Conservation Mapbook ESRI

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Esri ConservationMap Book


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Table o Contents

Creativity

4 Help Conserve Coral Rees

Innovation6 The Land Protection History o The Nature

Conservancy in New York

8 Climate o the United States or Continental andMultiscale Conservation Eorts

10 Priority Work Area Map in Western NorthCarolina

14 Baleen Whales Relative Distribution

Science

18 Global Nest Distribution o Green Turtles(Chelonia mydas)

22 Sea Lice (Lepeophtheirus salmonis) on JuvenilePink and Chum Salmon

26 Planning or Conservation in the RuvumaLandscape

30 Regional Conservation Design o the SouthernSierra Partnership

34 Conservation Lands Network

38 Evolution o the System o Protected Areas oMadagascar

40 Sea Turtle Stranding Probability

42 Limpopo National Park (Mozambique)

Social Impact

44 Urban Forest Restoration Sites

48 Connecting Wildlie and Water Networks

52 Zonication o an Indonesian Archipelago

54 Invasive Tree Map

Traditional

58 What Weve Accomplished in Martis Valley

62 Black Bear Bait-Station Surveys in Saskatchewans

East Boreal Plains64 Zooming in on the Secret Lie o Genetic

Resources in Potatoes: High Technology MeetsOld-Fashioned Footwork

68 Conservation Accomplishment & Opportunities

Web

70 Migratory Birds within the Arica-Eurasia Region

74 The Canadian Wetland Inventory Progress Map

78 Conservation o Americas Natural Places


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The Esri/Society or Conservation GIS (SCGIS)

International Conservation Mapping Competition

was organized to nd and recognize the best

conservation mapping work in the world today. We

specically used the term mapping to take in the

wide variety o digital and online work that have

expanded our concept o mapping well beyond

static paper maps. In all, we received more than

100 entries representing countries and projects

rom around the world. We are especially grateul

to the international SCGIS or its critical role in

reviewing and judging all the entries. Composed

o conservation GIS practitioners and senior

organization sta rom every major nonprot

conservation group and many environmental

agencies and businesses, SCGIS is the oremost

society representing and supporting conservation

GIS proessionals worldwide.

Charles ConvisEsri Conservation Program Coordinator

See Esri GIS orConservation atesri.com/conservation.

Esri and SCGIS assist conservationist worldwide in using

GIS through communication, networking, scholarships,

and training. This support builds community and

provides tools or the work o conservation science and

action. Learn more about SCGIS at scgis.org.


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Help Conserve Coral ReesBy Melissa McVee, Jan-Willem Bochove, Lorrae Guilfoyle

Coral Cay Conservation

London, United Kingdom

Data Sources

Surveying point data: Coral Cay Conservation, Tobago boundary and contours:

Buccoo Ree Trust

Coral Cay Conservation (www.coralcay.org) is a not-or-prot organization based in the

UK that works with volunteers in developing countries to research and monitor their

coral rees or conservation purposes. They have survey sites in Tobago, the Philippines,

and Cambodia. As well as providing scientic research and training, the organization

works toward incorporating and involving local communities to ensure sustainable,

workable outcomes with them and their local marine environments.

Coral bleaching is usually caused by prolonged periods o unnaturally high water

temperature, increasing ocean acidity, sedimentation, or pollution. These actors are

increasing because o climate change. These environmental stressors cause small algae

called zooxanthellae, which live saely within the tissue o the coral, to be expelled.

Zooxanthella is a cohost. In exchange or shelter, it can provide up to 90 percent o the

ood needed or the corals survival. I the expelled zooxanthellae do not return to the

coral, the coral will slowly die and turn white.

The coral ree map was designed to entice people to work with one o Coral Cays

survey areas o Tobago. In this case, the work would involve assisting in monitoring the

eects o coral bleaching. The document uses emotional language, illustrations, and

mapping within a scientic ramework. Engaging the viewer was essential, as Coral Cay

Conservation is reliant on a volunteer work orce to continue its scientic research.

The map is simple and clear in its intention to show the devastating eects o bleaching

over an area. The highly stylized approach is meant to engage but not overwhelm the

reader with the scientic inormation available about the impact o coral bleaching

ound around the coastline o Tobago.

Colors, rather than topography details, were used. The whites and reds o high

bleaching amounts were used to invoke a eeling o devastation, contrasting strongly

with the lush greens o land.

Support or this project was provided by Coral Cay Conservation, London, UK.

CreativityHonorable Mention


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InnovationFirst Place

The Land Protection History oThe Nature Conservancy in New York

By Brad Stratton and Kate Hubbs

The Nature Conservancy

Albany, New York, USA

Data Sources

The Nature Conservanc y, USGS 30 m NED

During the past 55 years, The Nature Conservancy (TNC) in New York has protected

or helped protect 700,000 acres o land. The Land Protection History o The Nature

Conservancy in New York map highlights the extent o the organizations land

conservation eorts. It shows

Landtracksbysite

Clustersofindividualparcelsaroundaprimaryconservationhotspot

Fees,transfers,casements,andtransactionassistance

Transactionsbytype(fees,transfers,casements,andassists)andnumberofacres

Timelinegraphofcumulativeacresconserved

The map is a milestone in the ve-year eort to create a comprehensive GIS database

o all TNC land transactions. The project team tracked down paper deeds and surveys

rom the last hal century to properly code the spatial data.

This map has been viewed by primarily TNC sta. It has helped them recognize that

knowing the organizations conservation history is vital in understanding its present.

This map helps people celebrate the organization in a way that a ew numbers exported

rom a database could never do.


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InnovationSecond Place

Climate o the United States or Continentaland Multiscale Conservation Eorts

By Hans Edwin Winzeler, Phillip R. Owens, and Zamir Libohova

Purdue University

Gettysburg, Pennsylvania, USA

Data Sources

PRISM Climate Group (Oregon State University), SRTM digital elevation model

The purpose o this project is to provide a continuous classication o climate and a

method or visualization o complex inormation using three color ramps combined in

one red, green, blue visualization. It oers a method o visualizing climate that can be

used in models o soil moisture, wetland preservation, species diversity eorts, and

other natural resource management tasks. A continuous classication avoids discrete

boundaries, which oten do not exist in nature.

This map displays temperature, rainall, and seasonality (a Mediterranean index that

measures the strength o annual precipitation imbalance) using red, green, and blue.

These measurements have traditionally played an important role in the understanding

and classication o climate.

First, a standard deviation histogram stretch (n = 2) was applied to allow greater

visualization o contrasts between high and low ranges o the histogram o values.Second, red, green, and blue rasters were combined into a single climate raster or

visualization.

The climate inputs will be applied to the Newhall Simulation Model, which is a

detailed simulation o soil moisture, to estimate soil moisture or the coterminous US

at multiple scales. The understanding o soil moisture has important implications or

wetland conservation, species diversity and management, and many other natural

resource planning and management decisions. Hans Edwin Winzeler and his team are

developing visualizations and estimates o soil moisture that can be used by natural

resource planners at multiple scales.

Using choropleth classications o climate, such as those o Koppen, with discrete

categories, requires detailed documentation o those categories, as well as conceptualrealization by map users. Continuous classications can consist o measured values,

such as 30-year climate inputs, on a pixel-by-pixel basis that can be more meaningul

and, we believe, easier to interpret. Continuous classication also avoids implied abrupt

boundaries between natural zones that may, in reality, have gradual boundaries.


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Priority Work Area Mapin Western North Carolina

By Mark Endries

US Fish and Wildlie Service

Asheville, North Carolina, USA

Data Sources

The Audubon Society, US Environmental Protection Agency, North Carolina Division o

Water Quality, Esri, US Gap Program, North Carolina Department o Environment and

Natural Resources, North Carolina Department o Transportation, North Carolina Energy

Oce, North Carolina Natural Heritage Program, North Carolina Wildlie Resources

Commission, One North Carolina Naturally, United States Department o Transportation,

US Fish and Wildlie Service, US Forest Service, US Geological Survey, Wildlands

The US Fish and Wildlie Services Asheville Field Oce (AFO) is responsible or

reviewing endangered species compliance or all ederally authorized, unded, and

permitted projects and implementing listing and recovery activit ies or ederally listed

endangered and threatened species and candidate species o concern in western

North Carolina (WNC).

AFO used GIS to develop a work area habitat prioritization map that incorporates awide variety o land-use, land-cover, and wildlie species data. It ranks the AFO work

area landscape on a 110 scale based on ederal trust resource priorities o the sta.

