SIST EN 16413:2014

2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.Kakovost zraka - Biomonitoring z lišaji - Kartiranje raznovrstnosti epifitskih lišajevLuftqualität - Biomonitoring mit Flechten - Kartierung der Diversität epiphytischer FlechtenQualité de l'air - Biosurveillance à l'aide de lichens - Evaluation de la diversité de lichens épiphytesAir quality - Biomonitoring with lichens - Assessing epiphytic lichen diversity13.040.20Kakovost okoljskega zrakaAmbient atmospheresICS:Ta slovenski standard je istoveten z:EN 16413:2014SIST EN 16413:2014en,fr,de01-julij-2014SIST EN 16413:2014SLOVENSKI
STANDARD
EUROPEAN STANDARD NORME EUROPÉENNE EUROPÄISCHE NORM
EN 16413
February 2014 ICS 13.040.20 English Version
Ambient air - Biomonitoring with lichens - Assessing epiphytic lichen diversity
Air ambiant - Biosurveillance à l'aide de lichens - Evaluation de la diversité de lichens épiphytes
Außenluft - Biomonitoring mit Flechten - Kartierung der Diversität epiphytischer Flechten This European Standard was approved by CEN on 13 December 2013.
CEN members are bound to comply with the CEN/CENELEC Internal Regulations which stipulate the conditions for giving this European Standard the status of a national standard without any alteration. Up-to-date lists and bibliographical references concerning such national standards may be obtained on application to the CEN-CENELEC Management Centre or to any CEN member.
This European Standard exists in three official versions (English, French, German). A version in any other language made by translation under the responsibility of a CEN member into its own language and notified to the CEN-CENELEC Management Centre has the same status as the official versions.
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Page Foreword .3 0 Introduction .4 0.1 Biomonitoring and air quality .4 0.2 Biomonitoring and EU legislation .4 0.3 Biomonitoring with lichens .5 1 Scope .6 2 Terms and definitions .6 3 Principles .7 4 Equipment .8 4.1 Field work preparation equipment .8 4.2 Field equipment .8 4.3 Laboratory equipment .9 5 Sampling . 10 5.1 General . 10 5.2 Sampling objective . 10 5.3 Study type considered . 10 5.4 Sampling design . 11 5.4.1 General . 11 5.4.2 Prior to sampling . 11 5.4.3 Standard tree species selection for a survey . 11 5.4.4 Standard tree parameter . 12 5.4.5 Sampling scheme . 13 5.4.6 Sampling unit . 16 5.4.7 Sampling density . 16 5.4.8 Surveying lichens . 17 5.4.9 Identification in laboratory of critical specimens . 17 6 Lichen species frequencies . 17 7 Recommendations for Quality Assurance and Quality Control . 17 Annex A (informative)
Example of survey sheets . 20 Annex B (informative)
Calculating lichen diversity metrics. 22 B.1 General . 22 B.2 Lichen Diversity Value (LDV) . 22 B.3 Diversity value of the indicators of eutrophication (e.g. LDVN sensu VDI 3957 Part 13). 23 Annex C (informative)
Suitable tree species . 24 Annex D (informative)
Sampling density calculations . 25 Annex E (informative)
Information needed at the end of the survey . 26 Annex F (informative)
Main phases of application of this European Standard . 27 Bibliography . 28
effect indicator organism which can indicate environmental conditions and their modification by either showing specific symptoms (molecular, biochemical, cellular, physiological, anatomical or morphological) or by its presence/absence in the ecosystem 2.5 lichen ecologically obligate, self-supporting symbiotic association of a fungus (the mycobiont, generally an ascomycete) and one or more populations of green algae and/or cyanobacteria (the photobionts), which results in a stable vegetative structure (“thallus”) with a definite morphology 2.6 lichen community biocoenosis assemblage of populations of lichens, whose composition and aspect is determined by the properties of the environment and by their relationship with other epiphytes, animals, etc. 2.7 lichen diversity species richness found on the bark of standard trees at a height ranging between 1 m and 1,5 m, above the base of the trunk at four different aspects (NSEW) Note 1 to entry: See Annex B. SIST EN 16413:2014

The choice of the map scale depends on the study area dimension and on the intended use of the map. Different scale maps will be necessary, both small scale maps for the study areas (e.g. 1:250 000 scale map) and large scale maps (at least 1:25 000 scale maps but also 1:10 000 and 1:5 000 scale maps) that may be useful for the location of the SU in the field. 4.1.2 Geographic Information System (GIS) with land use strata based on the Corine Land Cover nomenclature.
Other important sources of information may be the analysis of aerial photographs, of town and country planning maps, or ecological maps. The topography may also be used as an additional stratum in those regions presenting significant variation in topographical relief. 4.1.3 Identification of SU on the 1:25 000 (or more detailed if necessary) scale map.
The limits of the SU, and of their possible replacements, will be drawn on the map in order to facilitate field work. 4.1.4 Algorithm for random sampling (scientific calculator or statistics software). 4.2 Field equipment 4.2.1 Chemical reagents for spot tests on lichen thalli.
To produce characteristic colour changes. In particular, the most commonly used reagents are calcium hypochlorite (C), potassium hydroxide (K) and para-phenylendiamine dilution (P). 4.2.2 Compass-clinometer, essential to find the correct positioning of the observation grids on the trunk of the selected trees and also to measure bole inclination. 4.2.3 Identification keys.
Keys may be useful to distinguish species in the field (see Bibliography). 4.2.4 Envelopes.
Specimens to be transported to the lab for identification should be placed in separate, labelled envelopes. The use of paper envelopes is recommended to avoid the growth of mould on the lichen samples. 4.2.5 Global Positioning System (GPS) receiver. 4.2.6 Knife.
This is important to remove lichen samples from the bark of selected trees. SIST EN 16413:2014

