Sandbox:Ken's Page
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Displaying temporal data: http://webhelp.esri.com/arcgisdesktop/9.1/index.cfm?ID=3553&TopicName=About%20displaying%20temporal%20data&rand=910&pid=3552
Headline text
http://www.issg.org/database/species/ecology.asp?si=946&fr=1&sts=
Methodology: Use spatial interpolation to predict movement, as well as multi-criterion analysis.
17:07:54, Nov 28th. Found a new site, GBIF: http://data.gbif.org/species/13830707/
-A certain pacific ocean point from Obis has been eliminated from the map. 11-28-2007 3:53PM. Latitude: 34.431816 Longitude: -122.399960
Project outline - as of Nov 28, 2007
Objective: To illustrate previous observed range of important threatening aquatic invasive species on the west coast, and to forecast potential future range of the same species. The focus will be on northward expansion, mainly highlighting the potential from the Californian coast to the BC coast.
To do:
i. Collect information on AIS (aquatic invasive species): styela clava, ciona savignyi, didemnum sp.a, Carcinus (green crab) and erochier. (Done)
ii. Collect and input previous observations from pre-1990 to 2005 on various maps to see how they have been expanding in previous years (Done)
iii. Forecast potential range of these species by measuring previous expansion distance, and then repeating that distance (empirical forecast) and place on map
iv. Forecast potential range using the following possible factors/influences/explanations: water current, water temperature, ocean traffic and space/density/carrying capacity and place on other maps.
-Multi-criteria calculations will need to be done on water temperature, water currents and proximity to high-traffic areas. -Maybe use buffering with land layers or high-coast traffic layers? -Normalize criteria -Assign values to criteria to determine how much of an affect it would have -Do weighted response to vary the effect of the four possible factors
v. Write up a report, including abstract, introduction, methodology, results, discussion, acknowledgements and references and create a website
vi. Remember to incorporate some of the things we have learned in this course (Multi-criteria evaluation, reclassification, buffering, flow charts) onto the report
New links of reference:
http://www.exoticsguide.org/species_list.html
http://wascubaalliance.org/tunicates/styelaclava.htm
http://woodshole.er.usgs.gov/project-pages/stellwagen/didemnum/htm/brit2.htm
What:
-Species to Consider:
The list is prioritized according to available abundance data that I have and OBIS distribution maps.
High Priority Invasive Tunicates
Styela clava
Non tunicates:
Carcinus Maenas (Green Crab)
Eriocheir sinensis (Chinese Mitten Crab)
Medium-High Priority Invasive Tunicates
Botrylloides violaceus
Ciona intestinalis
Ciona savignyi
Didemnum sp. A
Low Priority Invasive Tunicates
Ascidia sp.
Ascidia zara
Molgula manhattensis
Styela plicata
Lowest Priority Invasive Tunicates
Botrylloides perspicuum
Botryllus schlosseri
Microcosmus squamiger
Polyandrocarpa zorritensis
Styela canopus
Symplegma reptans
Where:
From Alaskan - Tijuana coastal areas
How:
-Collect data -Input to ArcGIS -Maps:
Theoretical:
Scientifically backed:
1) Growth Rate 2) Carrying Capacity 3) Date/location
Guesswork:
4) Economic activity 5) Environmental factors (pH, salinity, temperature) 6) Competition effects
Emprical map
1) Historical/comtemporary occurence 2) Determining range/year 3) Abundance + density
Map based on previous data
Why:
Tunicates are an important invasive species
INFORMATION LIBRARY/LINKS:
-Docks
http://www.marine.csiro.au/crimp/nimpis/spSummary.asp?txa=6905
-Current abundance/density -Species range -
OBIS
Nisbase
FISHBASE NBII - http://www.nbii.gov/portal/community/Communities/Plants,_Animals_&_Other_Organisms/Fisheries_&_Aquatic_Resources/Species_Projects/ http://filaman.ifm-geomar.de/search.php
List of sites; http://www.gisinetwork.org/Documents/draftiasdbs.htm
Styela Clava
http://www.iobis.org/OBISWEB/ObisControllerServlet?category=all&names=data&tableName=0&searchName=styela++clava#
http://www.issg.org/database/species/ecology.asp?si=951&fr=1&sts=sss
http://nas.er.usgs.gov/queries/FactSheet.asp?speciesID=1292
Botryllus Schoressi
Botrylloides violaceus
Styela plicata
http://www.issg.org/database/species/ecology.asp?si=952&fr=1&sts=sss
http://nas.er.usgs.gov/queries/FactSheet.asp?speciesID=1293
Ciona savignyi
