Literature review and sensitivity assessments for ecological groups for circalittoral and offshore Level 5 biotopes. JNCC Report No. 512B, 260 pp.

Human activities within the marine environment give rise to a number of pressures on seabed habitats. Improved understanding of the sensitivity of subtidal sedimentary habitats is required to underpin the management advice provided for Marine Protected Areas, as well as supporting other UK marine monitoring and assessment work. The sensitivity of marine sedimentary habitats to a range of pressures induced by human activities has previously been systematically assessed using approaches based on expert judgement for Defra Project MB0102 (Tillin et al. 2010). This previous work assessed sensitivity at the level of the broadscale habitat and therefore the scores were typically expressed as a range due to underlying variation in the sensitivity of the constituent biotopes. The objective of this project was to reduce the uncertainty around identifying the sensitivity of selected subtidal sedimentary habitats by assessing sensitivity, at a finer scale and incorporating information on the biological assemblage, for 33 Level 5 circalittoral and offshore biotopes taken from the Marine Habitat Classification of Britain and Ireland (Connor et al. 2004). Two Level 6 sub-biotopes were also included in this project as these contain distinctive characterising species that differentiate them from the Level 5 parent biotope. Littoral, infralittoral, reduced and variable salinity sedimentary habitats were excluded from this project as the scope was set for assessment of circalittoral and offshore sedimentary communities. This project consisted of three Phases. • Phase 1 - define ecological groups based on similarities in the sensitivity of characterising species from the Level 5 and two Level 6 biotopes described above. • Phase 2 - produce a literature review of information on the resilience and resistance of characterising species of the ecological groups to pressures associated with activities in the marine environment. • Phase 3 - to produce sensitivity assessment ‘proformas’ based on the findings of Phase 2 for each ecological group. This report outlines results of Phase 2. The Tillin et al., (2010) sensitivity assessment methodology was modified to use the best available scientific evidence that could be collated within the project timescale. An extensive literature review was compiled, for peer reviewed and grey literature, to examine current understanding about the effects of pressures from human activities on circalittoral and offshore sedimentary communities in UK continental shelf waters, together with information on factors that contribute to resilience (recovery) of marine species. This review formed the basis of an assessment of the sensitivity of the 16 ecological groups identified in Phase 1 of the project (Tillin & Tyler-Walters 2014). As a result: • the state of knowledge on the effects of each pressure on circalittoral and offshore benthos was reviewed; • the resistance, resilience and, hence, sensitivity of sixteen ecological groups, representing 96 characteristic species, were assessed for eight separate pressures; • each assessment was accompanied by a detailed review of the relevant evidence; Assessing the sensitivity of subtidal sedimentary habitats to pressures associated with human activities • knowledge gaps and sources of uncertainty were identified for each group; • each assessment was accompanied by an assessment of the quality of the evidence, its applicability to the assessment and the degree of concordance (agreement) between the evidence, to highlight sources of uncertainty as an assessment of the overall confidence in the sensitivity assessment, and finally • limitations in the methodology and the application of sensitivity assessments were outlined. This process demonstrated that the ecological groups identified in Phase 1 (Tillin & Tyler-Walters 2014) were viable groups for sensitivity assessment, and could be used to represent the 33 circalittoral and offshore sediments biotopes identified at the beginning of the project. The results of the sensitivity assessments show: • the majority of species and hence ecological groups in sedimentary habitats are sensitive to physical change, especially loss of habitat and sediment extraction, and change in sediment type; • most sedimentary species are sensitive to physical damage, e.g. abrasion and penetration, although deep burrowing species (e.g. the Dublin Bay prawn - Nephrops norvegicus and the sea cucumber - Neopentadactyla mixta) are able to avoid damaging effects to varying degrees, depending on the depth of penetration and time of year; • changes in hydrography (wave climate, tidal streams and currents) can significantly affect sedimentary communities, depending on whether they are dominated by deposit, infaunal feeders or suspension feeders, and dependant on the nature of the sediment, which is itself modified by hydrography and depth; • sedentary species and ecological groups that dominate the top-layer of the sediment (either shallow burrowing or epifaunal) remain the most sensitive to physical damage; • mobile species (e.g. interstitial and burrowing amphipods, and perhaps cumaceans) are the least sensitive to physical change or damage, and hydrological change as they are already adapted to unstable, mobile substrata; • sensitivity to changes in organic enrichment and hence oxygen levels, is variable between species and ecological groups, depending on the exact habitat preferences of the species in question, although most species have at least a medium sensitivity to acute deoxygenation; • there is considerable evidence on the effects of bottom-contact fishing practices and aggregate dredging on sedimentary communities, although not all evidence is directly applicable to every ecological group; • there is lack of detailed information on the physiological tolerances (e.g. to oxygenation, salinity, and temperature), habitat preferences, life history and population dynamics of many species, so that inferences has been made from related species, families, or even the same phylum; • there was inadequate evidence to assess the effects of non-indigenous species on most ecological groups, and Assessing the sensitivity of subtidal sedimentary habitats to pressures associated with human activities • there was inadequate evidence to assess the effects of electromagnetic fields and litter on any ecological group. The resultant report provides an up-to-date review of current knowledge about the effects of pressures resulting from human activities of circalittoral and offshore sedimentary communities. It provides an evidence base to facilitate and support the provision of management advice for Marine Protected Areas, development of UK marine monitoring and assessment, and conservation advice to offshore marine industries. However, such a review will require at least annual updates to take advantage of new evidence and new research as it becomes available. Also further work is required to test how ecological group assessments are best combined in practice to advise on the sensitivity of a range of sedimentary biotopes, including the 33 that were originally examined.