It is essential to have a lens that magnifies by at least × 10 but a × 20 lens is also recommended for crustose lichens. 4.2.8 Maps. See 4.1.1. 4.2.9 Tape measure: at least a 20 m tape measure: useful for measuring tree circumference. 4.2.10 Observation grid, 10 cm × 50 cm grid (Figure 1), subdivided into five 10 cm × 10 cm quadrats, to be applied to the trunk of sample trees for example by means of rubber bands.
The grid shall be flexible enough to be easily placed on the bole but also sufficiently robust and resistant so as to prevent changes in shape and in dimensions with use.
Figure 1 — Observation grids attached at four aspects along the trunk (see 5.4.8) 4.2.11 Survey sheets: Sampling Unit survey sheet (see Annex A). 4.3 Laboratory equipment 4.3.1 Chemical reagents traditionally used in lichenology.
Solutions of iodine (I), calcium hypochlorite (C), and potassium hydroxide (K), para-phenylendiamine (P). For solution preparation procedures refer to Purvis et al. ([43]). Blotting paper to highlight the spot test reaction on SIST EN 16413:2014

They may be useful for nomenclature and ecological and distributional information of lichen species found in the field. 4.3.4 Optical microscope (required magnification: × 400 up to × 1 000), used for high-power magnification of lichen structures such as asci and spores.
An eyepiece micrometer will also be necessary to measure spore dimensions. Polarisator appliance is also recommended for the determination of several groups of species (e.g. Lecanora spp.). 4.3.5 Stereo microscope (minimum range × 10 to × 60), used for low-power magnification of lichen samples. 4.3.6 Usual small laboratory equipment (tweezers, scalpel or razor blades, microscope slides and cover slips, immersion oil, pipettes). 5 Sampling 5.1 General Sampling is the act or process of selecting a part (the sample) of something (the target population), with the intent of reflecting its quality, style and nature. Since there are many possible designs, and the most effective one depends on the nature of the population being investigated, there is no unique sampling design that can be recommended for all studies. Rather, the probabilistic nature of the sampling design shall always be maintained. The following guidelines are provided in order to drive the main steps in defining the sampling design for individual studies. A synthetic flow chart showing the main steps to be followed is provided in Annex F. 5.2 Sampling objective The sampling objective is to obtain an estimate of the parameter of the response variable (e.g. mean species richness or mean Lichen Diversity Value; LDV) over the study domain with a given precision. The precision level should be expressed in terms of confidence intervals for the defined probability level. It is required that the sampling objective is defined for each study. EXAMPLE Obtain an estimate of the mean LDV for the study domain with a confidence interval ± 10 % of the mean value, at a probability (P) level of 95 %. The computation of estimates and confidence intervals depends on the sampling design adopted. Therefore each study shall define precision and probability levels, taking into account the requirements of the study framework and considering the available resources. 5.3 Study type considered Lichen diversity assessment and monitoring is a typical observational, mensurative study. Studies can be classified with respect to their temporal coverage: a) the study is a baseline; SIST EN 16413:2014

NOTE Four trees of species A, 1 tree of species B, 7 trees of species C and 4 trees of species D are included within the Sampling Unit: — 5.4.3 a): only 4 trees of the species A (Group I) are selected; other possible trees are excluded because they belong to other species of the same bark group (species B), to other bark groups (species C) or to unsuitable species (species D); — 5.4.3 b): 4 trees of species A (Group I) and 1 tree of species B (Group I) are selected; other possible trees are excluded because they belong to other groups (species C) or to unsuitable species (species D); — 5.4.3 c): 4 trees of species A (Group I), 1 tree of species B (Group I) and 2 trees of species C (Group II) are selected; trees of species D are excluded because they belong to other groups or to unsuitable species. Figure 2 — Standard tree selection at plot level, according to different strategies previously agreed for monitoring the study area 5.4.4 Standard tree parameter A standard tree is defined as follows: a) it is a suitable species (see 5.4.3); b) it has a trunk circumference (at 130 cm from the ground level; see Figure 3 for details on how to measure) between 50 cm and 250 cm; c) each exposition (N, E, S, W) has an inclination (at the centre of each grid) < 20°; d) the area of the trunk that is unsuitable for recording (damage, decortication, branching, knots and/or other epiphytes or climbing plants such as ivy, preventing growth of lichens) within each of the 4 grids when summed < 20 %. Note that if the four grids cannot be adequately positioned on the trunk – meeting points c) and d) – some replacement procedures at tree level may be followed (see 5.4.8). Stems that have clear separation below 100 cm above the ground should be considered separate trees. SIST EN 16413:2014

