Regional Conservation Guide

Conception Coast Project July 2005

Prepared by: John Gallo James Studarus Elia Machado Greg Helms

CONCEPTION COAST PROJECT P.O. BOX 80241 GOLETA, CA 93118 [email protected] WWW.CONCEPTIONCOAST.ORG

DESIGN, COVER & LAYOUT BY JAMES STUDARUS ARTWORK BY EVAN CANTOR

Table of Contents Table of Contents

Executive Summary ...... 1

Chapter 1 - Introduction ...... 5 Origin and Development of the Regional Conservation Guide ...... 6 Acknowledgements ...... 8

Chapter 2 - Key Concepts of Conservation Planning ...... 11 Biodiversity ...... 12 Ecological Services ...... 13 Sustainability ...... 13 A Sense of Place ...... 14

Chapter 3 - Regional Overview & Threats ...... 17 Deﬁning a Regional Boundary ...... 18 Major Habitat Types of the Conception Coast Region ...... 19 Summary of Ecological Threats in the Conception Coast Region ...... 27

Chapter 4 - Methods & Results ...... 33 Overview of Regional Conservation Planning Approach ...... 34 Biodiversity Value Analysis ...... 38 Conservation Priorities Analysis ...... 56

Chapter 5 - Interpreting the Major RCG Findings ...... 87 Biodiversity Value Analysis ...... 88 Selected Key Conservation Priority Areas ...... 89

Chapter 6 - Implementing the Regional Conservation Guide ...... 95 Relevant Programs, Activities and Methods for Conservation ...... 96

References ...... 100

Appendices (available on enclosed CD) ...... 105 Appendix A Detailed Methodology ...... 106 Appendix B Focal Species Proﬁles ...... 143 Appendix C Steelhead Analysis ...... 146 References for Appendix ...... 157

Conception Coast Regional Conservation Guide Table of Contents

List of Figures: 1. Conception Coast Region and Watersheds ...... 19 2. General Land Use of the Conception Coast Region ...... 21 3. Habitat Types and Distribution within the Conception Coast Region ...... 25 4. Diagram of the Biodiversity Value Analysis ...... 36 5. Diagram of the Conservation Priorities Analysis ...... 37 6. Human Impact Types within the Conception Coast Region ...... 39 7. Estimated Degree of Human Impact within the Conception Coast Region ...... 41 8. Listed Species Locations within the Conception Coast Region ...... 45 9. Listed Species Hotspots Biodiversity Value within the Conception Coast Region (B1) ...... 47 10. Habitat Representation Biodiversity Value within the Conception Coast Region (B2) ...... 49 11. Locations of Large Wild Lands within the Conception Coast Region ...... 51 12. Wild Lands Biodiversity Value within the Conception Coast Region (B4) ...... 53 13. Habitat Quality for Mountain Lion Dispersal ...... 57 14. Large Wildlife Linkages within the Conception Coast Region ...... 59 15. Landscape Connectivity Biodiversity Value within the Conception Coast Region (B6) ...... 61 16. Estimated Biodiversity Value within the Conception Coast Region ...... 63 17. Comparison of Current and Predicted Urban Extent within the Conception Coast Region ...... 65 18. Comparison of Current and Predicted Housing Density within the Conception Coast Region ...... 67 19. Comparison of Current and Predicted Human Impact within the Conception Coast Region ...... 73 20. Predicted Change in Human Impact within the Conception Coast Region (i.e. “Threat”) ...... 75 21. Habitat Representation Conservation Value within the Conception Coast Region (C2) ...... 77 22. Wild Lands Conservation Value within the Conception Coast Region (C4) ...... 79 23. Reserve Adjacency Conservation Value within the Conception Coast Region (C5) ...... 81 24. Landscape Connectivity Conservation Values within the Conception Coast Region (C6) ...... 83 25. Estimated Conservation Priorities within the Conception Coast Region ...... 85

List of Tables: 1. Percentages of Vegetation Types in Region ...... 24

List of Figures in Appendix: A-1. Utility Function Curves ...... 136 C-1. Steelhead Barrier and Habitat Quality Map of Santa Clara Watershed ...... 149 C-2. Steelhead Barrier and Habitat Quality Map of Santa Maria Watershed ...... 151 C-3. Steelhead Barrier and Habitat Quality Map of Santa Ynez Watershed ...... 153 C-4. Steelhead Barrier and Habitat Quality Map of Ventura Watershed ...... 155

List of Tables in Appendix: A-1. Human Impact Categories and Values ...... 109 A-2. Source Data for the Regional Conservation Guide ...... 110 A-3. Species used for the Rare Species Hotspots Analysis of the RCG ...... 114 A-4. Input Values and Output Habitat Weights for the Regional Conservation Guide ...... 122

Conception Coast Regional Conservation Guide Executive Summary

Executive Summary

Conception Coast Regional Conservation Guide Executive Summary Executive Summary The south-central coast of California is home to status is critical, preempting the crisis manage- a globally unique array of natural resources, di- ment associated with endangered species recov- verse wildlife, varied landscapes and unmatched ery efforts. We believe the Guide contributes human amenities. Located at the intersection an important, clarifying sense of an overall of warm, semi-arid southern California and conservation vision to engage stewardship, guide cooler, wetter central California, this “Con- action and empower stakeholders with a com- ception Coast Region” hosts a natural bounty mon, achievable set of goals. We suggest that that blends northern and southern climates, no single interest will succeed alone in secur- landscapes and plant and animal communities ing our common future without a new sense of together as nowhere else in North America. teamwork, and offer the Regional Conservation Consisting of Santa Barbara, Ventura and parts Guide as a helping hand in that direction. of their adjacent counties, the region’s spectacu- lar coastline, mountainous wild backcountry, Following the catalogue of the region’s natural verdant working agricultural landscapes and bounty and a discussion of conservation plan- dramatic watersheds form the natural capital ning concepts, the Regional Conservation Guide upon which our daily lives—whether we recog- presents a powerful modeling tool with which nize it or not—are based. In a first sense, the conservation goals and ecological data are com- Regional Conservation Guide (RCG) you are bined with anticipated future threats to resources reading is a catalogue of our natural assets and a from growing human population, consumption call for greater understanding of their needs. and land-use trends. An important and powerful tool in itself, the RCG model’s graphical outputs More importantly, this Regional Conservation represent achievement of an important goal of Guide represents a unique tool we hope will as- the Conception Coast Project for the past half- sist in community planning efforts to secure our decade: usable, illuminating maps that identify natural heritage while seeing to the needs of our the most ecologically important areas of our human communities. This Regional Conserva- region, and, when combined with the factor of tion Guide provides focus on just what nature’s “threat,” maps that identify priorities for near- needs are in this region. The Guide draws on and long-term conservation efforts. These maps a wealth of locally-produced biological data, present options for a region wide system of pro- guided by proven concepts of conservation biol- tected areas that meet the needs of the landscape ogy to depict, for the first time, what would be for long-term ecological sustainability. To be needed to assure that future generations enjoy clear, all of the areas identified as conservation – and are sustained by – a thriving ecosystem priorities need not be secured in “reserves” – or with a healthy complement of wildlife, land- highly protected status such as wilderness— in scapes and natural resources. order to maintain the region’s ecological integrity. “Stewardship zones” —areas of quality The Guide also advances the notion of “eco- habitat that allow for human use of the landscape system-based management” which focuses simultaneous to managing for biodiversity—may conservation effort on habitats and assemblages be used as part of an effective network of re- of plants and animals together and before their gional conservation designations. Stewardship

Conception Coast Regional Conservation Guide Executive Summary

zones can occur on public and private lands and include certain types of agricultural and grazing practices, ecologically sustainable forestry, and recreational use such as hunting and ﬁshing.

Of critical importance in responding to and utilizing the information contained in this Guide is the use of the same long-range (25-100 years or more) planning perspective that was used in creating it. The Guide concludes with an extensive discussion of implementing its conservation recommendations, efforts we expect will take considerable time and greater ﬁnancial and other resources than presently exist. Nevertheless, we believe the Guide presents urgently needed information as well as inspiration to guide the use of currently available time, energy and resources to ensure our conservation and stewardship efforts are efﬁcient and pay maximum dividends. Given this timeline, we outline numerous voluntary, pro-active alternatives to complement existing effort towards assuring preservation of our natural heritage while meeting the complex and growing needs of our society.