GIS is an ideal tool or regional assessments o landscapes, development and application

o habitat models, and modeling o the potential distribution o species and habitats. It

assists in the resolution o land-use confict and the management o natural resources.

Digital habitat and wildlie data is used to identiy environmentally sensitive lands. GIS

users can view their projects in a landscape perspective. Habitat quality and wildlie

needs can be simulated, which is useul or proposing management plans.

To begin the mapping process, all the available spatial data relevant to wildlie in

western North Carolina rom 15 agencies was compiled and processed into 24 GIS data

layers. These layers were organized into two categories: layers benecial to ederal trustresources (benecial layers) and layers that are threats to ederal trust resources (threat

layers). All map input layers were classied on a 010 scale. The rank o 10 is assigned to

the most benecial layers, and 10 again to greatest threat layers. By doing this, all layers

were scaled the same using an easy-to-understand range o values.

The ArcGIS Desktop Grid stackstats command calculated a correlation analysis and

identied signicant correlation between the data layers. Signicant correlations

among data layers were resolved by removing eight layers rom the modeling process.

Next, AFO sta ranked each map input layer on a 110 scale based on perceived benet

or threat to ederal trust resources, and an average layer rank was calculated or each

InnovationThird Place


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Priority Work Area Map in Western North Carolina(continued)

map input layer. To calculate the nal map, all map input layers were multiplied by their

AFO rank and summed by category (benet or threat).

The nal step was to subtract the sum o the threat layers by the sum o the benecial

layers and classiy the result into a 110 scale. For the nal map, a high score indicates

an area that ranked high in the benecial input layers (numerous benets) but low in the

threat input layers (limited threats). A low score indicates an area that ranked low in thebenecial input layers (limited benets) but high in the threat input layers (numerous

threats). AFO generated a custom 10-class color ramp or this map to highlight the

high-ranking areas. Colors scale rom light gray to dark gray, light green to dark green,

yellow, orange, then red as the values in the nal map increase rom 1 to 10. As the

values increase, the colors become hotter, which is similar to how a weather map shows

intensity o storms.

The perspective image o the nal map was created using Esris 3D tools. Placing small

images o each model input data layer above this perspective image makes data layers

appear to hover over the map. A blue arrow tree (center in the poster) was used to point

rom each map input data layer downward, combining into a single arrow and pointing

to the nal map. This blue arrow tree graphically represents the actual combining o

each individual model input layer and draws the viewers eyes down to the nal map. Allthis inorms the viewer without any text that the data layers were combined to create

the nal map.

The AFO work area prioritization map data is provided in a le geodatabase along with

all the input data layers and is oered to users ree o charge. Data in this ormat gives

users GIS capabilities to perorm urther analysis or inquiries with the data. For example,

by using the Identiy tool in ArcGIS, users can identi y individual pixel values o the work

area prioritization map results and any map input data layer at specic locations. They

can then understand the impor tance o each map input data layer at specic locations.

People can use their own data in conjunc tion with the work area prioritization data. They

can also customize and recalculate the work area prioritization by adding or removing

data layers to better t the specic task at hand. This capability improves the utility o

the work area prioritization map by giving it the fexibility to suit the needs o specicprojects or queries. As new or better data becomes available, AFO will update the map

to keep it as current and accurate as the data available.


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Innovation

Baleen Whales Relative DistributionBy Brooke Wikgren and Kerry Lagueux

New England Aquarium

Boston, Massachusetts, USA

Data Sources

Right Whale Consortium Database, Esri; US Geological Survey

Marine spatial planning can mitigate conficts between existing and uture ocean

uses. Determining the relative spatial distribution o marine animals has become

increasingly important. Traditional distribution analyses based on survey sightings

can create highly variable spatial data and is greatly dependent on survey eort. To

help account or this, a methodology was created that incorporates survey eorts

with sightings data, resulting in an index termed sightings per unit eort (SPUE).

It involves assigning calculated SPUE values to spatially explicit gridded cells based on

latitude and longitude.

SPUE is useul or correcting possible bias in survey eorts and quantiying sighting

requencies. SPUE values are computed or consistent spatial units (numbers o animals

sighted per unit length o survey track) and can thereore be mapped or statistically

compared across areas, seasons, years, etc.

The study area was partitioned into a regular grid based on latitude and longitude using5 x 5 minute cells.

Aerial and shipboard survey tracks were broken down into grid cells and their lengths

computed. Sightings were also assigned to cells, and the numbers o sightings per

species were summed by cell. The number o animals in each cell was divided by the

eort value and multiplied by 1,000 to create a SPUE index in units o animals per 1,000

km o survey track.

SPUE was provided rom the Right Whale Consortium database and consists o sightings

and survey eorts rom 1978 to 2009. The SPUE results were summarized to grid cell

center points and presented in dBASE les containing the species, SPUE calculation,

latitude and longitude o 5 x 5 minute cell center points, season (annual, spring, summer,

autumn, and winter), number o animals, and kilometers o track line eort. Annual data

or a species grouping o all baleen whales was used. The dBASE le was imported intoArcGIS using the latitude and longitude o the 5 x 5 minute center point locations in the

WGS 1984 geographic coordinate system and exported into an ArcGIS point eature

class inside a le geodatabase.

The eature class was projected into UTM Zone 19 North, North Amer ican Datum 1983,

or the kriging interpolation, which was perormed by ArcGIS Geostatistical Analyst.

The resultant point dataset was a regularly spaced grid o points with SPUE values or

the annual distribution or all baleen whales.

Spatial autocorrelation is the tendency o locations closer together to be similar in

values, and this relationship can be modeled using a semivariogram dur ing the kriging


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Baleen Whales Relative Distribution (continued)

process. The Gaussian semivariogram model was used to weight the points in the search

neighborhood to determine the spatial prediction. The average nearest neighbor o the

SPUE points was used as the lag size along with a deault o 12 or the number o lags.

A smoothing actor o 1 (the maximum) and a major and minor semiaxis o 20 km to

include at least six points in the calculations were used or the predictions. The

smoothing neighborhood decreased the interpolated surace values by approximatelya actor o 10. Distributions matched the overall SPUE point distributions, and the

interpolated surace provided the relative abundance or all baleen whales.

The nal model o the annual distribution o all baleen whales was exported rom an

ArcGIS geostatistical layer to an ArcGIS raster grid with a 250-meter cell size. Any

negative values as a result o the interpolation were reclassied as zero. The raster grid

was mapped and symbolized on a stretched scale representing baleen whales relative

to SPUE.


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ScienceFirst Place

Global Nest Distribution oGreen Turtles (Chelonia mydas)

By Andrew DiMatteo, Bryan Wallace, Brian Hutchinson, Rod Mast, Nicholas

Pilcher, Jeffrey Seminoff, Andrea Whiting, Kellee Koenig, and Miya Su Rowe

Duke University

Norolk, Virginia, USA

Data Sources

State o the Worlds Turtles database (includes data contributed by SWOT team

members and reviewed literature), Natural Earth (Tom Patterson, NPS), GSHHS

Marine turtles are highly migratory, widely distributed marine megaauna. Several

populations have experienced signicant declines in recent decades. Most marine

turtle species have circumglobal distributions that extend rom tropical to temperate

latitudes. Distinct populations o the same species can show variations in body sizes,

reproduction habits, and population trends. Thus, regional and local conservation

eorts can be better directed and placed in context when the broader, global,

biogeography o a species is understood.

This map o green turtles (Chelonia mydas) is the culmination o six years o data

collection eorts and displays more than six times the number o nesting sites thanthe original map produced in 2005, which eatured leatherback turtles. Approximately

1,200 green turtle nesting sites are displayed in every tropical and subtropical ocean

region around the globe.

Since 2005, the State o the Worlds Turtles (SWOT) project has compiled data on

marine turtle nesting colonies worldwide through cultivation o a network o hundreds

o data providers that share annual nesting abundance data. Each year, SWOT

releases a print magazine that highlights inspiring and interesting stories o sea turtle

conservation successes and challenges, and the centerpiece is a map o the global

nesting biogeography o one species. These maps are the most comprehensive, up-

to-date geographic representation o sea turtle nesting distributions and abundance

in existence.

Among several challenges in creating this map (beyond the six years o data collection

rom over 500 sources), oremost was the sheer amount o data to be included. Not only

were there almost 1,200 sites to display, but they also span the globe and need to be

scaled by the size o the nesting colony.

