[BEN-L]BEN # 394
Adolf Ceska
aceska at telus.net
Thu, 22 May 2008 09:20:38 -0700
BBBBB EEEEEE NN N ISSN 1188-603X
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BBBBB EEEEE NN N N BOTANICAL
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No. 394 May 22, 2008
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aceska@telus.net Victoria, B.C.
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Dr. A. Ceska, P.O.Box 8546, Victoria, B.C. Canada V8W 3S2
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WORKSHOP: ANALYSIS AND CLASSIFICATION OF ECOLOGICAL DATA
Special Three-day Workshop
October 3-5, 2008
ALASKA PACIFIC UNIVERSITY
4101 University Drive, Anchorage, AK 99508
Analysis and Classification of Ecological Data Using JUICE Software: How =
to
Use the JUICE Package in Combination with Turboveg, Twinspan, PC-ORD, =
MULVA,
SYN-TAX, D-MAP, CANOCO and Others to Extend the Possibilities of these
Programs=20
The workshop will be conducted by Drs. Lubomir Tichy & Milan Chytry
Institute of Botany and Zoology, Masaryk University, Brno, Czech =
Republic=20
Description: This three-day course will combine lectures with hands-on
application to teach the basic concepts and advanced features of the =
JUICE
6.5 freeware, computing package based on the Microsoft WINDOWS platform. =
The
workshop will include:=20
1. Vegetation Databanking - Basic Overview
2. JUICE Installation, Management of Species Lists
3. Data Import (Input from TURBOVEG and other Data Formats, Species
Lists)
4. Quality of Phytosociological Data (Plot Size, Preferential Site
Selection)
5. Manual Editing of Vegetation Tables
6. Basic Classifications
7. Concept of Diagnostic Species and the Theory of Phytosociological
Fidelity
8. Synoptic Tables and Automatic Editing of Vegetation Tables
9. Stratified Data Selection from Phytosociological Databases
10. Calculating Species Indicator Values
11. Export Options
12. Measuring Beta Diversity
13. Modified TWINSPAN Classification
14. Comparison of Classifications: OPTIMCLASS Method
15. Formal Reproduction of Traditional Syntaxa: COCKTAIL Method
16. Matching Relev=E9s to Synoptic Tables
17. Expert System for Automatic Identification of Vegetation Units
18. Supervised Classification Methods: Neural Networks, Classification
Trees
19. Ordinations
20. Fitting Species Response Curves
21. Linking Phytosociological Data with Species Trait Databases
22. Defining Species Pools: Beals Smoothing
The workshop will be held at Alaska Pacific University and be limited to =
20
participants. Cost of workshop: $325 (a special price is available for
fulltime students). Checks, Visa, or purchase order should be made =
payable
to "Alaska Pacific University" and sent to: JUICE Workshop, =
Environmental
Science, Alaska Pacific University, 4101 University Drive, Anchorage, =
Alaska
99508; telephone contact for payment is Jeannine Fitzgeralds, =
Environmental
Science Office @ (907) 564-8207; FAX (907) 562- 4276; email:
jfitzgeralds@alaskapacific.edu . Classes from 9:00 -12:00 and 1:00 - =
4:00
pm.
Participants should bring their own laptop computers. Further =
information
concerning the JUICE package may be found on the Web homepage=20
( http://www.sci.muni.cz/botany/juice.htm ); a JUICE Manual will be
available for distribution two weeks prior to the workshop.=20
Questions concerning the workshop should be addressed to: Stephen =
Talbot,
U.S. Fish and Wildlife Service, 1011 East Tudor Road, Anchorage, AK =
99503;
phone (907) 786-3381, fax (907) 786- 3905, email: stephen_talbot@fws.gov =
CONTROLLING SCOTCH BROOM (CYTISUS SCOPARIUS) AND GORSE (ULEX =
EUROPAEUS)
From: Raj Prasad (2003) Management and control of gorse and=20
Scotch broom in British Columbia. Technology Transfer Note
Number 30,
Pacific Forestry Centre, Victoria, British Columbia.
rprasad@pfc.cfs.nrcan.gc.ca=20
MANAGEMENT STRATEGIES
The following control strategies for broom and gorse are recommended =
based
on information and experience gained from the literature, operational =
trials
and research.
RECOMMENDATIONS FOR CONTROLLING SCOTCH BROOM
A. Cutting:
If the adult plants have stem larger than 2 cm in diameter they
should be cut off low to the ground. If the plants are cut when the
carbohydrate food reserves are lowest in the root (after flowering) or =
at
the start of the drought season, the incidence of resprouting should be =
low.