Conception Coast Regional Conservation Guide Conception Coast Regional Conservation Guide Introduction Chapter 1

Chapter 1 Introduction

Conception Coast Regional Conservation Guide Chapter 1 Introduction Introduction ORIGIN AND DEVELOPMENT OF THE ings, and focus groups were held to advise CCP REGIONAL CONSERVATION GUIDE (RCG) staff regarding numerous technical decisions The Conception Coast Project (CCP) developed associated with the RCG. an initial vision of a landscape-scale conservation planning tool following its inaugural com- CCP Staff and their associated roles during the munity workshop in 1995. This vision was period of RCG Development consisted of: twofold: to communicate the requirements of the landscape for long-term ecological sustain- John Gallo, conservation director GIS analyst ability, and to create a tool to guide community James Studarus, operations director action towards achieving it. Over several years, Elia Machado, GIS analyst CCP refined a set of goals and principles for Cory Gallipeau, GIS analyst and data manager this tool—the Regional Conservation Guide Ethan Inlander, conservation advisor you are now reading—based upon community Michael Summers, development associate needs as well as those of the natural environment. CCP evaluated a variety of conservation The Land-Use Advisors are local resource planning frameworks for their suitability in professionals selected based on knowledge of meeting the needs of the local region and its conservation planning and land use and man- array of land-use and resource management agement in the region. They provided advice, stakeholders. The cutting edge modeling frame- feedback, and guidance in development of the work developed at UCSB Biogeography Lab land use components of the analysis as well as and the National Center for Ecological Analysis of the products. The organizational affiliations and Synthesis was selected (Davis, Stoms et of these advisors is provided for identification al. 2003). This framework was created for the purposes only, and do not reflect endorsement Legacy Program of the California Resources of or involvement of the organizations in this Agency. CCP then identified the portions of the document. framework that would be applied as well as the additional ecological sub-models that would be Darcy Aston – program specialist, senior, Santa added. The resulting model will be termed the Barbara County Water Resources Division RCG Model for the rest of this document. Rachel Couch – administrative assistant to Santa Barbara County Supervisor Susan Rose At the numerous decision points encountered Robin Cox – director of planning, The Nature in developing the RCG, local knowledge was in- Conservancy corporated as much as possible to ensure maxi- Jim Engel – executive director, Ojai Valley Land mum regional applicability of the document as a Conservancy planning tool for the public. Michael Feeney – executive director, Land Trust for Santa Barbara County Two groups of advisors, the Land-Use Advisors Maeton Freel- senior biologist, United States and the Ecological Advisors, where assembled Forest Service to augment the CCP Board of Directors and to Carla Frisk – project consultant, Trust for Public advise CCP Staff. Periodic workshops, meet- Land

Conception Coast Regional Conservation Guide Introduction Chapter 1

Dr. Rod Nash- professor emeritus Environmen- David Hubbard- UCSB Museum of Systematics tal Studies and Ecology Martin Potter – wildlife biologist, California John Labonte- doctoral candidate, Department Department of Fish and Game of Ecology, Evolution, and Marine Biology, Lisa Plowman- senior planner, Santa Barbara UCSB County Planning and Development Tom Olson – senior biologist, Garcia and As- Nancy Read – biologist, Vandenberg Air Force sociates Base Dr. Ralph Philbrick – botanical consultant Lorraine Rubin – regional planner, County of John Storrer- owner, Storrer Environmental Ventura Planning Division Services Kate Symonds –United States Fish and Wildlife Dr. Sam Sweet- professor, UCSB Ecology De- Service partment, Herpetiles Bob Thiel – project coordinator, Southern Cali- Dr. Jaimie Uyehara – biologist, United States fornia Wetlands Recovery Project Forest Service Alex Tuttle – planner, Santa Barbara County Planning and Development The Conception Coast Project’s Board of Direc- tors was instrumental in developing the original The Ecological Advisors consist of local scien- direction of the RCG as well in providing in- tists, resource managers and naturalists selected valuable advice to staff throughout the process. based on knowledge of conservation planning Again, organizational affiliations are included and about one or several taxa or ecological for identification purposes only. principles. They provided advice, feedback, and guidance in development of the ecologi- Greg Helms – The Ocean Conservancy cal components of the analysis as well as of the Rachel Couch products. The organizational affiliations of these John Storrer advisors is provided for identification purposes Darcy Aston only, and do not reflect endorsement of or Paul Jenkin –Ventura County Surfrider Chapter involvement of the organizations in this document. A group of academics and conservation planners was also consulted in order to provide an ongo- Dr. LynneDee Althouse- Co-Director, Althouse ing source of informal peer review in the de- and Meade, inc. Biological and Environmental velopment of the RCG. Some members of this Services group provided theoretical and technical input Liz Chattin- biologist, County of Ventura Plan- on an ad hoc (i.e. for the purpose at hand) basis ning Division and are listed in the acknowledgements section Chris Clervi- data manager, United States Forest of the RCG. CCP extends its sincere thanks Service to each of the advisors for their contributions. Paul Collins- curator of vertebrate zoology, They graciously volunteered their time and their Santa Barbara Museum of Natural History wealth of knowledge. Jim Greaves- principal, Jim Greaves Consulting

Conception Coast Regional Conservation Guide Chapter 1 Introduction

Finally, although we believe the RCG is an im- Gallipeau, Jenna Garmon, Kathy Daly, Jennifer portant source of information and an outstand- Bernstein, Ralph Philbrick, John Storrer, Rachel ing basis for community-based conservation Couch, Darcy Aston, Paul Jenkin and Lorie planning, we recognize that the document serves Baker. as a starting point rather than a conclusion. As discussed within this Conservation Guide, re- Also, Conception Coast Project owes many ﬁnement of its components and implementation thanks to individuals and organizations that of its ﬁndings will necessarily entail a highly have supported and collaborated with us over inclusive team of community members working the past decade. We are grateful for their together towards the common goal of protecting support that enhanced the capabilities of our our natural heritage. project. These include: Shoreline Preserva- tion Fund, California Wilderness Coalition, ACKNOWLEDGEMENTS Paul Collins and the Santa Barbara Museum Many exceptional organizations and individuals of Natural History, Mike Goodchild and Keith aided in the creation of the Regional Conserva- Clarke and UCSB Department of Geography, tion Guide. This project has been a bold vision Eric Zimmerman and UCSB Environmental for over a decade and came to this point through Studies Department, Frank Davis, David Stoms hard work, vision and generosity. and the UCSB Biogeography Lab, UCSB Envi- ronmental Affairs Board, Mark Holmgren and Conception Coast Project is grateful for the the UCSB Museum of Systematics & Ecology, generous contributions from the numerous and the Alexandria Digital Library. In addition, individuals and organizations who supported CCP thanks the scientists that have made them- this effort. We are especially thankful for the selves available for consultation on an ad hoc following organizations that made it possible to basis: Richard Church, Sara Fabrikant, Helen complete the Regional Conservation Guide: Couclelis, Reed Noss, Bob Pressey, and Marc Hoshovsky. Wendy P. McCaw Foundation Lawson Valentine Foundation Finally, CCP would like to thank those who aid- Patagonia, Inc. ed in the creation, establishment and technical Ben and Jerry’s Foundation capabilities of the project. We appreciate their Environmental Systems Research Institute expertise, wisdom and guidance. These individ- Maps.com uals include: Michael Summers, Kristen Penrod, RAIN Networks Jim Thorne, Scott Bull, Ariana Katovich, Phil Fund for Santa Barbara Tseng, Alasdair Coyne, Chris Stebbins, Valerie Olson, Thomas Carver, Chris Clervi, Morgan Conception Coast Project would like to thank Ball, Mike Weintraub, Dianne McCutchan, Pat- these individuals who contributed directly to the rick McDermott, Juliette Harding, Chris Longo, Regional Conservation Guide through over- Diego Pedreros, Jack Ucciferri, Matt Stoecker, sight, review of documents, writing materials Sarita Vasquez, Eric Dahlke, Michael McGin- and technical assistance: Ethan Inlander, Cory nis, Zac Stanley, Ryan Aubry, Jessica Scheeter,

Conception Coast Regional Conservation Guide Introduction Chapter 1

Jeff Kuyper, Nicole Schultze, Sue Brooker, Jesse Wickizer, Brandi Webber, Jim Balsitis and Bob Arenz.