The decision to keep the global extent o the main panel intac t meant that the density o

sites necessitated the creation o numerous insets around the periphery so that people

viewing the map could discern individual sites. The creation o insets both alleviated

and complicated the issue o annotating the map.

Because SWOT prioritizes proper attribution o every data point to its original provider,

each site is linked to a data record ound in the back o the magazine, and painstaking


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Global Nest Distribution o Green Turtles (continued)eorts are made to label each site. The insets help ensure that this connection was easy

to make, but the inset titles also take up room on the main map. Many sections o the

map went through several versions o annotation beore the right balance between

clarity o labeling and density o inormation was reached.

Inset design also represented a challenge, as in many cases, nesting sites were so closely

spaced that bleed-over between insets was a concern. Some insets were at such a smallscale that the Natural Earth background layer appeared uzzy. In these cases, higher-

resolution polygons were created using coastline data rom the Global Sel-consistent

Hierarchical High-resolution Shoreline (GSHHS) dataset. Additionally, insets needed to

be laid out in such a way as to be easily ound rom their reerence points on the main map,

limiting what order they could be placed in and how much space they could be allocated.

The map also needed to convey inormation about turtle distribution and abundance

patterns, as well as the quality o the data used to make the map. Two important

attributes are displayed or each nesting site: colony size (including a class or sites that

are not quantied) and a binary classication as to whether the data shown had been

collected in the last ve years. Classication o abundance by symbol size allows viewers

o the map to roughly quantiy the abundance value o each point. By then reerring to

the data record in the back o the map, they can nd the exact count provided by thecitation or data provider. A transparency gradient was used to represent increasing

abundance across nesting sites, thereby acilitating interpretation o numerous sites

that were clustered spatially. A white halo was given to sites where data was collected

in the last ve years, and a gray halo to others, to subtly but clearly convey inormation

about quality and accuracy o data.

The end result o collating many hundreds o data points rom hundreds o distinct

sources rom around the worldwhile balancing data quality with being as inclusive as

possibleis a visually compelling, multilayered, inormation-rich map that will draw in

audiences rom scientic researchers to casual observers to explore the dynamic and

detailed world o green turtles.

This map was made under the auspices o the State o the Worlds Turtles project.

Dr. Bryan Wallace, chair o the SWOT Scientic Advisory Board, can be reached [email protected].


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Leg

Pie

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ScienceSecond Place

Sea Lice (Lepeophtheirus salmonis)on Juvenile Pink and Chum Salmon

By Karin Bodtker and Carrie Robb

Living Oceans Society

Sointula, British Columbia, Canada

Data Sources

British Columbia Ministry o Agriculture and Lands (BC MAL) updated by Living

Oceans SocietyMarch 2008

Sea lice (Lepeophtheirus s almonis) are small parasites that occur naturally on many

dierent species o wild sh. They attach to the outside o marine sh, usually the skin,

ns, or gills, and eed on the mucus, blood, and skin o their host sh. A ew lice on a

large salmon may not cause serious damage, but many lice on an adult sh or just one

louse on a juvenile salmon can be harmul or atal. Salmon arms are typically located in

sheltered bays and inlets near rivers on or near the migratory routes that juvenile salmon

use to reach the ocean. The adult sh living in high densities in salmon arms provide

unnatural reservoirs o sea lice that juvenile wild salmon must swim past as they head

or the ocean. Beore commercial-scale salmon arming began, sea lice numbers were

typically low in the spring, during the time o juvenile migration, because the number o

available hosts in coastal areas was also low.

Juvenile salmon are especially at risk to sea lice because o their small size and the

stresses associated with changes that occur when they enter saltwater. Just one or two

sea lice are enough to kill a juvenile pink salmon newly arrived in saltwater. Much higher

numbers have been observed recently on juvenile pink salmon near salmon arms in

British Columbia (BC), Canada.

A substantial and growing body o research published in peer-reviewed journals began

to demonstrate that sea lice were dangerous to wild salmon. Cutting-edge research

published in the journal Science in December 2007 was the rst study to calculate the

impact individual wild salmon mortalities have on the population o a whole run.

Living Oceans Society is Canadas largest organization that ocuses exclusively on marine

conservation issues. It is based in Sointula, a small shing village on the central coast oBritish Columbia.

Living Oceans Society decided to create a map that would allow readers to easily weigh

the evidence. The majority o data ocused on pink and chum salmon, so the map

represents the problems o sea lice on juvenile pink and chum salmon in BC. The map

presents the best available science related to transmission o sea lice rom open net-

cage salmon arms to migrating wild juvenile salmon and puts the dierent studies into

a single geographic context.

The basic question posed by various scientic papers was relatively straightorward:

Do wild juvenile salmon that migrate past open net-cage salmon arms have a higher


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Sea Lice (Lepeophtheirus salmonis) onjuvenile pink and chum salmon in BC

VancouverIsland

Skeena River(no exposureto fish farms)

Rivers Inlet(no exposureto fish farms)

Smith Inlet(no exposureto fish farms)

Gulf Islands(peripheral

exposure 2003,no exposure

2004-2005)

ce Rupertexposuresh farms)

Klemtu /

Bella Bella

BroughtonArchipelago

Licensed Salmon Farm(may not be active all years)

Sample Site Status (per Morton et al. 2008)

20046,240 Fish

Exposed toFish Farms

52003 2004 2005 2004

NotExposed

Peripheral

Site Status

200512,245 Fish

20062,963 Fish

66 Fish

462 Fish

2,134 Fish

096 Fish 2,082 Fish

1,558 Chum, 620 Pinksplit equally between groups

619 Fish

13,874 fish sampled, divided equallyamong groups for illustration

552 Fish

1

2

2002

566 Fish

2002

250 Fish

2002

48 Fish

3

3

3

2003 2004 2005

1,126 Fish1,313 Fish1,408 Fish

5

2003 20052004

2002

2,149 Fish1,086 Fish676 Fish

537 Fish

491 Fish

Site Status


(fallow 2003)2005 2006 2007

fected Chum

fected Pink

ninfected Chum

ninfected Pink

64

3

5

Not exposed *

Peripheral *

Exposed to fish farms *

ample size * Colour coded by study


NotExposed

Site Status

(near but not betweenfish farms)


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Sea Lice (Lepeophtheirus salmonis) on Juvenile Pinkand Chum Salmon (continued)

sea lice inection rate than those that do not migrate past salmon arms? However, the

studies exhibited more dierences than similarities. For example, juvenile wild salmon

were sampled in dierent regions o BC and at dierent locations, using sample sizes

that diered by orders o magnitude. Two dierent salmon species were sampled, but

both species were not sampled in all studies. Some studies sampled control areas

geographically removed rom salmon arms. Lastly, the rates o sea lice inection were

presented dierently by dierent authors.

Map authors Karin Bodtker and Carrie Robb compiled the relevant published work,

requested and obtained GIS data or geographic coordinates when available, and

digitized juvenile salmon sampling locations rom published illustrations when necessary.

They needed to represent sample site status by indicating whether sh sampled at each

site had migrated past salmon arms or not and showing which sites were related to

which published study. They wanted to present inection rates by study, year, salmon

species, and site status and report the number o sh sampled in each case. Finally,

they needed to list the ull citation or all the published (and one unpublished) sources

o data. The map was created entirely within ArcGIS. Living Oceans Society made this

map available or viewing and or download on its website and provided a printed copy

to colleagues working on this issue who, in turn, used it as a communication tool to help

summarize the state o scientic knowledge to others, including government, industry,and unders. The map served as a catalyst or discussion.

In June 2008, Marine Harvest Canada agreed to coordinate the stocking o its arms

in the Broughton Archipelago region to establish saer migratory routes or the wild

salmon as they make their way rom the rivers to the open ocean. This migration corridor

plan is expected to provide interim protection or some o the threatened wild salmon,

but it is not a permanent or widespread solution to the conservation issue. Ultimately,

open net-cage salmon arms must transition to closed containment to ensure the long-

term health o our oceans.

More and more science is indicating that the impact o sea lice rom salmon arms

has a much greater reach than was previously studied. Results now suggest that BCs

largest sockeye salmon run, the Fraser River sockeye, may be acing unnaturally highlevels o sea lice because o open net-cage salmon arms. Sockeye salmon spawning

returns to the Fraser River in 2009 were the lowest in over 50 years, and were only a small

raction o numbers expected. As a result, the Canadian ederal government launched

a commission o inquiry into the 2009 collapse o the Fraser River sockeye salmon.