http://www.iobis.org/OBISWEB/ObisControllerServlet?searchCategory=/AdvancedSearchServlet&genus=Ciona&species=savignyi&Subspecies=&sciname=Ciona%20savignyi&comName=null&organismType=a%20sea%20squirt%20(ascidian)&nameVerifiedBy=&nameAttributionUrl=
http://nas.er.usgs.gov/queries/FactSheet.asp?speciesID=1285
microcosmus squamiger
Ciona intestinalis
http://www.iobis.org/OBISWEB/ObisControllerServlet?searchCategory=/AdvancedSearchServlet&genus=Ciona&species=intestinalis&Subspecies=&sciname=Ciona%20intestinalis&comName=null&organismType=a%20sea%20squirt%20(ascidian)&nameVerifiedBy=Catalogue%20of%20Life;%20ITIS&nameAttributionUrl=%26nbsp%3B%26nbsp%3B%3CA+href%3D%22http%3A%2F%2Fwww.itis.usda.gov%2F+%22+class%3D%27in-link%27+target%3D%22_blank%22%3EITIS%3C%2FA%3E%26nbsp%3B%26nbsp%3B%26nbsp%3B%26nbsp%3B%26nbsp%3B%26nbsp%3B#
http://nas.er.usgs.gov/queries/FactSheet.asp?speciesID=1284
Green Crab / Carcinus maenas http://www.iobis.org/OBISWEB/ObisControllerServlet?category=all&names=data&tableName=0&searchName=green+crab
http://www.issg.org/database/species/distribution.asp?si=114&fr=1&sts=sss
Ascidia zara
Ascidia sp.
http://www.iobis.org/OBISWEB/ObisControllerServlet?searchCategory=/AdvancedSearchServlet&genus=Ascidia&species=sp.&Subspecies=&sciname=Ascidia%20sp.&comName=null&organismType=a%20sea%20squirt%20(ascidian)&nameVerifiedBy=&nameAttributionUrl=
http://www.issg.org/database/species/ecology.asp?si=1126&fr=1&sts=sss
styela canopus
polyandrocarpa z-
symplegma reptans
molgula manhattensis
botrylloides perspichuum
didemnum
http://www.iobis.org/OBISWEB/ObisControllerServlet?searchCategory=/AdvancedSearchServlet&genus=Didemnum&species=&Subspecies=&sciname=Didemnum%20(unspecified)&comName=null&organismType=a%20sea%20squirt%20(ascidian)&nameVerifiedBy=&nameAttributionUrl=
Chinese Mitten Crab
http://www.issg.org/database/species/distribution.asp?si=38&fr=1&sts=sss
Polyandrocarpa zorritensis
symplegma reptans
Background information and sources
http://www.cwf-fcf.org/invasive/chooseSC.asp
http://www.pac.dfo-mpo.gc.ca/recfish/Species/shellfishID_e.htm
Assignment 1: Paper Review Logging residues from regeneration fellings for biofuel produciton - a GIS-based availability analysis in Finland
Tapio Ranta
This paper deals with the subject matter of using forest fuels as energy in Finland. The current issue is that its usage has been limited so far and biofuels have not yet been tapped to potential. However, future growth is expected of the resource for usage in industrial and municipal power and heating plants, much of which the sources would arrive from logging residues of regeneration fellings of the trees. As harvesting these fuels is highly dependant on their spatial properties and locale, the author uses in his paper a GIS model to perform spatial analyses in finding the availability and the least-cost most efficient pathways in harvesting these biofuel supplies. The ultimate objective is to minimize the total transport cost as a product of demand and distance.
The author's main argument in supporting his research is that the potential and supply-cost of these biofuels are highly site specific, and that regional resource and infrastructure characteristics can highly affect the potential of using that location as a biofuel supply point. In other words, as regional variations in availability, so do the level of supply costs. The GIS model's aim is to calculate these regional characteristics in order to identify what spatial locations would be best to supply and deliver the biofuels.
The basis for his research derives from the importance of using wood derived energy when other alternatives are available. Wood fuels in Finland already account for 20% of the annual primary energy supply, and there is much to gain from increasing the amount of wood fuel resources for the economy. One of the most underused potential sources of wood fuels are forest chips from tree fellings, and that is where the author believes the most major growth will occur in.
The problem originates from increases in supply costs mainly from an increase in transportation distances. Transportation costs will involve the infrastructure and distribution of the supply locale in relation to the end user, and was approached in the paper through a location-allocation modelling process which attempts to find the optimal location of new facilities and supply existing facilities through the least amount of costs.