Key a height from the ground level to the lower edge of the grid (a = 1 m) b height to measure the circumference of the trunk (b = 1,3 m) c circumference of the trunk d inclination at the center of the grid e observation grid Figure 3 — Measurement height from the ground level for positioning the lower edge of the grid (1 m) and location for measuring the circumference and the inclination of the trunk (1,3 m) 5.4.5 Sampling scheme 5.4.5.1 General The sampling design varies according to the distribution of the standard trees within the study domain. Different designs are suggested as examples (see also Figure 4), mainly on the basis of ecological homogeneity or heterogeneity of the study domain. In each study, ecological variables to assess homogeneity should be explicitly provided (e.g. altitude, land use, resident population density, vegetation), according to the aim of the study. SIST EN 16413:2014

a) Case 5.4.5.2 a) for a homogeneous area; standard trees abundantly and homogeneously distributed over the study domain Plot sampling: light plot has been randomly selected and defined (7 trees are included). Dark plot has been selected but a priori excluded because it does not contain any trees.
b) Case 5.4.5.3 a) for a heterogeneous area; stratified random design with two strata: agricultural area (dark circles); forested area (light circles) Figure 4 (continued) SIST EN 16413:2014

c) Cases 5.4.5.2 b) and 5.4.5.3 b); standard trees abundantly scattered in clusters over the study domain Cluster sampling. Trees A1 and B1 are included in clusters A and B, respectively, following the criterion of the threshold distance from the centroid of the cluster.
d) Cases 5.4.5.2 c) and 5.4.5.3 c); standard trees scattered infrequently over the study domain Tree-based sampling: trees 2A, 4A and 5A have been randomly selected from among the population of isolated trees of species A. Trees 1B-7B belong to an unsuitable species and are excluded from the tree population. Figure 4 — Examples of different sampling regimes (see 5.4.5) 5.4.5.2 Sampling schemes in ecologically homogeneous areas a) Standard trees abundantly and homogeneously distributed over the study domain: A simple random or systematic design is recommended. Plot sampling is recommended, with sample plots allocated according to a regular grid, with the starting point of the grid chosen at random. b) Standard trees abundantly scattered in clusters over the study domain: Tree-based cluster sampling or two stage sampling are recommended. Firstly define a criterion to identify clusters (e.g. defining a threshold maximum distance between adjacent trees to be included within the same cluster and/or defining a threshold minimum distance for two clusters to be considered as separate sampling units), then identify and list all the clusters and obtain a random sample of them. If the average SIST EN 16413:2014

Standard trees abundant and homogeneously distributed over the study domain: A stratified random sampling design is recommended. Plot sampling is recommended. First, identify strata on the basis of the information available on the heterogeneous ecological variables (e.g. altitudinal maps, land use classification, forest type). Subsequently calculate the sampling density (see below); allocate sample plots on a random basis within the strata, and in proportion to the dimension of the strata. b) Standard trees abundant, scattered in clusters over the study domain: A stratified random sampling design is recommended. Tree-based cluster sampling or two stage sampling are recommended. Firstly, define a criterion to identify clusters (e.g. defining a threshold maximum distance between adjacent trees to be included within the same cluster and/or defining a threshold minimum distance for two clusters to be considered as separate SUs), based on the information available on the heterogeneous ecological variables (e.g. altitudinal maps, land use classification), identify and list all the clusters and obtain a random sample of them. If the average number of standard trees per cluster within the study domain is reasonable (≤ 10), perform measurements on all of them. Otherwise, proceed with two stage sampling: obtain a random selection of trees within the cluster and perform measurements on all the trees selected. Sub-sampling of the sampling units introduces a further source of variability which may affect the quality of the data. It is important to take this into account when performing statistical analysis of the data. c) Standard trees infrequently scattered over the study domain: Use a tree-based stratified random design. Obtain a list of the individual trees per stratum on the basis of the aerial photo and select the sample trees at random. 5.4.6 Sampling unit — Plot sampling: each plot represents a sampling unit. As selected plot size depends on tree density in the study domain, different sizes could be considered. In most cases, a circular sampling plot with a radius of 30 m is recommended. Each plot shall be allocated, centred on a sampling point. All the standard trees in the plot are measured. — Tree-based sampling: each tree or cluster of trees represents a sampling unit. 5.4.7 Sampling density The minimum number of plots to be selected should be calculated on the basis of available sample size formulae for different designs (e.g. [46]). Usually, these formulae require preliminary information on data variability in a given study area, so that a pilot study and/or the revision of data from previous campaigns (or surveys carried out in comparable areas) are recommended before embarking on a formal investigation. Further inputs in terms of expected precision are also required. Practical examples are reported in Annex D. SIST EN 16413:2014
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