Conception Coast Regional Conservation Guide Conception Coast Regional Conservation Guide Key Concepts of Conservation Planning Chapter 2

Chapter 2 Key Concepts of Conservation Planning

Cottonwood - Populus trichocarpa

Conception Coast Regional Conservation Guide Chapter 2 Key Concepts of Conservation Planning Key Concepts of Conservation Planning Imagine a house of cards consisting of level decreases when the genetic variation within a upon level of cards, all stacked in an intricate species decreases, a species becomes extinct or display. Each level depends on the last for its an ecosystem complex is lost. stability, and each card depends on another to stand upright. Gravity is the force that holds the Biodiversity is typically considered at three entire structure together. This illustration is not different levels: genetic diversity, species diver- unlike the relationships that exist in the natural sity and ecosystem diversity. Genetic diversity world. Our natural environment is an intricate refers to the variety of genetic information con- display of interdependent forms of life, bringing tained in all of the individual plants, animals and forth a remarkable array of benefits to the whole. microorganisms. Such diversity occurs within and between populations of species as well as A card can be pulled from a house of cards, between species. Species diversity refers to the one at a time, without collapse because gravity variety of living species. Ecosystem diversity maintains a balance. But after enough cards are relates to the variety of habitats, biotic commu- removed, a threshold is reached, and if just one nities, and ecological processes, as well as the more card is removed, the house collapses. The immense diversity present within those ecosys- environment and all that it encompasses is of tems. similar constitution, and it can only sustain so much degradation before functioning is impaired An important issue regarding biodiversity is that or its many components become dismantled or scientists don’t know very much about it on a destroyed. global scale. About 1.4 million species have been identified in some way or another, but the Today, society faces a significant challenge true number is estimated at between 10 and 100 in balancing the needs of humankind with the million. We have scarcely begun to understand needs of the environment. To begin to better the scope of the biodiversity upon which our understand these challenges, it is important to collective well-being is ultimately dependent. grasp some key concepts that are fundamental to the natural world. Extinction is occurring at an unprecedented rate. Harvard University’s E.O. Wilson predicts that BIODIVERSITY one-third of the world’s species could easily die Biological diversity or biodiversity refers to the out in the next 40 years. Anthropogenic (hu- variety of life forms: the different plants, ani- man) activities increasingly disturb the integrity mals and microorganisms, the genes they con- of global biodiversity. Pollution, the introduc- tain, and the ecosystems they form. This living tion of exotic species, unsustainable agricultural wealth is the product of hundreds of millions of practices, urban sprawl, fragmentation of habi- years of evolutionary history. The process of tat by roads and fences, draining of wetlands, evolution means that the pool of living diver- elimination of natural fire processes, damming sity is dynamic. It increases when new genetic of rivers, clear-cut logging, and climate change variation is produced, a new species is created all contribute to the loss of biodiversity through or a novel ecosystem is formed; biodiversity ecosystem disruption and habitat destruction.

Conception Coast Regional Conservation Guide Key Concepts of Conservation Planning Chapter 2

Natural disturbance aside, species richness has versity, and biodiversity correspondingly main- decreased as the world’s human population has tains the world’s ecological services. They are grown. interconnected and unified. As you may recall in the house of cards analogy, all of the cards ECOLOGICAL SERVICES must stand upright, and all the levels must sup- Ecological services rank high on the list of rea- port the ones below, in order for the house to be sons the biodiversity crisis is of major concern. sustained. If the cards cannot stand upright, or The term “ecological services” refers to the the levels collapse, what will be left of the struc- conditions and processes through which natural ture? Both must be present and robust. ecosystems sustain the environment, including the needs of humanity. They are a result of If left unchecked, failure and collapse of our complex natural cycles, driven by solar energy, important and valuable ecological services and which operate on different scales, influencing biological diversity is a real possibility. In many the workings of the biosphere in different ways. respects, we are on the path of breakdown with a Ecological services produce ecosystem goods, documented multitude of endangered or threat- such as food, timber, energy, and natural fibers, ened species and habitat, as well as a long list of as well as raw materials used in pharmaceuticals extinct species. Like a thermometer registering and industrial products. The harvest and trade of a fever, the accumulating trends of ecological these goods is based upon “natural capital” and decline are the indicators of our condition. is a fundamental part of the global economy. SUSTAINABILITY In addition to the production of goods, ecologi- It is not the environment that needs to be man- cal services include life support functions, such aged. It is what we as humans do in our environ- as protecting watersheds, reducing erosion, ment that needs better management. The ways cycling nutrients and providing habitats, as well in which humans manipulate biological diversity as cleansing, recycling, and renewal. Examples determine how sustainable human populations of the benefits of ecological services include: will be. purification of air and water, mitigation of floods and droughts, detoxification and decomposition Sustainable development involves complex of wastes, generation and renewal of soil and processes of purposeful change in the attitudes, soil fertility, pollination of crops and natural behaviors, and institutions of human societies, in vegetation, dispersal of seeds and translocation which humanity chooses to balance its consump- of nutrients, control of agricultural pests, pro- tion and development with the needs of the natu- tection from the sun’s harmful ultraviolet rays, ral world. Sustainability asks that we attempt moderation of temperature extremes, and the “…to meet the needs of the present without force of winds and waves. A further benefit is compromising the ability of future generations the aesthetic value we receive from the world’s to meet their own needs (Bruntland, 1987). natural ecosystems and landscapes. Sustainability in this context – the decision to Ecological services maintain the world’s biodi- conserve resources so that impacts on the en-

Conception Coast Regional Conservation Guide Chapter 2 Key Concepts of Conservation Planning

vironment can be minimized to reduce the rate social and physical environment is increasingly of environmental degradation – is an attainable being identiﬁed as a cornerstone of success- goal. The economic and social fabric of human ful conservation work. Watershed groups are societies does not have to suffer as a result. By example of such a place-based, locally focused reevaluating our routine actions to avoid those arrangement for directing collective action that that are unnecessary and wasteful, by reducing emphasizes the values of teamwork, civility, our consumption, and by recycling and reus- dialogue, mutual aid and information sharing. ing our wastes, we may begin to see a turn of Sociologists have termed this notion “biore- the tide, and perhaps meet somewhere in the gionalism,” although its roots probably predate middle. sociology itself.

The intricacies and fragility of the world around Central to a “place-based” basis for addressing us must be acknowledged. The environment is the concerns discussed in this Guide is the sense not as fragile as a house of cards, but degrada- of shared responsibility to the land and to one tion is rapidly occurring on a global scale and another. A critical step in this direction entails the cumulative impact is yet unknown. Aware- developing an intimate knowledge and under- ness is crucial, and indicators of degradation standing of the natural and social character of should not be ignored. Loss of habitat and a place. The process of gaining knowledge species diversity is real, and is creating concrete about the land brings with it an awareness of the and as yet unknown implications for the future. history of the land, and understanding history produces a concern for the future. This Guide A SENSE OF PLACE contains a modern and science-based interpre- A ﬁnal notion implicit in the development and tation of the landscape of the region, speaking use of this Regional Conservation Guide is a directly to the needs of natural systems. Within personal commitment to the place in which one the people and cultural history of this region lives. A personal commitment to understanding lies another rich, invaluable source of informa- and caring for one’s local social and physical tion we must be willing and able to discover environment plays an essential role in ensur- and use. For success over the long term, these ing their long-term well-being. Increasingly, resources must be integrated through a process the sense of personal engagement in a particu- of sharing, teamwork, and trust in each other. lar landscape and community is diminished by modern society’s transience, mobility and global concerns. Rural residents, although they may be physically farther from their nearest neighbor compared with urban dwellers, often retain a much greater personal involvement with their neighbors and with their physical surroundings. While modern amenities may have reduced the necessity of relying on one’s neighbors, the active involvement of individuals with their local

Conception Coast Regional Conservation Guide Key Concepts of Conservation Planning Chapter 2

Conception Coast Regional Conservation Guide Conception Coast Regional Conservation Guide Regional Overview & Threats Chapter 3