Any sprouts that occur may not survive the drought period in the summer.
=09
If the stems are less than 2 cm in diameter they should be pulled
out, either by hand or with a broom puller, and not cut. Seedlings and
smaller plants have a greater tendency to sprout after cutting than =
adult
plants.
=09
The initial treatment, including chipping, may cost about $ 1000/ha;
the first follow-up treatment will cost about $ 300/ha; the cost of
subsequent follow-up treatments will continue to decline.
B. Cut the plant and treat the stump:
=09
Cutting the adult plants and treating the stumps with a herbicide
(Release) immediately after cutting appears to be an effective way of
killing broom.
=09
A follow-up treatment should be carried out to control emerging
seedlings before they reach 50 cm in height. Since broom seedlings grow =
much
faster , this follow-up treatment may be needed before the second year =
after
the initial treatment, and repeated every few years until the broom =
plants
are totally eradicated from the site. The seedlings should be pulled out =
by
hand and not cut, as cutting promote sprouting.
=20
The cut plant material should be disposed of by burning, chipping or =
removed
from the site, to avoid creating a fire hazard.
RECOMMENDATIONS FOR CONTROLLING GORSE
A. Remove the entire adult plant:
=09
Since gorse is capable of resprouting from cut stems, ideally the =
entire
adult plant should be removed, roots and all.=20
=20
Where practical, adult plants should be uprooted, by pulling or with =
a
brush rake, with the roots left to dry.
=09
This method is not appropriate for sensitive sites or sites with =
species
at risk.
=09
This should be only done on heavily disturbed site, as much soil =
will be
exposed and gorse seeds in the soil will grow as a result.
=09
Due to the high level of ground disturbance, a large number=20
of seedlings can be expected to emerge and should be pulled out
before they become too large.
=09
B. Cut the plant below ground level:
=09
Since adult gorse plants do tend to resprout from roots, the plant =
can
be killed if the stem is cut _at least 5 cm_ below ground level. =
However,
care must be taken because prolific resprouting will result if the stem =
is
cut anywhere above the root.=20
=20
This method is applicable to small areas because it is extremely
difficult and labour intensive.
C. Cut the plant and treat the stump:
=09
Cutting the plant and painting the stumps with a herbicide (Release)
immediately after cutting appears to be the most effective way of =
killing
gorse on most sites.
=20
D. Mulching:
=09
Mulching a large area with uneven terrain is not economical, but
mulching might have some limited application on small, selected areas =
where
other methods cannot be employed.
The uprooted or cut plant material should be disposed of by chipping or
removed from the site to avoid creating a fire=20
hazard. Burning gorse may not be desirable due to the high content of
volatile oils in the branches which creates an oily, black smoke.
Follow-up treatments will be necessary to control the seedlings that =
emerge
from the seed bank. The seedlings should be pulled out by hand before =
they
reach 50 cm in height, and not cut as cutting promotes sprouting. Since
gorse seedlings are fairly slow growing, this follow-up treatment will
likely not be required until the second year after the initial =
treatment. It
should be repeated every few years until the gorse plants are totally
eradicated from the site.
The initial treatment will be the most expensive due to the size of the
adult plants, but follow-up treatment will be considerably less costly =
and
will become less expensive for each successive treatment.
New infestation of gorse should be treated before older infestations.
Younger plants are smaller and therefore easier and less costly to =
remove.
Early eradication also prevents the build up of a large seed bank on the
site.
Priority should be given to removal of gorse within 10 m of roads to =
prevent
spread of seeds by vehicles. Roads should be surveyed once a year for =
new
gorse infestations. These infestations should be removed by pulling the
plants before they seed and create a seed bank.
NEW BOOK: VEGETATION OF THE CZECH REPUBLIC - VOLUME 1
Chytr=FD, M. (ed.) (2007): _Vegetace Cesk=E9 republiky: 1. =
Travinn=E1 a
ker=EDckov=E1 vegetace (Vegetation of the Czech Republic: 1. =
Grassland and
heathland vegetation)._ Academia, Praha, 525 p. ISBN =
978-80-200-1462-7
[hard
cover]
Price: 550.00 Kc=20
Orders can be placed at
http://www.academia.cz/cs/kniha/vegetace-ceske-republiky-1 =20
=20
This is the first volume of the four-volume compendium on the Vegetation =
of
the Czech Republic. The first volume deals with 12 classes, 41 alliances =
and
111 plant associations. These vegetation units were established based =
on
21,794 releves using the computer techniques in the JUICE computer =
program
package (see above).