The Cohen Commission is currently under way and is examining a range o actors

contributing to the collapse including the impact o salmon arming on wild stocks.

For more inormation on this important conservation issue, including a variety o

inormative maps, please visit the Living Oceans Society website (www.livingoceans.org).


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ScienceThird Place

Planning or Conservation inthe Ruvuma Landscape

By Adam P. Dixon, Jessica Forrest, and Stephan Ehl

World Wildlie Fund US

Washington, D.C., USA

Data Sources

WWF 2011; Birdlie International 2010; World Database on Protected Areas 2010;

ArcGIS Online; Socioeconomic Data and Applications Center at Columbia University;

Instituto Nacional de Estatistica o Mozambique; Dar es Salaam Corporation; Gazateer.

de; DeLorme World Roads; IUCN Mission Report or Monitoring Selous Game Reserve;

Baccini, A. et al., 2008, A First Map o Tropical Aricas Above-ground Biomass

Derived rom Satellite Imagery, Environmental Research Letters

The Ruvuma Landscape has geographic eatures that make the challenge o conservation

planning dicult. The landscape is bisected by the national boundary o Mozambique to

the south and Tanzania to the north. Coordinating eorts to conserve natural resources is

problematic because o dierences in language, culture, and government commitment.

The decisions made on management protocols in these areas are critical to the ultimate

success o conservation in the region. Furthermore, by comparing the protected areas tothe Ecological Zones map, one can determine areas that may not have enough protection.

The map Planning for Conservation in the Ruvuma Landscape presents an initial graphic

introduction to the concept o conservation planning though the display o the multiple

criteria used to develop a nal conservation plan. The nal map, titled Ecological Zones,

combines the complementary datasets into one comprehensive plan or conserving

the unique biological heritage that the Ruvuma Landscape contains while addressing

the needs o human development in this region o Mozambique. The Ecological Zones

map was developed by displaying the most to least sensitive conservation targets in

the region. Sensitive habitat starts as Zone 1a, then megaauna and bird habitats are

considered, as well as mangroves, riparian zones, and areas o high carbon biomass.

The nal zones are areas that pose small risk to maintaining the ecological integrity o

the region.

The maps national boundaries and country name labels are easily lost when attempting

to show multiple concepts. Thereore, width and grayscale o country boundaries were

used to suggest that the conservation landscape is transnational and that several

countries orm the geopolitical calculus o conservation planning in the region. The

width and grayscale o the country boundaries were also intended to emphasize the

act that ecosystems do not have national boundaries. Nuance was critical in the

development o this map.

Final touches to the map included processing outside ArcGIS. Dixon exported the map

as several Adobe .ai les, thereby adding background shadows to each criteria map


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Planning or Conservation in the Ruvuma Landscape(continued)and showing the rame o the extent globe in the upper right-hand corner o the map.

This makes it easier to see that each criterion is separate rom the overall Ecological

Zones map. It also makes the map more visually appealing and the viewer more likely to

consider each criterion.

Each criterion in the map is drawn rom geographic science to spatially represent the

theme. Habitatsuitabil itymodelsarebasedonaliterature-basedmethodologyfordeveloping

a prediction o species occurrence.

Thewatersourcesdata includedwith theImportant Bird Area themedmap were

developed rom the World Wildlie Fund (WWF) and US Geological Survey Hydrosheds

project.

TheElephantZonesmapwasdevelopedbyusingahabitatsuitabilitymodel,aleast-

cost corridor analysis to model elephant movement in the region, radio collar data,

and point observations rom other elephant studies in the region.

Theland-coverdatasetwasbasedona seriesof land-coveranalysesin the region

based on separate datasets or Tanzania and Mozambique. An amalgamation o data

was ultimately used to process the nal land-cover dataset.

Socialsciencesdataincludespopulationand humanlanduse such asoil andgas,

timber, and mining concessions.

Protectedareaboundariesaredelineated.

To insinuate the decision-making process, Dixon positioned the datasets according

to theme. The species datasets are more toward the let side o the map, the carbon

biomass and land cover are placed near the middle, and the datasets that contain social

and political data are more toward the right side o the map. The human-elephant

confict and low development areas, human land-use, roads, and population datasets

were purposeully placed in the upper r ight-hand corner o the maps to emphasize their

importance and inclusion in conservation planning.

The outcome o these eorts is a map that provides a comprehensive inclusion o

criteria used to develop a conservation plan. Landscape-level planning comes rom a

combination o disciplines and, in this case, a blend o ecological and social research

to suggest the best way to advance the protection o the unique biological heritage

o an area with high rates o poverty and joblessness and inadequate development o

public resources such as clean water and health care. Furthermore, the map presents a

concept that orms a prediction o how best to conserve the natural environment and

challenges the viewer to develop reasons why the map is logical or why the map might

not present enough evidence to make a convincing case or the study.


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30/8430

Regional Conservation Design othe Southern Sierra Partnership

By Dick Cameron

The Nature Conservancy

San Francisco, Caliornia, USA

Data Sources

Caliornia Protected Areas Database 2010, Esri 2011, USGS 2000, Southern Sierra

Partnership 2010, CA Department o Conservation 2004

The Southern Sierra Partnership, which is composed o Audubon Caliornia, the

Conservation Biology Institute, The Nature Conservancy, the Sequoia Riverlands Trust,

and the Sierra Business Council, conducted a collaborative conservation assessment

that incorporated climate change across seven million acres o public and private lands.

The outcome is the Regional Conservation Design (RCD), which is a spatial vision that

links conservation goals, threat projections, and climate change responses to areas

o the landscape that oer the best opportunities or sustaining biodiversity and

ecosystem services in the southern Sierra regions o Caliornia.

This map is the primary spatial product o a yearlong planning process that dened

what areas need to be managed or ecological values to sustain biodiversity. Manyconservation issues are addressed in the planning process and discussed in the nal

report, including habitat connectivity, changes in species distribution due to climate

change, the value o riparian areas or streamfows, and wildlie movement.

The map needed to be compelling visually so that it could command the attention

o viewers. As such, it combines elements rom traditional cartography with a design

sense similar to an oil painting that uses lots o paint. The blue colors in the network are

meant to be the primary storyline, conveying a sense that the landscape connections

transcend ownership and elevation gradients.

The RCD needs to reinorce the value o ecological stewardship o dierent landholdings

and provide the connective tissue between the existing protected and well-managed

areas. As such, displaying public and private conservation land was critical but dicult

given the high amount o overlap with the RCD and the need to make the RCD theprimary visual element. Smaller preserves and parks are displayed on top o the RCD

and used a complementary color palette and high saturation in the colors.

On the map, Bureau o Land Management, US Forest Service, and National Park Service

holdings that cover the mountain regions have a background o a lighter set o colors

and a higher transparency. Because it is important that the boundaries and patterns o

ownership (e.g., consolidated vs. checkerboard) are displayed, two elements are used

to represent the boundaries that make them clear yet secondary in the visual design.

A wider transparent line weight highlights a thin strong line. The designation o each

agency employs a similar yet more saturated color as the ll or the lands, thereby

making the association between them easy or the map viewer.