Chapter 3 Regional Overview & Threats

Tiger Salamander - Ambystona tigrinum

Conception Coast Regional Conservation Guide Chapter 3 Regional Overview & Threats Regional Overview & Threats DEFINING A REGIONAL BOUNDARY The Conception Coast Region extends from Defining the boundary for a conservation plan the Santa Maria to the Santa Clara River water- is a difficult but critical early step. A regional sheds, and includes all of Santa Barbara County, conservation planning boundary should be both most of Ventura County, and small portions of ecologically and socially defined. The region San Luis Obispo, Kern, and Los Angeles Coun- should also be large enough to address biogeo- ties, incorporating the watersheds that intersect graphic issues, yet small enough to be socially the two Jepson ecoregions as its boundary. The and politically tractable. Channel Islands, Santa Barbara Channel, and the coastal waters of the area are also included Setting the boundary of the “Conception Coast within the Conception Coast Region. These Region,” presents a unique challenge in south- island and offshore areas will not be addressed central California in that the area encompasses in this first edition of the RCG. The Conception a “transition” zone between a truly southern Coast Region also includes the Calleguas Water- California ecological setting and the distinct shed, which was included for important plan- central California setting. Intuitively, residents ning purposes for Ventura County. See Figure 1 of the area identify themselves as both southern (Conception Coast Region and Watersheds) and and central Californians, and science from a Figure 2 (General Land Use of the Conception host of disciplines confirms it. Widely accepted Coast Region). ecological subdivisions of California such as the Jepson Ecoregion system confirm this “in-be- MAJOR HABITAT TYPES OF THE tween” character of the south-central coast of CONCEPTION COAST REGION California, placing Santa Barbara County at the The 14,000 square kilometer Conception Coast junction of the central western and southwestern Region is named after Point Conception, the regions. Drawing from studies of the distribu- geographic feature that defines the boundary tion patterns of animal and plant taxa, climate between central and southern coastal California. regimes and ocean current patterns, the south- The region serves as a geologic, topographic central coast of California stands out clearly and climatic transition zone supporting a rich as a “mixing zone” –an area in which northern diversity of ecosystems and habitats. The and southern coastal ecological features occur region’s ecosystem types are highly diverse, together. This transition zone is unique in the ranging from interior scrub-dominated desert United States, and represents a rich, diverse and landscapes to alpine conifer forests to coastal critical biological “hotspot” that might be over- dune and wetland complexes. These ecosystems looked if treated simply as the northern extent harbor approximately 1,400 native species, of of the southern California region or the southern which more than 140 are endemic to the region. end of the northern California region. Bio- The convergence of the Southern California logically and socially, this area of transition is and Central California climates occurs around distinct in itself, and the Regional Conservation the Santa Ynez ridge. The Conception Coast Guide therefore establishes a region that encom- Region has a high diversity of plant and animal passes this unique transition zone. species as a result of the transitional characteristics of the area.

Conception Coast Regional Conservation Guide Regional Overview & Threats Chapter 3

Figure 1: Conception Coast Region and Watersheds FRONT

Conception Coast Regional Conservation Guide Chapter 3 Regional Overview & Threats

Figure 1: Conception Coast Region and Watersheds BACK

Conception Coast Regional Conservation Guide Regional Overview & Threats Chapter 3

Figure 2: General Land Use of the Conception Coast Region FRONT

Conception Coast Regional Conservation Guide Chapter 3 Regional Overview & Threats

Figure 2: General Land Use of the Conception Coast Region BACK

Conception Coast Regional Conservation Guide Regional Overview & Threats Chapter 3

A list of the major vegetation-based habitat gion include the coastal live oak community, the types that was used in regional analysis appears blue oak-foothill pine group and the valley oak at the end of this section. Below, the major savannah. habitat groupings present in the Conception Coast Region are briefly overviewed. Grassland communities are present in the region at a wide variety of elevations. Lowland Coastal lowlands and seashore habitats bound grasslands have been extensively converted to the coastal edges of the region, with rocky residential, agricultural and other uses, although shores predominating in the northern stretches examples of less-disturbed lowland grassland and sandy beaches most typical in the south communities exist at More Mesa and the Ell- facing southern reaches. Rocky shore habitat is wood Mesa in Goleta, in the Hollister/Bixby extensive north of Vandenberg Air Force Base, Ranch area, and elsewhere. Grassland areas in from Point Sal to Pursima Point, and along Point the mountains are known as “portreros,” which Conception. Sandy beaches are widespread, al- are highly localized in the Santa Ynez and San though often heavily disturbed (Lehman, 1994). Rafael ranges but extensive in the Sierra Madre range (Lehman, 1994). Coastal wetlands, although severely reduced in scope and size in the last century, are present in Chaparral covers much of the undeveloped the region in the south at Point Mugu and Or- coastal areas that lie in the South Western Cali- mand Beach, in the north at the Santa Maria and fornia Ecoregions. Areas along the front range Santa Ynez River mouths, and at the Devereux of the Santa Ynez Mountains through the Ven- and Goleta Sloughs. A few freshwater marshes tura, Santa Clara and Calleguas watersheds host such as the Barka Slough and at the interior areas of undisturbed chaparral. delta of the Santa Maria River near Guadalupe remain (Lehman, 1994). Riparian woodlands occur throughout the region, both inland and coastal. Inland riparian The majority of the oak woodlands occur in woodlands occur around the Santa Ynez and sheltered valleys or along the north-facing Sisquoc Rivers and along several tributaries, slopes of canyons and coastal mesas. In the and may contain a complex understory/oversto- north, woodlands most frequently occur on ry structure including willow, cottonwood, and hilltops or in wide valleys, providing habitat, sycamore (Lehman, 1994). shelter and refuge from heat for many species (Stephenson et al. 1999). They often occur in Foothill and mountain pine/oak forests and two distinct forms: as closed canopy stands in Bigcone Douglas-fir forest occur sporadically canyons or along streams, and as open savannas along of the north facing mountain slopes of the in broad valleys. Large fauna including moun- region. Higher elevation areas such as Mount tain lions (Felis concolor), black bear (Ursus Pinos and Figueroa Mountain contain Montane americanus) and mule deer (Genus Odocoileus) conifer forest where Jeffrey pine and white fir continue to inhabit the oak woodlands of the are often found (Stephenson 1999). region. Oak woodland habitat types in the re-

Conception Coast Regional Conservation Guide Chapter 3 Regional Overview & Threats

Vernal pools were prevalent on the coastal and TABLE 1: HABITAT TYPES AND interior lowland areas of the Conception Coast DISTRIBUTION WITHIN THE CONCEPTION Region during pre-settlement times. Vernal COAST REGION pools are seasonal wetlands that ﬁll with water Habitat Type Percentage during fall and winter rains (Stephenson 1999). Agriculture 7.00 The coastal mesas and plains were dotted with Alkali Desert Scrub 0.34 vernal pools that provided habitat for an array of Annual Grassland 13.8 animals, including migratory waterfowl, frogs, Barren 1.35 toads, salamanders, and pollinating insects. Blue Oak Woodland 2.27 Coastal dune, coastal sage scrub and estuarine Blue Oak-Foothill Pine 0.05 salt marshes, along with the intertidal marine Chamise-Redshank Chaparral 3.70 complex represent the dominant habitat types of Closed-Cone Pine-Cypress 0.04 the coast. Coastal Oak Woodland 8.04 Coastal Scrub 16.8 The current extent of the many habitat types Desert Scrub 0.97 within the region has been dramatically affected Desert Succulent Shrub 0.01 by urbanization, agricultural conversion and Desert Wash 0.06 industrial uses. Chaparral such as coastal sage Freshwater Emergent Wetland 0.01 scrub has been reduced to only 15 percent of its Jeffrey Pine 1.18 former range in Southern California (Stephen- Joshua Tree 0.01 son 1999). One major issue with chaparral is Juniper 0.71 replacement of native chaparral with nonnative Lacustrine 0.00 grasslands after frequent ﬁre disturbances (Ste- Mixed Chaparral 31.1 phenson et al. 1999). Montane Chaparral 0.47 Montane Hardwood 1.74 For an indication of the percent cover of each Montane Hardwood-Conifer 1.38 habitat type within the region, see the below Montane Riparian 0.91 Table 1. To see how these types are distributed Pinyon-Juniper 5.67 geographically, see Figure 3: Habitat Types and Ponderosa Pine 0.01 Distribution within the Conception Coast Re- Sagebrush 0.62 gion. Saline Emergent Wetland 0.01 Sierran Mixed Conifer 0.68 Subalpine Conifer 0.00 Unknown Conifer Type 0.00 Unknown Shrub Type 0.19 Valley Foothill Riparian 0.12 Valley Oak Woodland 0.20 Water 0.60