The project aims at creating vegetation classification of the Czech
Republic, based on the analysis of data from the Czech National
Phytosociological Database and associated with a computer expert system =
for
automatic identification of vegetation units. The results will be =
published
in a four-volume monograph, which will contain descriptions of
phytosociological associations, alliances and classes, comparative =
tables of
species composition, distribution maps and photographs of representative
stands.=20
Individual volumes will contain:=20
1. Grassland and heathland vegetation (2007)=20
2. Ruderal, weed, rock and scree vegetation (2009)=20
3. Aquatic and wetland vegetation (2009)=20
4. Forest and scrub vegetation (2010)
For more information on this project go to the Vegetation Science Group =
web
site
http://www.sci.muni.cz/botany/vegsci/vegetace.php?lang=3Den =20
If you click on the link "Text", you will get a .doc file that contains =
the
unformatted text of this volume. If you do not read Czech, skip the =
first 27
pages and starting with page 28, you will get an excellent English
translation of the introductory chapters.
The "Distribution Maps" will be of little interest to the foreign =
readers,=20
BUT
The "Tables" contain vegetation tables of all the syntaxonomical units
covered in this volume.
EXCERPTS FROM THE INTRODUCTORY CHAPTERS:
The demand by environment protection agencies for consistent and
well-documented systems of vegetation classification led in the 1990s to =
the
implementation of modern national projects of vegetation classification =
in
some European countries, e.g., Great Britain (Rodwell 1990-2000), =
Austria
(Mucina et al. 1993), the Netherlands (Schamin=E9e et al. 1995-1999), =
Slovakia
(Valachovi? et al. 1995, Jarol=EDmek et al. 1997, Valachovi? 2001), =
Germany
(Dierschke 1996) and the German federal state of Mecklenburg-Vorpommern
(Berg et al. 2004).=20
These projects have the following features in common: thorough revision =
of
previously described vegetation units on the basis of a critical
reassessment of large relev=E9 data sets; documentation of accepted
associations using species composition tables; the detailed revision of =
the
nomenclature of vegetation units; and the compilation of the =
distribution
maps of phytosociological associations within the area in question. =
Research
teams have shared their experiences from these projects with vegetation
scientists from other European countries at the annual meetings of the
European Vegetation Survey working group that have been held every year
since 1992 (Mucina et al. 1993c, Rodwell et al. 1995). This working =
group
has also produced the European synopsis of vegetation units at levels
ranging from classes to alliances (Mucina 1997, Rodwell et al. 2002).
Despite a long tradition of phytosociological research and a good level =
of
documentation of vegetation, the Czech Republic did not possess the =
modern
classification of vegetation. In 1995 a decision was made to start to =
work
on a new monograph entitled Vegetation of the Czech Republic. The =
initial,
partial goal was to generate the Czech National Phytosociological =
Database
which would contain the representative sample of relev=E9s from =
different
habitats and regions of the Czech Republic in an easily accessible
electronic format (Chytr=FD & Rafajov=E1 2003). Such relev=E9s existed =
but were
scattered in a number of scientific books, articles, theses, unpublished
research reports, inventory surveys of protected areas, field books and
other written materials maintained by different botanists.=20
Thanks to Professor John S. Rodwell from Lancaster University (UK) and
Stephan M. Hennekens from Alterra - Green World Research in Wageningen =
(The
Netherlands), we were able to use know-how from the British and Dutch
vegetation classification projects from the very beginning of our work =
on
the database. In 1995-1997, John Rodwell arranged a series of courses to
acquaint with the principles of phytosociological database management =
and
particularly with the computer program TURBOVEG (Hennekens 1995, =
Hennekens &
Schamin=E9e 2001). The author of this program Stephan=20
M. Hennekens kindly provided it to Czech users free of charge.=20
TURBOVEG was prepared for use in Central Europe in cooperation with
colleagues from Austria (Ladislav Mucina, Harald Niklfeld, Walter =
Gutermann)
and Slovakia (Milan Valachovi?, Ivan Jarol=EDmek) and in 1996 it was =
made
accessible to all vegetation scientists in the Czech Republic (Chytr=FD =
1996).
In February 1997 Masaryk University in cooperation with John Rodwell
organized a TURBOVEG training course in Brno for colleagues and students
from the Czech Republic and Slovakia. Subsequently, a network of local
TURBOVEG coordinators was established, which covered all major botanical
institutions in the Czech Republic.