Science


31/84

S I E R R A

N A T I O N A L

F O R E S TS E Q U O I A

A N D

K I N G S

C A N Y O N

N A T I O N A L P A R K S

I N Y O

N A T I O N A L

F O R E S T

S E Q U O I A

N A T I O N A L

F O R E S T

Blue RidgeNWR

PixleyPreserve

Dry CreekPreserve

HomerRanch

James K.HerbertWetland Prairie

Preserve

KaweahOaks Preserve

Lewis HillPreserve

SandRidge Preserve

McKenziePreserve atTable Mountain

Miller Preserve

at BlackMountain

TivyMountainPreserve

WindWolvesPreserve

San JoaquinRiver Parkway andConservation Trust

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Bonadelle

Ranchos-Madera Ranchos

Oakhurst

Madera

Fresno

Wasco West Wasco

Tehachapi West

Shafter

McFarland

Frazier Park

Delano

California CityTehachapi

Lancaster--Palmdale

Reedley-

-Dinuba

Terra Bella

Tulare

Arvin

Bishop

Lemoore

Bakersfield

Edwards AFB

S A N

L U I S

O B I S P O

K E R N

K I N G S

T U L A R E

I N Y O

F R E S N O

M A R I P O S A

V E N T U R A

M A D E R A

S A N T A

B A R B A R A

L O S A N G E L E S

DeerCreekColony

Ducor

Elderwood

FullerAcres

Greenfield

Halfway

House

Jones

Corner

Lemoncove

Lindcove

Meridian

Mettler

Millersville

Mitchells

Corner

OilJunction

Patch

RockyHill

SevilleSilverCity

Springville

Springville

Stout

Traver

Ultra

Vance

Vestal

Woodlake

Yokohl

Elk

Gordon

HoffmanPoint

Ivesta

Lacjac

Riverbend

Tokay

Wahtoke

BealvilleBealville

Bena

Cameron

Elmco

Fane

Higby

Hillmaid

Hollis

Ilmon

LairdsCorner

Loma

LowesCorner

Lumer

Magnolia

Merryman

OldTown

Ponca

Rayo

Rector

Redbanks

Ribier

Sageland

Sequoia

Summit

Sunland

Swall

Taurusa

TwinOaks

Walong

WheelerRidge

Woody

Worth

Zante

Zentner

Loraine

Weldon

Monolith

RoadsEnd

Badger

BalchCamp

Dunlap

MarshallJunction

Miramonte

PiedraPO

Prather

AltaSierra

Edison

Fairview

Glennville

PettitPlace

SierraCedars

Delano

ExeterFarmersville

Ivanhoe

LakeIsabella

Lindsay

London

Oildale

Porterville Porterville

Strathmore

Visalia

BretzMill

Burness

CedarGrove

Dinkey

Creek

AntesCameronCreekColony

Claraville

DiGiorgioDiGiorgio

EastFarmersville

FivePoints

FountainSprings

Hammond

Jovista

List

MatchinMitchellCorner

OakGrove

Trocha

Venida

WestVenida

Advance

Auckland

Avocado

Big

Bunch

Cedarbrook

Cella

Crabtree

Cutler

DeerCrossing

Del Rey

DelftColony

EastOrosi

Edmiston

EllisPlace

Enson

EthedaSprings

Goodmill

Hartland

Hume

Ivory

Miley

NorthDinuba

Parlier

Piedra

Pinehurst

Pinewood

Potwisha

Rodgers

Crossing

SawmillFlat

Lois

SevenPines

SierraGlen

Squaw

Valley

Sultana

Tollhouse

Trimmer

WhitneyPortal

Wilsonia

Wimp

Wineland

Wolf

Wyeth

Zediker

Algoso

Ambler

BalanceRock

BellaVista

Bodfish

Burr

BurtonMill

CabinCove

Cable

CairnsCorner

Calgro

Calico

Caliente

Caliente

CaliforniaHot Springs

Camp

Nelson

Camp

Owens

Canebrake

Cawelo

CedarSlope

Citro

CottonCenter

EdmundsonAcres

ElMirador

Fayette

Fig

Orchard

Gillete

Globe

Goodale

Goshen

Grapevine

GuernseyMill

Harpertown

Havilah

Idlewild

Jasmin

Johnsondale

Kaweah

Kayandee

Keene

Kernville

KeyesvilleKeyesville

Lackey

Place

Lamont

Lamont

Lisko

Lonsmith

Lucca

Magunden

Maltha

Manolith

Marcel

Mayfair

Milo

MiracleHot Springs

Mirador

Monson

MorelandMill

MountainMesa

Nanceville

Naranjo

OilCity

Onyx

Orris

Peral

PineFlat

PineFlat

Plainview

Plano

PleasantView

Poplar

Posey PosoPark

Quaker

Meadow

Quality

RedwoodCorral

Richgrove

Rowen

Seguro

Shirley

Meadows

SierraHeights

SmithMill

SodaSprings

SouthLake

SpearCreek

SummerHomeTract

Spinks

Corner

SquirrelMountain

Valley

SquirrelMountain Valley

SugarloafMountainPark

ThreeRivers

Tonyville

Toolville

TwinButtes

TwinLakes

Vinland

WeedPatch

WhiteRiver

WhiteRiverSummerHomeTract

WhiteRiverSummerHomeTract

WibleOrchard

WoffordHeights

Woodford

Woodville

Yettem

Abilene

Elba

HumeStation

GrantGroveVillage

RedFir

StonyCreekVillage

Riverkern

MountainHome

Ponderosa

Sugarloaf

Village

Wheatons

MineralKing

WoodlakeJunction

SandCanyon

ElRita

Roche

Westfield

Harmony

Vincent

Saucelito

Cypress GardensMobile

HomeCommunity(subdivision)

Delano MobileHomePark(subdivision)

EastBakersfield(subdivision)

Kern(subdivision)

ArvinMobileHomeEstates (subdivision)

StallionSprings

BearValley Springs

EastPorterville

GoldenHills

SouthLake

Selma

Orosi

CentervilleClotho

Friant

Gravesboro

Minkler

Navelencia

OldBretzMill

Uva

Alameda

ChinowthsCorner

DeerCreekColony

StonePlace

6565

6363

180180180180

137137

4343

46466565

155155

190190

178178

6363

4141

168168

180180

245245

168168

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166166

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202202

4141

9999

145145

137137

216216

201201

201201

198198

245245

395

395

395

0 10 20 305

Miles

TheNatureConservancy(TNC)uses themostcurrentandcompletedataavailable.GIS dataandproductaccuracymayvary.UsingGIS productsforpurposes otherthan thosefor whichtheywere intendedmayyieldinaccurateor misleadingresults.TNC reserves therightto correct,update,modify, orreplaceGIS productswithoutnotification.Map producedby theTNC CA Science Dept. Date:

January2011

Data sources:CaliforniaProtectedAreasDatabase2010,ESRI 2011,USGS 2000,S outhernSierraPartnership2010, CADept.ofConservation2004

Regional Conservation Design

Regional Priority*

Core Conservation Area

Primary Buffer and Connector

Secondary Buffer and Connector

Public and Conservation Land (Also Regional Priority)

Bureau of Land Management

United States Forest Service

National Park Service

Local/Regional

State Owned-Lands

NGO Conservation

United States Fish and Wildlife Service

Easements

Elevation (ft)

14,496

0

Lakes and Reservoirs

Rivers and Streams

Highways

Current High Density Development

Counties

Southern Sierra PartnershipRegional

Conservation Design

1:280,000

* The priority areas shown on this map represent how different parts of the region cancontribute to a network managed for ecosystem resilience. It is not a plan for public orprivate land acquisition, nor is it meant to imply that areas in blue should be subject toincreasing regulatory constraints. The SSP strongly respects private property rightsand would only engage willing landowners in conservation projects.


32/8432

Regional Conservation Design o the Southern SierraPartnership (continued)The third theme represented is the diversity o land uses and steep elevation gradients.

To do this, the basemap is a combination o a satellite image; a digital elevation model

(DEM); and a smoothed, simplied hillshade. As this was a supporting message, it is

very subtle and only draws the eye in a ew places. The agricultural land uses in the San

Joaquin Valley to the west are apparent but in a very subtle way.

Connectivity across habitats and ecosystems is a critical conservation goal in the aceo both land use and climate change. Scientists project that many species distributions

will respond to climate change by shiting to areas with more suitable climate. Those

movements, or range shits, are constrained by past land-use conversion as well as

uture changes. The spatial dimensions o connectivity are just as diverse as its role in

maintaining species viability and ecosystem unctionality. At ne spatial scales, mobile

species move at daily and seasonal requency to orage, breed, and nd cover. River

systems access ormer channels, nearby wetlands, and foodplains during storms and

seasonally. At broader time and space scales, the distribution o a species might move

uphill to adjust to higher temperatures in its current range, and juvenile, wide-ranging

species might disperse rom their natal range to set up a new home range. Disturbance

regimes, such as wildre in the orests o the region, historically have operated over

large areas, creating a mosaic o plant communities that changes connectivit y or plants

and animals over time.


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Conservation Lands Network (continued)

and CLN map creation, led the map development eort, guiding the council through

each step. Though many tools were developed to convey the message and acilitate

the implementation o the CLN, the nal map allows the entirety and complexity o

the work to be displayed in one piece. Given the myriad o biological actors analyzed

in development o the CLN, including habitat corridors, over a thousand conservation

targets, landscape integrity, and rarity o vegetation communities, it was clear rom the

beginning that the comprehensive map would have to be a complex piece.