Conception Coast Regional Conservation Guide Regional Overview & Threats Chapter 3

Figure 3: Habitat Types and Distribution within the Conception Coast Region FRONT

Conception Coast Regional Conservation Guide Chapter 3 Regional Overview & Threats

Figure 3: Habitat Types and Distribution within the Conception Coast Region BACK

Conception Coast Regional Conservation Guide Regional Overview & Threats Chapter 3

SUMMARY OF ECOLOGICAL THREATS IN and suburban areas, leads to a tendency towards THE CONCEPTION COAST REGION sprawl and development of remaining urban The natural landscape of the Conception Coast open spaces and agricultural land. Compound- Region forms the backbone of its living commu- ing this problem are recent trends towards nity, supplying clean air, water and open space. development of large residential developments California’s population is roughly 36 million and associated infrastructure in rural and semi- people, and is adding a half million people an- rural areas, fragmenting habitat. Such develop- nually (California Legislative Analyst’s Office, ment adjacent to rural, wilder areas increases the 2002 ). Undoubtedly, the region will experience incidence of wildlife-human interactions, which drastic effects of this swelling population as inevitably leads to harm to habitat and wildlife. pressures build for more housing, roads, com- Predator extermination is a common practice in mercial centers, and other developments. While residential-wild land interface areas, as is large- an exhaustive treatment of negative ecological scale fencing, which closes off wildlife travel trends is beyond the scope of this document, it routes. is vital to understand the broad types of threats facing the Conception Coast Region in order to The effects of increased development are mani- create a conservation strategy that will be effec- festing in other less-direct ways. Water demand tive in addressing these problems. is increasing, drawing down the water supply, reducing stream flow and threatening riparian The principal threats of our region include: vegetation and riparian-dependent species such -Development pressure as steelhead. In addition, automobiles and runoff -Habitat Fragmentation from impervious surfaces have affected the -Loss of top predators health of streams and creeks, and consequently -Oil development the ocean. Construction of roads in rural and -Climate change semi-rural areas has impeded wildlife move- -Agricultural intensification ment and increased human uses in these areas. -Aquatic fragmentation Many urban creeks have been channelized and -Loss of native species degraded, reducing their habitat functions. -Exotic species -Erosion FRAGMENTATION -Lack of coordinated conservation strategy Habitat fragmentation has been identified as one of the chief threats to biodiversity (Burgess and DEVELOPMENT PRESSURE Sharpe, 1981). Fragmentation refers to the iso- The Conception Coast region faces immense lation of one part of a habitat area from another, and growing development pressure. In 2002, usually by a physical barrier such as a develop- there were 4,536 more acres of urbanized land ment, road or other impassable barrier, or to in Santa Barbara County than there were in the general reduction in available habitat area. 1990 (California Department of Conservation, Fragmentation of habitat undermines ecological 2002). This pressure, combined with a general integrity on at least two levels: by reducing the resistance to increasing the density of urban extent of habitat available to a species or species

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group, and by isolating wildlife groups in a way OIL DEVELOPMENT that narrows their genetic strength. A classic The Conception Coast region has also seen example of habitat fragmentation is a highway. increased pressure to develop onshore and Highway 33, running between the two wilder- offshore oil reserves in recent years. The U.S. ness areas, fragments the Dick Smith Wilder- Forest Service has issued a study analyzing the ness and the San Rafael Wilderness, disturbing potential for development of oil reserves in the historic animal linkages. Smaller fragmenta- Los Padres National Forest. Despite intense tion issues occur as a result of urbanization state opposition to increased oil development off and conversion of habitat to agricultural lands, California’s coast, the federal government and golf courses and housing subdivisions. While elected officials have made numerous attempts the fragmentation of habitat in the Conception to facilitate the exploration and development of Coast Region is extensive, a major finding of the 36 federal oil leases off California’s coast, this Regional Conservation Guide is that sig- most of which are off Santa Barbara County. nificant restoration of habitat connectivity is feasible. CLIMATE CHANGE Climate change will have impacts on ecosys- LOSS OF PREDATORS tems of the Conception Coast Region. Califor- The range of top predators such as black bears nia winters are expected to become warmer and and mountain lion has been significantly dimin- wetter during the next century. Summers will ished. This has allowed for prey such as deer also become warmer, but the temperature in- to swell in population. In turn, enhanced deer crease will not be as great as the winter increase populations impact grasslands and other vegeta- (Union of Concerned Scientists, 2003). Cali- tion through overgrazing. Similarly, mesopreda- fornia’s natural ecosystems are highly sensitive tors (predators which are prey for other preda- to the availability of water. Thus, changes in the tors) such as skunks and raccoons have swelled timing or amount of precipitation over the next in population. Thus, in many parts of the region century are likely to have a greater impact than ecological imbalance occurs as a result of top changes in temperature. For example, decreased predators being eliminated, disrupting a prop- summer stream flows would intensify compet- erly functioning system. Loss of any species ing demands for water to meet the needs of agri- from a biological community disrupts biologi- culture, industry, and urban areas, and to sustain cal structure, as with the explosion of rodent the health of California’s aquatic and streamside populations due to decline of coyotes, which has ecosystems. caused in dramatically decreased propagation success in oak woodlands. Overall, protection A large proportion of the effects of climate of “keystone species” – those species which change on California ecosystems will be indi- have an ecological influence disproportionate to rect; climate change may alter the frequency their numbers—is best achieved by setting aside and/or intensity of extreme weather events such connected wild lands. This protection provides as severe storms, El Niños, winds, droughts, and stability to wildlife communities and sustains frosts in still-uncertain ways. Similarly, the fre- the ecological services they provide. quency and/or magnitude of some ecologically

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important processes such as wildfires, flooding, Conversion of uncultivated land to agricul- and disease and pest outbreaks is likely to alter ture has caused significant impact on regional as climate changes occur. Altogether, these dif- resources. There are currently (2002) 8,321 ficult-to-predict phenomena, driven by shifts in more acres of cultivated land in Santa Barbara climate patterns, may be more important for the County than there were in 1990, mostly due future of California ecosystems than changes in to the conversion of grazing land (California average temperature and precipitation (Union of Department of Conservation 2002). Of these, Concerned Scientists, 2003). 5,404 acres of new cultivated land were created between 1998-2000 (California Department of AGRICULTURAL INTENSIFICATION Conservation 2002). Recent installation of new AND EXPANSION vineyards, primarily in the Santa Ynez Valley, Agriculture interacts with conservation plan- has resulted in significant loss of oak woodland ning in both beneficial and unfavorable ways. and savannah habitat and presented obstacles to In addition to its economic, historic and cultural wildlife movement. importance, agricultural landscapes define and, ideally, limit the extent of urban and suburban Intensification of agriculture also alters the land uses. Agriculture often establishes a vis- ecological value of the landscape it occurs on. ible boundary between land primarily reserved A rough hierarchy of the value of agricultural for dense human settlement and more lightly land for wildlife would assign highest ecologi- used and less developed areas at the transition cal value to grazing land, followed by orchards between urban and wild lands. While highly and dry farmed crops, followed by irrigated row mechanized and intense forms of agriculture crops. Agricultural practices such as application such as irrigated row crops offer little in terms of pesticides, water use, wastewater manage- of habitat, they represent a landscape that retains ment and other stewardship factors dramatically options – it has not generally been compacted, affect the impact of agriculture on habitat value. paved and transformed permanently as have the core of urban and suburban areas. Less intense AQUATIC FRAGMENTATION agricultural landscapes such as grazing land In stream barriers have fragmented many wa- often host valuable habitat and, despite strong terways in the Conception Coast Region. This and growing pressure for conversion to residen- disrupts the flow of ecological processes, in- tial or other uses. Retaining the large single- cluding the spawning (egg-laying) by steelhead, owner working landscapes of the Region such a keystone species. The steelhead’s return from as cattle ranches is a high priority for conser- years at sea to spawn and to enter the food web vation. As discussed below, agricultural prac- is one of the few ecological processes in which tices vary widely, and all forms of agriculture nutrients are returned to the landscape from the have environmental consequences that should ocean, instead of vice versa. There are many be addressed on an ongoing basis. However, other beneficial effects of a vibrant steelhead agriculture can and will play a significant role in population. Unfortunately, dams in large rivers conservation planning for the future. such as the Santa Ynez, Ventura and Santa Clara prevent Southern steelhead from reaching most