Identifying predictable foraging habitats for a wide-ranging marine predator using ensemble ecological niche models

Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.

Identifying predictable foraging habitats for a wide-ranging marine predator using ensemble ecological niche models

Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.

Ecological equivalence of species within phytoplankton functional groups

1.There are tens of thousands of species of phytoplankton found throughout the tree of life. Despite this diversity, phytoplankton are often aggregated into a few functional groups according to metabolic traits or biogeochemical role. We investigate the extent to which phytoplankton species dynamics are neutral within functional groups. 2.Seasonal dynamics in many regions of the ocean are known to affect phytoplankton at the functional group level leading to largely predictable patterns of seasonal succession. It is much more difficult to make general statements about the dynamics of individual species. 3.We use a 7 year time-series at station L4 in the Western English Channel with 57 diatom and 17 dinoflagellate species enumerated weekly to test if the abundance of diatom and dinoflagellate species vary randomly within their functional group envelope or if each species is driven uniquely by external factors. 4.We show that the total biomass of the diatom and dinoflagellate functional groups is well predicted by irradiance and temperature and quantify trait values governing the growth rate of both functional groups. The biomass dynamics of the functional groups are not neutral and each has their own distinct responses to environmental forcing. Compared to dinoflagellates, diatoms have faster growth rates, and grow faster under lower irradiance, cooler temperatures, and higher nutrient conditions. 5.The biomass of most species vary randomly within their functional group biomass envelope, most of the time. As a consequence, modelers will find it difficult to predict the biomass of most individual species. Our analysis supports the approach of using a single set of traits for a functional group and suggests that it should be possible to determine these traits from natural communities.

Ecological comparative study of the rock-rose scrubs of Madrid, II. Soil-pH seasonal fluctuation

During twao years soil and litter pH of 31 permanent plots grown by several rock-rose scrubs (jarales) of Cistion laurifolii at different dynamic stages have been measured. Acidily records show the existence of important seasonal variations and according to a certain rythm. The different syntaxa are characterized as for this ecological factor and the results for these matorrals are compared with other data of heath-scrubs. Adult jaral-phases tend to decrease soil pH when compared with younger dwarf-scrubs-phases, nevertheless upper soil levels generally remain less acidic. Multivariable analysis do not show preference of t he different syntaxa for a certain soil-pH range.

New wild Brassica oleracea L. germplasm at its western distribution limit in the Iberian Peninsula

An exploration and collection mission for wild Brassica oleracea populations was carried out in spring and summer of 2013. The aim of this collection was to expand the number of accessions of wild Brassica oleracea available for basic and applied research in plant breeding. In this paper we report a new accession of wild Brassica oleracea in an unexplored coastal area of Galicia, NW Iberian Peninsula. Details of population ecology and vegetation, soil, climate and geographic data were recorded for this population. The “Endangered” threat category for the region is proposed, and actions for in situ and ex situ conservation are proposed. Seeds will be added to the germplasm collections of University of Santiago de Compostela and Misión Biológica de Galicia (CSIC) for further research on diverse aspects of the dynamics and ecophysiology of the population along with characterization and evaluation of useful traits.

Summary statistics, educational achievement gaps and the ecological fallacy

Summary statistics continue to play an important role in identifying and monitoring patterns and trends in educational inequalities between differing groups of pupils over time. However, this article argues that their uncritical use can also encourage the labelling of whole groups of pupils as ‘underachievers’ or ‘overachievers’ as the findings of group-level data are simply applied to individual group members, a practice commonly termed the ‘ecological fallacy’. Some of the adverse consequences of this will be outlined in relation to current debates concerning gender and ethnic differences in educational attainment. It will be argued that one way of countering this uncritical use of summary statistics and the ecological fallacy that it tends to encourage, is to make much more use of the principles and methods of what has been termed ‘exploratory data analysis’. Such an approach is illustrated through a secondary analysis of data from the Youth Cohort Study of England and Wales, focusing on gender and ethnic differences in educational attainment. It will be shown that, by placing an emphasis on the graphical display of data and on encouraging researchers to describe those data more qualitatively, such an approach represents an essential addition to the use of simple summary statistics and helps to avoid the limitations associated with them.