The online map can be seen at http://bayarealands.org/gis/maps.php. The viewer is rst

encouraged to recognize the vast swaths o blue areas representing the complex CLN,

but when zoomed in to 100 percent or greater, the additional layers o inormation begin

to unold including more detail on the CLN, priority streams, converted lands, and the

existing protected lands rom which the network is built. The converted lands, made up

o cultivated agriculture and urban and rural residential lands, are an important eature

o the map, which shows ragmentation o the landscape and the resultant threat to

the viability o the network to maintain a connected and unctional ecosystem. While

zooming in to the map, the viewer will also begin to see key labels o important priority

streams and existing protected lands as well as cit y, county, and highway labels meant

to help orient the reader.

GreenIno used ArcGIS 10 to create the map and manage the underly ing data. The main

technical challenge in developing the map was the symbolization, taking a very detailed

and extensive array o data and providing a sequence o understanding as the viewer

moves rom several eet away to close up.


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38/8438

Evolution o the System oProtected Areas o Madagascar

By Wildlife Conservation Society Madagascar and Madagascar Protected

Areas System Committee

Antananarivo, Madagascar

Data Sources

Commission SAPM, geographic database rom FTM (Malagasy National Hydrographic

and Geographic Institute)

Madagascar is a global biodiversity hot spot, having an exceptionally high diversity o

wildlie species and endemic fora and auna. This biodiversity remains under severe

threat rom deorestation, ragmentation, and overexploitation. Past conservation

planning eorts in Madagascar have suered rom the lack o an eec tive biodiversity

database and the tools or its use.

The Madagascar project Rseau de la Biodiversit de Madagascar (REBIOMA) is a

collaboration between the Wildlie Conservation Society (WCS) and University o

Caliornia, Berkeley, that brings the latest analytic methods and technologies rom the

research community to bear on conservation problems.

Since 2001, REBIOMA has improved biodiversity conservation planning in Madagascar

by providing easy access to updated and validated biodiversity data and enabling

institutions and scientists to share and publish their occurrence data or conservation

uses such as quantitative conservation planning.

To depict biodiversity conservation hot spots, mapmakers chose the results o

REBIOMAs 2008 Malagasy Protected Areas System (SAPM) analysis. Projects

conducted by REBIOMA and its partners are indicated by hatch marks. SAPM generally

consolidates inormation about the protected areas in Madagascar, which has been

classied by category, periods o development, and management. Feature classes

include existing protected areas, the extension o protected areas, protected areas

with temporary status, new protected areas, important sites or conservation (priority

sites or uture protected areas), and potential sites or conservation (sites with high

probability or uture protected areas).

The selection o species shown along the right side o the map is a showcase o

REBIOMAs contribution to Madagascar biodiversity conservation, but, sadly, it also

highlights the illegal logging crisis.

Science


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APR

MA

40

Science

Sea Turtle Stranding ProbabilityBy Agnese Mancini

Boomerang or Earth Conservation

Antony, France

Data Sources

Stranding data collected in Baja Caliornia Sur between 2006 and 2009, oceanographic

data obtained rom http://coastwatch.peg.noaa.gov, shery data obtained rom

SAGARPA (2007), interviews with local shers conducted by the author

Although sea turtle stranding networks have existed or many years, very little is known

about why this occurs. From March 2006 to June 2008, a team rom Boomerang or Earth

Conservation surveyed sea turtle mortality along 220 km o coastline o Baja Caliornia

Sur, Mexico. The team ound a total o 757 stranded turtle carcasses but determined the

mortality cause o 15 percent. Fishing was the largest cause.

To determine the cause o death, the map author used GIS to create a model that

identied high-risk areas or sea turtles. It included oceanographic (SST, chlorophyll

concentration, wind and current direction and strength) and anthropogenic (shing

activity) variables to explain the absence or presence o sea turtle strandings on a

beach. The model is composed o ve steps:

1. Determine sea turtle presence/absence by analyzing chlorophyll concentration andsea surace temperature.

2. Quantiy shing activity and associated risk based on shing gear used per month.

3. Estimate the probability o sea turtle mortality related to shing activity.

4. Determine avorable/unavorable wind and current conditions.

5. Estimate the probability o nding stranded sea turtles on a beach.

The 2007 map gives an account by month. Each page contains ve maps, represent ing

the ve steps used to calculate the probability o nding st randed turtles on a specic

beach. Color intensity rises as the impact numbers increase.

The maps were useul to identiy high-risk areas and seasons or turtles in Baja Caliornia

Sur. Furthermore, they highlight areas where incidental shing activity could be a serious

threat to turtles.


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L 2007

2007

JUNE 2007

JULY 2007


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Science

Limpopo National Park(Mozambique)

By Craig Beech and Willem van Rieti

Peace Parks Foundation

Stellenbosch, West Cape, South Arica

Data Sources

Peace Parks Foundation, Tracks4Arica

Limpopo National Park (LNP) in Mozambique was proclaimed a national park in 2003.

The core o the park has been cut o rom the Limpopo River, which orms the eastern

boundary o the park. Wildlie needs access to this river course because the interior o

the park is predominantly veld land and has only seasonal water supply. The movement o

larger mammals arther east to other parks, such as Banhine and Zinave, is a strong uture

consideration within the realms o the Great Limpopo Transrontier Conservation Area.

Peace Parks Foundation wanted to identiy wildlie corridors rom the core o LNP to the

river. This corridor analysis used the actors o habitat use, ecological sensitivities, and

land use. An overlay analysis was used to visualize the resource utilization buer zone.

The project included these components:

Land-covervaluesinrelationtoecologicalcorridorcontribution

Habitatvaluefromuntouchedtodegradedstatus

Sensitivityvaluesforecotourism,wildlife,landuses,andecologicallinkages

Hydrologicsensitivityinrelationtohydrologicprocessesthatcoulddamagecorridor

inrastructure

Weighted overlay analysis was calculated by combining land cover (50%), habitat value

(25%), combined sensitivity (20%), slope (3%), and hydrologic sensitivity (2%). The

percentages denote the respective weightings used.

A 3D view o corridors was veried by air- and ground-based crews. This reveals that

corridors are impacted by settlements, cultivated lands, and other activities that need

to be rehabilitated to create corridor linkages. The 3D view shows the corridor linkages

(dark blue), extruded boundaries, and fight paths o airplanes doing verication work.

This map poster reads rom the top le t in a sequence o input layers and analyses to the

derived corridors. The 3D view, acing rom northeast, allows the user to visualize the

corridors as they link rom the river back to the core o the park. The map has helped

park authorities prioritize steps that create open connectivity rom zones to the river as

well as improve management and prevent human-wildlie confict.


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44/8444

Social ImpactFirst Place

Urban Forest Restoration SitesBy Christopher Walter

Cascade Land Conservancy

Seattle, Washington, USA

Data Sources

Cascade Land Conservanc y, Seattle Parks and Recreation, EarthCorps Science, King

County GIS, Washington Department o Natural Resources

Within 20 years, experts estimate that 70 percent o the urban orest in Seattle,

Washington, will become an ecological dead zone where invasive plants predominate,

trees are dead or dying, and wildlie habitat is gone.

The Green Seattle Partnership is a unique, community-based collaboration administered

by Cascade Land Conservancy and committed to restoring and establishing long-term

maintenance or the citys 2,500 acres o orested parkland by the year 2025.

The Urban F orest R estoration S ites map was created in 2007 to help address the

challenges o mobilizing a constituency and galvanizing support or a 20-year project

and beyond. It supports publicity, outreach, and public education. Partnership sta

and volunteers display the poster-sized map during requent presentations to schools,

businesses, and community groups and at a wide range o public venues such as

community airs, trade shows, and other events held throughout the city. In most cases,the map is part o a larger, visually oriented display that illustrates the threat o invasive

plants, makes the case or restoring our urban orests, and demonstrates how the Green

Seattle Partnership works to maniest a shared vision o healthy, sustainable urban

orests throughout Seattle. Most importantly, the map and other display materials tell

the story o how volunteers play a critical role in the success o the project and delivers

the message that there is both need and opportunit y or everyone to contribute.

The map illustrates the magnitude o the conservation challenge.

The hook relies on the conventional wisdom that the rst thing someone looks or

on a map is where they live. I they live in Seattle, chances are that there is a orested

park within a mile o them in need o care and attention, and because it is prominently

colored in a dark green and boldly labeled by name, viewers will note that proximity.

Most residents are amiliar with the larger destination parks, like Discovery, Interlaken,

Lincoln, Magnusen, and Seward, but many are oten surprised to learn that the small

orested hollow or knoll nearby is also a city park. This brings both the challenge and the

vision o a green Seattle to the neighborhood and squarely into the daily lie o every

potential volunteer.