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historic spawning grounds. Culverts and road EROSION crossings have also fragmented smaller creeks Human induced erosion can be caused by nu- especially on the South Coast. In addition, merous activities including mining, urban de- water flows are often diverted or altered causing velopment and agricultural operations. Exposed significant changes to the streams. soil that breaks down under the pressures of the wind and air ends up clogging rivers and creeks. LOSS OF NATIVE SPECIES Habitat for fish and other animals is degraded Depletion and loss of native species is occur- by excessive erosion. In addition, erosion from ring at an alarming rate and is clearly evident urban projects has contributed to degradation of here in the Conception Coast Region. Loss of our creeks and rivers. native species destabilizes the natural system as the ecological roles (predator-prey relationships, LACK OF COORDINATED CONSERVATION or seed transport, for example) are vacated and STRATEGY often re-occupied by invasive species, which The creation and management of protected areas crowd and compete with natives but do not serve in the Conception Coast region has occurred the displaced species ecological role. Species without a regionally coordinated strategy. While loss tends to simplify biological community a crucial tool, the Endangered Species Act is structure, leading to weaker and more highly based upon an inefficient, last minute species- fluctuating population dynamics. Weaker bio- by-species approach to conservation that has logical systems face greater likelihood of signifi- proven expensive and insufficient. The Regional cant species declines, and the attendant social Conservation Guide will aid in coordinating a controversy over measures for their recovery. regional conservation strategy.

EXOTIC SPECIES There are positive forces that aid natural areas in The introduction of exotic species such as Eu- our region. The Conception Coast Region ben- ropean grasses, argentine ants – even household eﬁts from environmental and social factors that pets and livestock – has changed the vegetation positively inﬂuence the extent and condition of and ecology of the land. Invasive species have its natural resources. One is the high percentage altered ecosystem structures in chaparral and na- of publicly owned land that is protected to some tive grassland areas through a process described degree, including the Los Padres and Angeles above. Nonnative eucalyptus trees and ice plant National Forests, several wilderness areas and are common along many coastal areas of the wild and scenic river segments, city and county region, displacing native plant communities. parks, the Channel Islands National Park, the Disruption of vegetation and soils due to road Channel Islands National Marine Sanctuary, building, development and agriculture are com- newly enacted marine reserves and privately mon pre-cursors to the introduction of invasive protected land. exotic species. There is strong and growing support for stewardship in the Region, as demonstrated through political awareness, activism and funding of

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conservation causes. Nonproﬁt and community organizations have aided in protecting key natural areas and bringing the community’s attention to potential harmful developments. These groups have often been effective as a last line of defense to projects deemed unsuitable for the area.

Existing environmental and socioeconomic trends will likely continue in the foreseeable future and development pressures are likely to continue to escalate in the Conception Coast region. The California Department of Finance projects that Santa Barbara County’s population will grow from its current 415,600 to 521,200 in 2020. Santa Barbara County’s agricultural land will also continue to face development pressure in the foreseeable future. In Santa Barbara County, 1491 net acres of land were urbanized during 1998-2000, compared to 264 acres during 1996-98. Most of the urbanization in these four years took place in the Santa Maria area.

Conception Coast Regional Conservation Guide Conception Coast Regional Conservation Guide Methods & Results Chapter 4

Chapter 4 Methods & Results

Mountain Lion - Felis concolor

Conception Coast Regional Conservation Guide Chapter 4 Methods & Results Methods & Results OVERVIEW OF REGIONAL CONSERVATION overlain such that, at a particular location on the PLANNING APPROACH landscape, the sum of the corresponding square The Regional Conservation Guide (RCG) is a of all the layers is determined. Similarly any long-term, landscape-scale planning tool that other algebraic manipulation can be performed. describes and depicts the long-term requirements of the landscape and natural resources of THE LEGACY FRAMEWORK the Conception Coast Region. The RCG draws Conception Coast Project’s (CCP) Regional together modern ecological principles and re- Conservation Guide extends and is based upon gional biological data using powerful computer conservation assessment models such as the technology. A Geographic Information System one developed by Dr. Frank Davis, Dr. David (GIS) is used to locate and depict biological Stoms, and colleagues at the UC Santa Barbara information such as the location of specific Biogeography Lab and the National Center animals or vegetation on a map. The RCG’s for Ecological Analysis and Synthesis (Davis, GIS framework divides the Conception Coast Stoms et al. 2003) for the State of California Region into a grid of one and one-half kilometer Resources Agency (http://legacy.ca.gov/). A re- “sites”, each of which are assigned a color-code vised manuscript of this model and its approach value for each of a series of ecological criteria. has been submitted to Ecology and Society Modern concepts of biology and ecosystem- (Davis, Costello and Stoms, submitted). This based planning are used to define a series of “Legacy Framework” is designed to help set conservation objectives as the basis for a set conservation priorities over large geographic re- of GIS “layers,” described below. These layers gions by examining the incremental value of all can be overlain to perform analyses that “syn- the specific areas within the region. It can use thesize” two or more criteria through a process relatively coarse biological and environmental of “map algebra.” The RCG adapts the power- information. The Legacy Framework is de- ful Legacy Framework tool developed at the signed to incorporate agricultural, aesthetic, and University of California, Santa Barbara, which resource use objectives in addition to terrestrial provides the recipe for these complex multi-lev- and aquatic biodiversity objectives. The terres- el analyses to produce first-ever map outputs for trial biodiversity component of the framework the Conception Coast Region to guide conserva- is the portion adopted by Conception Coast tion action over the long term (Davis, Stoms et Project. This portion of the framework recog- al. 2003). nizes and incorporates multiple tracks of conservation planning (Davis, Stoms et al. 2003). For a brief explanation of the above terms in The multiple tracks included in the framework quotes, imagine a piece of clear plastic Mylar are: protecting hotspots of threatened and with a square grid drawn on it. Each of those endangered species, representing habitat types, squares can have a color and numerical value representing biophysical landscapes, protecting associated with it that represents the impor- wild lands, and expanding existing reserves (i.e. tance of that square with respect to a particular protected areas) (Davis, Stoms et al. 2003). ecological objective, such as species hotspots. Then all of the layers are “synthesized,” or

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THE RCG MODEL tives to create a composite map identifying Two major additions were made to the terrestri- relative biodiversity values for each 1.5 km site. al biodiversity component of the Legacy Frame- This analysis identifies generic biodiversity work in creating the Regional Conservation value of each site without regard to its status Guide (RCG). The resulting model is termed inside, outside or near a protected area (e.g. the RCG Model. The changes include introduc- wilderness, etc) and without regard to the site’s ing the concept of “landscape connectivity” into expected degree of future habitat degradation the process, as well as providing an output of if no conservation occurs (i.e. no analysis of raw “biodiversity value” that is not influenced “threat” is included). The methodology for this by the complex concept of development threat. analysis is illustrated by Figure 4, and described These terms will be defined and described in the in Part 1, below. following methodological sections. The Regional Conservation Guide’s six ecologi- The second major finding of the RCG is the cal objectives are as follows. Each objective Regional Conservation Priorities Analysis Map, and its rationale are explained within the discus- which includes the concept of threat. Under sion of its use in the RCG Model. the Conservation Priorities Analysis, a site that RCG Ecological Objectives is important ecologically, but is not perceived 1. Conserve hotspots of endangered and to be threatened with development receives a threatened species lower conservation priority score. A site re- 2. Represent all habitat types within pro- ceives a high conservation priority value only if tected areas it is both important ecologically and threatened 3. Protect biophysical landscapes to main- with anticipated future degradation. A schemat- tain ecological and evolutionary processes ic of this analysis is provided in Figure 5. This 4. Protect wild lands for large carnivores finding is presented, along with the methods by and other area-dependent species which it was produced in Part 2, below. 5. Protect areas next to existing reserves 6. Establish landscape connectivity between wild lands

Each of these objectives is modeled through the input of existing biological data to create a GIS layer. Each layer is used by itself as an intermediate finding of the RCG, and is also combined with other layers to create subsequent analyses. The RCG Ecological Objectives are combined in different ways to create two major analyses. The first of the major findings of the Regional Conservation Guide is the Biodiversity Value Analysis Map. This analysis combines the layers representing each of the above RCG objec-

Conception Coast Regional Conservation Guide Chapter 4 Methods & Results

Figure 4: Diagram of the Biodiversity Value Analysis

Note: Arrows indicate the ﬂow of information and data.