Besides the creation of the relev=E9 database, the preparation of the
monograph Vegetation of the Czech Republic also necessitated the =
development
and testing of methods for vegetation classification using large data =
sets.
In the case of data sets with tens of thousands of relev=E9s, standard =
methods
developed for classification of smaller data sets are not suitable or do =
not
allow the potential of these data to be fully exploited. In addition, =
there
has been only very limited experience with how various shortcomings in =
data
quality affect the analysis of large relev=E9 data sets. It was =
therefore
necessary to perform various methodological studies.=20
One of the challenges was to establish a method of selection of =
relev=E9s from
the database which would prevent the negative impact on the resultant
classification caused by the uneven distribution of relev=E9s within the =
Czech
Republic (Knollov=E1 et al. 2005). For vegetation classification on the =
basis
of a phytosociological database, we selected the Cocktail method =
(Bruelheide
1995, 2000). This method creates explicit definitions of vegetation =
units
which allow an unambiguous assignment of every relev=E9 to these units. =
It
thus allows matching of newly obtained relev=E9s to the units of =
established
classification. The Cocktail method underwent comprehensive testing and
modifications and was extended with a procedure that enabled the =
assignment
of relev=E9s to vegetation units based on similarity (Ko?=ED et al. =
2003, Tich=FD
2005).=20
Attention was also devoted to the testing and development of statistical
methods to determine species fidelity to vegetation units (Chytr=FD et =
al.
2002, Tich=FD & Chytr=FD 2006), an important criterion in the =
determination of
diagnostic species and the presentation of vegetation classification in
tables. Chytr=FD & Tich=FD (2003) calculated species fidelities to =
vegetation
classes and alliances of the current standard vegetation classification =
of
the Czech Republic (Moravec et al. 1995), using data from the Czech =
National
Phytosociological Database. Based on this analysis, they were able to
evaluate the quality of delimitation of vegetation units. This work was =
used
as a guideline for identification of (1) which vegetation units from the
current classification should be adopted in the new classification =
system
and (2) which should be eliminated or modified. Since 1998 all methods =
of
analysis of phytosociological data used in the project have been =
included in
the computer program JUICE (Tich=FD 2002), which has become a tool for =
the
comprehensive analysis of phytosociological data and is currently being =
used
by a number of individuals and institutions in many countries worldwide.
References
Berg, C.,J. Dengler, A. Abdank, & M. Isermann. (eds.) 2004.=20
_Die Pflanzengesellschaften Mecklenburg-Vorpommerns und ihre =
Gef=E4hrdung
- Textband._ Weissdorn-Verlag, Jena.
Bruelheide, H. 1995. Die Gr=FCnlandgesellschaften des Harzes und =20
ihre Standortsbedingungen. Mit einem Beitrag zum Gliederungsprinzip =
auf
der Basis von statistisch ermittelten Artengruppen. _Diss. Bot._ 244: =
1-338.
Bruelheide, H. 2000. A new measure of fidelity and its=20
application to defining species groups. _ J. Veg. Sci._ 11: =
167-178.
Dierschke, H. (ed.) 1996. _Synopsis der Pflanzengesellschaften=20
Deutschlands. Heft 1._ Floristisch-soziologische =
Arbeitsgemeinschaft
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Chytr=FD, M. 1996. Datab=E1zov=FD syst=E9m pro projekt p?ehledu vegetace =
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Cesk=E9 republiky. _Zpr=E1vy Cesk=E9 Bot. Spolecn._ 31: 193-200.
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Chytry, M. & L. Tich=FD. 2003. Diagnostic, constant and dominant=20
species of vegetation classes and alliances of the Czech Republic: a
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processing, and presentation of phytosociological data.=20
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_Rastlinn=E9 spolocenstv=E1 Slovenska 2. Synantropn=E1 veget=E1cia_. =
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Hejn=FD, =A9 Hus=E1k, J. Jen=EDk, J. Kolbek, F. Krahulec, Z. =
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Dring, & D. Moss. 2002. _The Diversity of European Vegetation. An
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Tich=FD, L. 2005. New similarity indices for the assignment of=20
relev=E9s to the vegetation units of an existing phytosociological
classification. _Pl. Ecol._ 179: 67-72.
Valachovic, M. (ed.) 2001. _Rastlinn=E9 spolocenstv=E1 Slovenska. 3.=20
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