Familiar navigational reerences, such as neighborhoods, highways, arterial and local

streets, public trails, streams, water bodies, shoreline eatures, and parks, are all

careully portrayed and their names clearly labeled.

The basemap content takes advantage o Seattles ascinating geography to draw

viewers into exploring their landscape in greater detail. A subtle elevation color ramp


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46/8446

Urban Forest Restoration Sites (continued)

and shaded relie brings out the complex patterns o hills, valleys, blus, and sinks in

noticeable detail. The variety o water eatures connecting the uplands to the sound

and lake, which dene Seattles character, as do its orest and nearby mountains, are

shown in a contrasting blue, in a detail appropriate to the scale o the map and with

names clearly labeled.

Finally, to reach a wide and diverse audience, a successul map must have a simple messageand must communicate it clearly. With the undamental principles o cartography in mind,

mapmakers layered and symbolized the dozen spatial datasets involved with careul

attention to an appropriate hierarchy o inormation. For the main subjects o orested

park sites and leadership vacancies, they chose bold green and red, respectively, and

labeled park names in black with thin white halos to set them o against the park areas

themselves. All elements o the basemap appear in various muted shades o either tan

or land areas or blue or water. Labels or corresponding eatures have similar colors

just dierent enough rom the background to be read legibly yet avoid becoming a

distraction.

Since its inception in 2004, thousands o volunteers have contributed more than 400,000

hours o labor to the partnership during 2,500 restoration events. The partnership has

enrolled 625 acres o invasive species-inected parkland into the care o 108 volunteerstewards. To date, volunteers have planted some 65,000 native tree saplings to

rejuvenate lost canopy on newly restored land.


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48/8448

Social ImpactSecond Place

Connecting Wildlieand Water Networks

By Will Allen and Jazmin Varela

The Conservation Fund

Chapel Hill, North Carolina, USA

Data Sources

Metropolitan Government o Nashville and Davidson County, Nashville Area

Metropolitan Planning Organization, Cumberland Regional Tomorrow, Land Trust

or Tennessee, the Conservation Fund, US Environmental Protection Agency Multi-

Resolution Land Characteristics Consortium, Tennessee Wildlie Resources Agency,

Tennessee Department o Environment and Conservation, US Fish and Wildlie Service,

US Federal Emergency Management Agency, US Department o Agriculture Forest

Service, US Army Corps o Engineers, US National Park Service, National Register o

Historic Places, Esri ArcGIS Online, US Geological Survey, Tele Atlas North America

Purpose: To educate the community during a public orum o the Nashville: Naturally

initiative. The orum and the associated maps were key elements in the development o

an open space plan or Nashville-Davidson County, Tennessee.

This map was prepared by the Conservation Fund as part o the Nashville: Naturally

initiative. The primary purpose o the map was to educate the community about its

water and wildlie resources during a public orum o the Nashville: Naturally initiative

in September 2010.

The orum and the associated maps were key elements in the development o an open

space plan or Nashville-Davidson County, Tennessee. As a result, the public voted on

resource priorities or implementation o the open space plan. Through an involvement

process, the public identied our key themes to be included in the open space plan:

water and wildlie networks, recreation, arming, and historic/iconic concerns. This plan,

with a detailed set o conservation priorities, policy recommendations, and benchmarks

or success, was released in April 2011.

To address the theme connecting water and wildlie networks, designers created a greeninrastructure network GIS layer that represents an interconnected network o land and

water area needed or clean air; clean water; and other economic, environmental, and

social benets or people and nature. These areas were determined as most suitable

or protection.

Designers then used ArcGIS ModelBuilder to model how hubs and core orests,

wetlands, and aquatic systems are linked by corridors. The map combines data rom

more than a dozen disparate sources and creates inventories o existing open space,

food-sensitive areas, and the green inrastructure network. A cartographic challenge

was highlighting Davidson County within the context o the surrounding landscape. This


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50/8450

Connecting Wildlie and Water Networks (continued)

was accomplished by using the ArcGIS SM Online shaded relie map service and adding

transparency to the green inrastructure network layer. Applying a transparency mask

to areas outside the Davidson County boundary ser ved to lighten but not remove them.

This project resulted in the rst comprehensive inventory o open space and analysis o

potential uture open space in Nashvilles history. This was particularly important, since

Nashville experienced a major food in May 2010. The public needed to understand thevalue o natural systems and regulated foodways, foodplains, open water, and the Mill

Creek watershed as well as how conservation oppor tunities could mitigate uture food

hazards.

Nashvilles mayor Karl Dean is using a version o this map to highlight the importance

o long-term recovery rom the food and explain to residents where to ocus green

inrastructure investments.

More inormation on the green inrastructure network design approach is available at www

.greeninrastructure.net.


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Social ImpactThird Place

Zonication o anIndonesian Archipelago

By Lucia Morales Barquero and Ruben Venegas Li

University o Bangor, Gwynedd, United Kingdom

Keto Foundation, Costa Rica

Data Sources

Landsat 5 TM, rest o data generated by eldwork

Kecamatan Pulau Banyak is an archipelago that is part o the Singkil Regency in the

south o the Aceh province o Indonesia. It consists o approximately 70 islands and

provides an important range o habitats such as coral rees, sea grass and algae patches,

reshwater swamps, and mangrove and lowland tropical rainorests. These habitats are

home to a high diversity o plants and animals, some o which are yet to be discovered.

Many species are designated as protected by the International Union or Conservation

o Nature. Some o these are the mouse deer, coral species, ree shes, dugongs, and

three species o sea turtles.

The Zonifcation o f P alau Ba nyak, A ceh, S ingkil map was created or the local

nongovernmental organization Yayasan Pulau Banyak and is the rst map o its kind or

this area. Designating conservation zones denes and minimizes the confict betweenresource utilization and resource conservation. It is hoped that zonication will increase

the probabilities o being eective, ecient, and equitable. A smart zonication and

management plan o the area will ensure the long-term sustainability o the ecosystems

and the well-being o the communities living o them.

Researchers generated most o the data or the project, which included a habitat map,

habitat assessment, and cultural data. The habitat map was the rst o its kind or the

Archipelago o Pulau Banyak. To create it, the authors classied Landsat 5 thematic

mapper satellite images and perormed extensive eld surveys. Habitat assessment

included surveys used or classiying the state o the dierent habitats. Point les were

generated. The result o the eort was the creation o the rst ormal assessment o the

state o the resources within the region. Finally, the researchers invited the participation

o local people, especially shermen. This inormation was essential or identiying thetypes o economic activities they did, how and where they did them, and the extent to

which people considered these activities benecial or detrimental or the environment

and their economy.

The map and a report on zones were presented to Aceh Singkil government ocials. As

a result, these authorities requested that Yayasan Pulau Banyak prepare a management

plan to be used by the Aceh Singkil government.

For more inormation about this project, contact the program director, Maggie

Muurmans, at [email protected].


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Social ImpactHonorable Mention

Invasive Tree MapBy Logan Berner

Big Island Invasive Species Committee

Hilo, Hawaii, USA

Data Sources

GeoEye QuickBird satellite images; County o Hawaii Planning Department roads; US

Geological Survey streams, coastline, and DEM; Hawaii GAP Analysis Program shrubs

and trees

Invasive Tree Map conveys the distribution and hazards associated with an invasive tree

in Hilo, Hawaii.

The Hawaiian archipelago, spanning nearly 2,400 km, is the most isolated island chain in

the world and home to many endemic and endangered species. On Hawaii Island (the

Big Island), a ew intact lowland orests remain, but the invasive species F. moluccana,

which is a tree rom Southeast Asia, poses a signicant threat to them. In addition,

islanders are concerned about the spread o this tree in urban areas on the eastern side

o Hawaii Island, where wind-thrown trees have caused atalities and damaged homes

and inrastructure.

Concern by the Piihonua Community Association (PCA) over the spread oF. moluccana

within its Hilo neighborhood prompted the association to contact its legislativerepresentative, Senator Takamine, who helped subsequently convene a community task

orce. As an interested neighborhood resident and volunteer, Logan Berner oered

to conduct a mapping project to determine the extent o the problem in both the

neighborhood and surrounding area. In doing so, he hoped it would be possible to

convey to both the community and task orce that the spread o F. moluccana was, in

addition to a neighborhood-level problem, a regional problem, aecting urban areas

and lowland orests.

Goals in creating the map were to show the dist ribution oF. moluccana in northwest Hilo;

identiy stands oF. moluccana that, i wind thrown, could hinder medical emergency

access and damage inrastructure; suggest control priorities to county planners and

natural resource agencies; and raise public and ocial awareness about the growing

threat posed by the spread oF. moluccana in both natural and urban areas.