Conception Coast Regional Conservation Guide Methods & Results Chapter 4

Figure 5: Diagram of the Conservation Priorities Analysis

Note: Arrows indicate the ﬂow of information and data.

Conception Coast Regional Conservation Guide Chapter 4 Methods & Results

PART 1: BIODIVERSITY VALUE ANALYSIS The resulting map is presented here in Figure This section provides the methodology of the 6: Human Impact Types within the Concep- Biodiversity Value Analysis of the RCG Model, tion Coast Region. To see the relative impact along with the maps of the results. For a more of these land use types, see Figure 7: Estimated detailed treatment of this methodology, see Degree of Human Impact within the Conception Appendix A: RCG Detailed Methodology. The Coast Region. Again, the details are provided analysis results from the combination of GIS in Appendix A. layers representing four of the six ecological objectives listed above plus a GIS layer called BIODIVERSITY OBJECTIVE B1: CONSERVE Human Impact on Habitat at Year 2000, which HOTSPOTS OF ENDANGERED AND THREATENED depicts human impact on the landscape. SPECIES Efﬁcient conservation effort requires direct- HUMAN IMPACT ON HABITAT AT THE YEAR 2000 ing conservation resources towards areas that Many of the ecological data used in the RCG are most vulnerable as well as contain high analyses identify the species or ecological levels of biodiversity. Imperiled species usu- communities that are present at a location, but ally include those with small populations, large the data do not indicate condition of the site. ranges, poor dispersal abilities, low reproduc- For example, species data do not distinguish tion potential, or dependence on habitats that between a stand of oaks surrounded by a golf are themselves threatened (Noss 1991). Many course and roads versus one in a wilderness conservation efforts give high priority to areas area. To incorporate this important ecological that support high densities of geographically distinction, the Human Impact 2000 layer is restricted, threatened and endangered species combined with each of the GIS layers represent- (Dobson et al. 1997, Abbitt et al. 2000, Chaplin ing ecological objectives. et al. 2000 in Davis, Stoms et al. 2003).

The Human Impact layer is a product of six dif- To form the Listed Species Hotspots Layer, a ferent sub-layers. These sub-layers include: list of species was compiled that ﬁt the criteria -Development densities of rare, endemic and threatened. Species that -Industrial lands are utilized in this model and hereafter called -Agricultural lands “listed” species are: -Grazing lands -State and Federal Endangered, Threatened, -Roads Proposed Endangered, Proposed Threat- -Reserves (areas under some form of protec- ened, Candidate, and CA Rare species. tion) and known conservation easements. -Imperiled Species of Natural Heritage List- ing System (i.e. G1 or G2) The sub-layers were weighted for their impor- -State or Federal Species of Concern, or tance in affecting overall ecological condition California Native Plant Society Rare Listing by CCP’s ecological advisors. The six sub-layers were merged and the highest potential hu- These data were then placed into a GIS to create man impact value for any given area was used. a map layer, using a data accuracy ranking code

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Figure 6: Human Impact Types within the Conception Coast Region FRONT

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Figure 6: Human Impact Types within the Conception Coast Region BACK

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Figure 7: Estimated Degree of Human Impact within the Conception Coast Region FRONT

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Figure 7: Estimated Degree of Human Impact within the Conception Coast Region BACK

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and combining several different data sources to their status in protected areas. Representation insure completeness (Figure 8: Listed Species can also be understood using the metaphor of Locations within the Conception Coast Region). tinkering with the motor of an automobile: in order to ensure the continued function of the The Listed Species Hotspot value assigned to a motor, one must “keep all the pieces.” site was determined by combining: -the listed species at the site, Allowing for better inclusion of poorly repre- - the level of data confidence for each obser- sented natural communities within protected ar- vation, eas enables the survival needs of large numbers -the degree of endemism (rarity) of each of species to be met simultaneously with less species based on the total area of known oc- reliance on individual species protection. Thus, currence in the region, representing all habitats serves as a “coarse -the level of human impact at the site, filter” serving to ensure the representation of -and the human impact at all other sites species for which little data exists. where the species occurs (Davis, Stoms et al. 2003). The RCG adds to the concept of habitat representation by assigning greater weight to habi- Maps produced from this analysis were then re- tats that are known to be scarce, or that occur fined to produce a smoother, less blocky appear- below their historical range due to conversion ance than would be achieved using the raw, 1.5 to human uses (e.g. development). In addition, kilometer site grid. This presentation depicts certain habitats host species that have declined the fluid and interconnected aspects of eco- or are regularly the focus of species recovery logical processes. It also conveys the inherent efforts. Such habitats might be common in the variability of data when collected on a regional region, but scarce elsewhere in the ecoregion or scale. The final results of all objectives in both state, and thus merit more attention. models utilize this procedure of smoothing results. For a full explanation of this process, The locations of each habitat were determined please refer to Appendix A. The results for this using a widely recognized dataset called the objective are displayed here in map form as Multi-Source Land Cover Data (MLCD) (i.e. Figure 9: Listed Species Hotspots Biodiversity Figure 3). A “weight” (relative value) of each Value within the Conception Coast Region (B1). habitat was determined and is a function of these items: rarity of habitat (rare areas are BIODIVERSITY OBJECTIVE B2: REPRESENT ALL assigned a higher value), ecoregional context HABITATS WITHIN PROTECTED AREAS (habitats which are rare elsewhere besides the Modern biological and ecological science has CCP region are valued higher), the estimate of long supported the necessity of representing all historical habitat loss (areas with large historical habitat types within protected areas in order to losses are valued higher) and inherent habitat ensure long term protection of the entire region- value. al ecosystem. “Representation” is the process of identifying various habitats and assessing In sum, the site’s habitat representation value is

Conception Coast Regional Conservation Guide Chapter 4 Methods & Results

a function of the following: a wild land -the habitat types at the site and their cor- -amount of human impact on that land responding weights, -the amount of each habitat type at the site The results are mapped in Figure 12: Wild -the human impact on the land in the site, Lands Biodiversity Value within the Conception -and the amount of human impact on all Coast Region (B4). other sites where the habitat occurs (Davis, Stoms et al. 2003). BIODIVERSITY OBJECTIVE B6: ESTIMATE LANDSCAPE CONNECTIVITY BIODIVERSITY VALUE The results highlighting priority habitats for Connectivity is the concept that if two or more their conservation value were mapped and are large areas of quality habitat are connected by a again indicated as a map, Figure 10: Habitat narrower area of habitat that facilitates animal Representation Biodiversity Value within the movement, then the overall biodiversity value Conception Coast Region (B2). of the region is increased (Soule and Terborgh 1999). These areas of connecting habitat are BIODIVERSITY OBJECTIVE B4: ESTIMATE WILD termed landscape linkages, or “linkages” for LANDS BIODIVERSITY VALUE short. These linkages allow individuals to move Conservation scientists have increasingly from one habitat area to another, enlarging the promoted the landscape-scale conservation available genetic pool to avoid inbreeding and beneﬁts of protecting large wild areas that serve allowing slower moving species to move across as habitat for large carnivores and other wide- the landscape in response to changing condi- ranging species that require large natural areas tions. If a species is “extirpated” (made locally for survival (Soule and Terborgh 1999). These extinct) from an area of habitat, such as through large wild areas also allow ecological processes a wildﬁre or disease, then that population can and dynamics to proceed naturally. In addition be replenished by a surviving population from to maintaining populations of space demand- another habitat area by way of the linkage. ing species, and the food web that they support, Maintaining connectivity between protected ar- wild lands also provide habitat for disturbance eas is also a mechanism to reduce the total area sensitive species. of protected lands needed to sustain long-term ecological health—since the alternative is a This model estimates the location of suitable single, overall larger protected area. The con- “core” wild areas, based on large areas of concept of connectivity applies at all scales, such tiguous low average human impact. The results as the suitable habitat between horned lizard are again reported in map form (Figure 11: Lo- populations, as well as the river corridors and cations of Large Wild Lands in the Conception ridgelines that connect populations of mountain Coast Region). lion.