The methodology centers aroudn using a GIS model, based on stand data to analyze spatial differences of forest fuel resuorces. The variation of forest fuel resources between different regions was analyzed to fin the mots suitable regions to increase forest fuel usage in Finland. Resource focused analysis, fuel resources were clustered through locaiton-allocaiton modelling to find optimal locaionts to set up harvest plant. Forest fuel resource was allocated ccording to transport distance minimization without factoring in demand-side constraints. Matching between the forest fuel resource and demand side occurerd to analyze deficit/surpus areas.
Modelign stage in the paper: 1. GIS-analysis of primary data including geographic location of demand side and supply resources, distance calculations between geographica entities, queries and filtering according to location attributes.
2. Supply-cost calculation: supply chain, policy/logistics
3. Allocation: allocating the supply resources between demand sites from overlapped supply areas an dfor finding optimal olcation soccrding to supply resources. Location-allocation modeling was used to pinpoint most feasible plant sites.
4. Reporting, illustrating with the GIS maps the supply cost and availability using garphic maps.
-other forms of analysis? Results: is the evidence valid?
The objective of the GIS analysis
and the author wishes to explore The issue that this paper attepts
Purpose of the study: Evaluate availability of logging residues for biofuel production using a GIS availability analysis.
Vertical mapper grouped and statistically merged the data if shit was in close proximity (potential for error?). Assign area data to set of points belonging to subregions.
Using this aggregated stand data, natural neighborhoods were built around the points with Delanay triangulation. Thiessen polygons were generated from point locations. Assume uniformly spread residue over entire area of geographic objects.
Effects of regional geography were analyzed – 100km supply transport distances along road network. Assumption that no road network was going to exceed 100km in supply.
p-median problem – optimal locations for p facilities relative to supply points or supply zones. Transport-cost minimization and allocation element of the problem came through
Results show logging residue per unit area varied by region. Large potential = shorter distance.
Logging residue availability according to transport distance expressed in GWh. Availability maps illustrate effect of regional geography to potential, show advantages of inland areas – possible to collect same logging residue volume.
Straightness – accessibility via road network to forest fuel sources
Subject: Using forest fuels, produced from logging residues of fellings.
Issue: Identify the availability of logging residues, by means of resource and demand. Look for suitable regions to focus on increasing forest fuel usage.
GIS is implemented with spatial analyses, which reveal that supply potential of these forest fuels at different locations can differ a lot. Calculating the costs of the potential and supply of these forest fuels depend on specifics of the site where its regional characteristics of resources and infrastructure should be taken into consideration by using a GIS-modeling approach which was done in this paper.
Supply potential is limited to the plant level.
The purpose of this paper is to
-Purpose -Topic of the main argument -Key points relating to main argument -Methods -Are they appropriate -Evidence? Validity? -Rating
-Wood energy is important in Finland.
Mar 19: Sciteam event - GAPS, Registration deposit due + Summer Registration + Course Research
Mar 24: G471 Crime Analysis + GIS Review
Mar 26: Sciteam Event
Mar 31: G471 presentation
Apr 2: Wed: Case study due PHIL435
Apr 8: G304 Lab Exam
To-do
-Ongoing: G471 / MURP Project - Research Marina data by Wednesday
-Email Deng, IAIA
-Deposit to CT Bank: May 3rd
-Stop Fund payment
-Canadalife
-Air filter
-Sell phone
- AMS Internships
- FSWEP
- career fairs
- goodplanet
Next semester: Take two Econs for night classes, or one econ + FNH 330 -Decide between FNH 355 or FNH 330... -MUSC 326!
What options I have this summer:
Plan A: Math 200 Econ 334 Econ 370 Econ 442
Winter Term 1 Econ 355 Econ 455 Term 2 Econ 365 DET something easy ie MUSC 326
997
remind lady of work in July
References http://archive.casil.ucdavis.edu/casil/uncategorized/legacy.ca.gov/Hydrology/hydro/ http://www.dot.ca.gov/hq/tsip/gis/datalibrary/gisdatalibrary.html http://www.mtc.ca.gov/maps_and_data/GIS/data.htm http://www.google.ca/search?q=california+harbor+OR+harbour+OR+port+traffic+GIS+data&btnG=Search&hl=en&client=firefox-a&rls=org.mozilla%3Aen-US%3Aofficial
http://www.canada.com/vancouversun/news/story.html?id=ed614ea0-4816-44fc-9804-f072252668e1