The Big Island Invasive Species Committee supported Berner with the distribution

project. He began by gathering data via roadside surveys (n = 3) throughout the

community to identiy the location, size, age, and threat posed by stands oF. moluccana

(n = 43). To better understand the landscape-level threat, he conducted a land-cover

analysis using GeoEye QuickBird (2006) imagery. SPRING, which is a remote-sensing

image processing system that integrates raster and vector data representations, was

used to rst run an image segmentation then an unsupervised iterative sel-organizing

cluster algorithm. Inormed by the ground surveys, Berner used ArcGIS 10 to identiy

which cluster categories related to F. moluccana and identiy areas where F. moluccana

wasgrowingwithin30meters(~100feet)ofroadsandstreams.


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Invasive Tree Map (continued)

Many F. m oluccana patches were immediately visible in the high-resolution images;

however, the variability in canopy structure and sun-object-sensor angle hindered the

use o a pixel-based land-cover classication scheme. The image segmentation proved

to be a way o reducing intraclass spectral variability and improving the accuracy o

the occurrence model. Spectral similarity with other tree species led to some errors o

commission, a common problem in remote sensing o diverse tropical orests.

Using a hierarchical approach, all cartography was generated by ArcGIS 10. First,

neighborhood control priorities were created based on the threat that F. moluccana

stands posed to inrastructure and emergency access corridors. Second was the

regional distribution oF. moluccana, particularly in relation to roads and streams. Third

was the island-wide extent o invasive trees and shrubs. The hierarchical approach

was intended to portray how neighborhood-level invasive species problems relate to

regional and island-wide invasive species issues.

The 43 F. moluccana stands identied during the roadside survey were plotted on top

o a multispectral QuickBird image o the greater Piihonua area and color coded (red,

orange, or yellow) depending on the threat that they posed to the community. The

model showing F. m oluccana occurrence was then added, and trees within 30 m o

either a road or stream were color coded to denote their proximity. GIS layers depictingroads and streams were used to place the distribution oF. moluccana in a context more

recognizable to the community.

One inset map shows the Hawaiian island chain, and another shows the study area

in relation to native and alien vegetation on the Big Island. Again, the hierarchical

approach was used to place the neighborhood issue in a broader context. Berner tried

to maximize the use o colors that contrasted with the satellite image and logically t

with the displayed eatures.

Mapping the distribution o invasive species plays a key role in building consensus

among community stakeholders and planning control and restoration activities. Mapping

F. m oluccana in Piihonua helped empower the community association and oster a

broadening dialog about the island-wide impacts o F. m oluccana and other invasive

species. The project demonstrates that high-resolution satellite imagery, together withnovel image processing techniques, can be used to characterize the spread o invasive

pests, something which has not been widely investigated in Hawaii.


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TraditionalFirst Place

What Weve Accomplishedin Martis Valley

By Larry Orman, Maegan Leslie, and Alexandra Barnish

GreenIno Network

San Francisco, Caliornia, USA

Data Sources

Sierra Watch, Caliornia Protected Areas Database, US Geological Survey

The Sierra Watch What Weve Accomplishedmap is the culmination o a ve-year battle

over habitat and development areas in the Martis Valley located in Caliornias Sierra

Nevada area, just north o Lake Tahoe. The map rames the achievement o a negotiated

outcome that will generate over $75 million or land conservation and habitat restoration

in the Tahoe region. The outcome modies developments that otherwise would have

been allowed ree rein by the approving local government. It is a precedent-setting,

innovative, major accomplishment in conservation.

Sierra Watch, the nonprot organization that played the leadership role in this eort,

asked GreenIno Network to develop the map to help dene this complex victory so

that individual and institutional unders and other key opinion leaders would realize

what they had accomplished and be motivated to continue the eort to secure the last(huge) remaining parcel in the region (shown in orange). The map was created entirely

in ArcGIS.

The campaign involved extensive use o GIS or conservation and other issue analyses,

including dening the Priority Conservation Area (PCA) shown (an area with signicant

wildlie corridors and other natural resources). That PCA gave Sierra Watch a bottom

line or the negotiations. However, because o the complexity o the nal legal

settlements and the process that got it there, Sierra Watch needed a single image that

distilled its strategy, results, and uture directions into one map product.

The process o creating the map and its actual use were o strategic value to Sierra

Watch. It continues to be used now, two years ater it s creation. The process o creating

the map started with distilling the short, high-level message that Sierra Watch needed

to convey. This took the orm o discussions and drat image concepts or the map itsel

and assessment o how best to rame the map with design elements. It was a crucial

step mostly done in words, not with detailed map development.

From an initially more complex working map (more color themes, labels, and additional

data), GreenIno encouraged Sierra Watch to hone its visual, geographic message into

two primary themesland that had been saved and land that represented the next

challenge. These themes had to be seen within the context o the area, including other

protected lands, landscape, and the priority conservation zone.

The labeling hierarchy was careully attended to as well. Labels were limited to key


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What Weve Accomplished in Martis Valley (continued)

eatures, with some needing to be seen early rom a distance while others intended to

be seen only upon much closer examination.

The relie was kept subdued so it wouldnt distract rom the primary themes but would be

available to second looks. When the viewer moves in closer, contours emerge that help

dene the specic topography and also lend an elegant eel to the map cartography,

making the viewer more emotionally condent in what it says.

Great care was taken to make the map colors unold in a layer o meaning, where viewers

see key inormation rst, then gradually see other inormation as they view and move in

closer to the map.

A key graphic technique in the map is the use o a eathered buer around the

conservation zone. Ater evaluating several options, GreenIno chose an inside eather

to invite the viewers eye to ocus on what is in the zone and use the sharper outside

edge to push away the surrounding data when viewed closer up.

The printed versions are provided to donors and others who need or want to learn about

the ongoing issues in the valley and uture conservation opportunities. The map serves

as a geographic reerence or discussions.

It has also established a visual, geographic language or the organization. Since it wasbuilt out o GIS data and GIS sotware, layer control allowed GreenIno to export the

individual components o the map into images that can be shown individually or in

animation ormat. A two-minute narrated movie was created by GreenIno that includes

map layers and other historical data to tell a time-series story o the campaign.


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TraditionalSecond Place

Black Bear Bait-Station Surveys inSaskatchewans East Boreal Plains

By Lori L. Arnold and Edward Kowal

Saskatchewan Ministry o Environment

Regina, Saskatchewan, Canada

Data Sources

Saskatchewan Ministry o Environment

The American black bear (Ursus americanus) is part o the heritage o Saskatchewan,

Canada. This magnicent creature is timid and intelligent, and much o its behavior is

governed by its search or ood. This is a ortunate trait, because luring black bears to

sardinebaited stations allows researchers to monitor population size.

The thematic map 2010 Fourth Annual Black Bear Bait-Station Surveys, Saskatchewans

East B oreal P lains was created or Saskatchewan Ministry o Environments ongoing

conservation project to sustainably manage American black bear populations.

To perorm sustainable management o black bear populations, the Saskatchewan

Ministry o Environments Fish and Wildlie Branch conducts an annual survey. Specically,

the use o bait hit rates over consecutive years by black bears at a series o bait stations is

used as an index or tracking changes in black bear population size over time.

A total o 16 lines are surveyed in the province, and 7 o these are located in Saskatchewans

east Boreal Plains. A line consists o 50 bait stations spaced 1 km apart. In 2009, survey

techniques increased the spacing between stations up to 2 km, thereby reducing the

probability o one bear visiting successive stations. Habitat along all survey lines is

typical o bear habitat, which consists o various orest cover types including clear-cuts

and burned areas.

GPS and GIS are used to navigate to stations, map routes, and collect data in the eld.

This mobile GIS includes a Panasonic Toughbook with integrated GPS and loaded

with Esri ArcPad sotware. Data collection in the eld that was originally achieved

by entering data onto a hard-copy orm has been replaced by digital collection using

a stylus pen to enter data into an ArcPad orm. This method eliminates the need totranser data rom paper to computer back in the oce. Data is entered directly into

a shapeles attribute table, brought into an .mxd le, and used to update the annual

Black Bear BaitStation Surveys map.

The map includes access to complementary documentation, photos, and other relevant

data. People can see inormation about the projects absolute and relative location, hit

rates on bait stati

Documents

Conservation Mapbook ESRI