The wild lands biodiversity value of each site is A connectivity analysis is ideally performed at simply a function of multiple scales, but if only one scale is fea- -the amount of land of the site that is within sible, it is best to use a coarse scale approach

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Figure 8: Listed Species Locations within the Conception Coast Region FRONT

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Figure 8: Listed Species Locations within the Conception Coast Region BACK

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Figure 9: Listed Species Hotspots Biodiversity Value within the Conception Coast Region (B1) FRONT

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Figure 9: Listed Species Hotspots Biodiversity Value within the Conception Coast Region (B1) BACK

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Figure 10:Habitat Representation Biodiversity Value within the Conception Coast Region (B2) FRONT

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Figure 10:Habitat Representation Biodiversity Value within the Conception Coast Region (B2) BACK

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Figure 11: Locations of Large Wild Lands within the Conception Coast Region FRONT

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Figure 11: Locations of Large Wild Lands within the Conception Coast Region BACK

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Figure 12: Wild Lands Biodiversity Value within the Conception Coast Region (B4) FRONT

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Figure 12: Wild Lands Biodiversity Value within the Conception Coast Region (B4) BACK

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to ensure the core wild lands of a region are -Mountain lion habitat suitability (See Fig- interconnected. Unless a protected area is mil- ure13: Habitat Quality for Mountain Lion lions of acres in size, individual core protected Dispersal). areas will not be able to function independently -Human Impact Value as whole ecosystems, in the sense of maintain- -A specific consideration of roadedness, the ing viable populations of animals and ecological primary source of death to mountain lions and evolutionary processes (Noss and Harris in southern California (Beier 1995; Beier, 1986). The mountain lion was selected as the Choate et al. 1995) connectivity focal species because it operates at this coarse scale, with males having a home The movement cost was analyzed using the range of nearly 400 square kilometers (Dickson gated least cost path to create a data layer that 2001). The mountain lion is also a keystone identifies the major movement linkages and species since it maintains the integrity of an their relative values (See Figure 14: Large ecosystem by controlling the population of large Wildlife Linkages within the Conception Coast herbivores and “meso-predators” (medium sized Region). The final connectivity biodiversity predators such as skunk and opossum). The value of a site is a function of: loss of such keystone species are more profound -the quality of the landscape linkage that the and far-reaching than others, because their site lies within elimination from an ecosystem often triggers -the mountain lion habitat suitability of the cascades of direct and indirect changes, leading site eventually to loss of habitat and extirpation of -the amount of human impact on the land in other species in the food web (Noss and Soule the site 1999). The results are given in map format as Figure A “least cost path” analysis was utilized that in- 15: Landscape Connectivity Biodiversity Value dicates the path between two habitat areas with within the Conception Coast Region (B6). the lowest level difficulty of travel (i.e. “movement cost”) for a mountain lion. A movement SYNTHESIS PART 1: ESTIMATE AND MAP cost GIS layer is created such that the value of “BIODIVERSITY VALUE” every location has a measure of how difficult Ecological advisors weighted the four objec- or dangerous it is for a mountain lion to move tives (Habitat Representation, Listed Species across it. For example, a path across highway Hotspots, Wild Lands and Connectivity) at a 101 will have a very high cost, whereas the workshop. The results are as follows: Habitat path in the wilderness forest will have a very Representation: 20, Listed Species Hotspots: low cost. The “gated” variety of least cost path 15, Wild Lands: 10 and Connectivity: 10. The analysis used provides an output that has a layers of these objectives were combined to- width rather than a very fine line of habitat con- gether using these relative weights to determine necting two wild lands. Movement cost, which the Biodiversity Value of each site. The final is the foundation of the analysis, is a combina- results represent Part 1 of the Major Findings of tion of: the Regional Conservation Guide, and appear in

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map format as Figure 16: Estimated Biodiver- PROJECTED HUMAN IMPACT FOR THE YEAR 2050 sity Value within the Conception Coast Region. This analysis models the predicted land use changes in the region over the next half a PART 2: CONSERVATION PRIORITIES ANALYSIS century. These changes constitute a vital con- The Conservation Priority Analysis of the RCG sideration in deriving the “threat” layer and Model estimates the conservation value of the in identifying conservation priorities. This different areas in the region based on biodiver- analysis combines an urban growth sub-model, sity value objectives and on development threat. a suburban growth sub-model, an agricultural This section provides the methodology of the expansion sub-model, and an oil and gas expan- Conservation Priorities Analysis, along with the sion sub-model. maps of the intermediate and synthesis results. For a more detailed treatment of this methodol- The urban outgrowth sub-model used was de- ogy, see Appendix A: RCG Detailed Methodol- rived by a team at U.C. Berkeley and is called ogy. the California Urban and Biodiversity Assess- ment (CURBA) model (Landis, Cogan et al. The Conservation Priorities Analysis results 1998). CURBA predicts future urban growth from the combination of five of the ecological patterns based on indicators of past growth pat- objectives to determine the resource value of terns (Fulton, Wilson et al. 2003). The model is the site and combines this resource value with driven by human population growth, and uses threats (habitat conversion and degradation) to the same growth predictions used by the state the landscape. The five objectives utilized are: to formulate policy (Department of Finance C1) Conserve hotspots of endangered and 2004). For a depiction of the CURBA outputs, threatened species see Figure 17: Comparison of Current and C2) Conserve important habitats Predicted Urban Extent within the Conception C4) Protect wildlands for large carnivores Coast Region. and other “area-dependent species” C5) Protect areas next to existing reserves To model rural and suburban growth in the re- C6) Establish landscape connectivity be- gion, CCP utilized the Western Futures Growth tween wild lands Model (WFGM) developed by David Theobald of the Natural Resource Ecology Lab at Colo- A major characteristic of this analysis is that it rado State University (Theobald 2001). This incorporates a projection of how the landscape sub-model also bases is projections based on will likely be modified over time (e.g. from past patterns, but rather than looking solely at wild land to suburban) which is termed “threat”. urban growth, it considers growth of all devel- The threat layer is derived from this prediction opment densities. The primary data inputs are of landscape change, which aids in identifying past and present U.S. Census Data patterns, high biodiversity areas likely to be degraded in distance from urban centers, and the population the future, and thus, conservation priorities. growth predictions of state demographers. For a depiction of the model results for our region, see Figure 18: Comparison of Current and Pre-

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Figure 13: Habitat Quality for Mountain Lion Dispersal FRONT

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Figure 13: Habitat Quality for Mountain Lion Dispersal BACK

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Figure 14: Large Wildlife Linkages within the Conception Coast Region FRONT

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Figure 14: Large Wildlife Linkages within the Conception Coast Region BACK

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Figure 15: Landscape Connectivity Biodiversity Value within the Conception Coast Region (B6) FRONT

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Figure 15: Landscape Connectivity Biodiversity Value within the Conception Coast Region (B6) BACK

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Figure 16: Estimated Biodiversity Value within the Conception Coast Region FRONT

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Figure 16: Estimated Biodiversity Value within the Conception Coast Region BACK

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Figure 17: Comparison of Current and Predicted Urban Extent within the Conception Coast Region FRONT

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Figure 17: Comparison of Current and Predicted Urban Extent within the Conception Coast Region BACK

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Figure 18: Comparison of Current and Predicted Housing Density within the Conception Coast Region FRONT

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Figure 18: Comparison of Current and Predicted Housing Density within the Conception Coast Region BACK

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dicted Housing Density within the Conception cies already incorporates the concept of threat Coast Region. by deﬁnition, the GIS layer for Objective B1 is used for Objective C1 in the synthesis stage Areas available for agriculture expansion within of the Conservation Priorities Analysis (Davis, a half a century were all areas that did not meet Stoms, et al. 2003). one of the following conditions: urban lands, reserves, conservation easements, current indus- CONSERVATION OBJECTIVE C2: HABITAT REPRE- trial areas, roads, water, creeks, and areas with SENTATION CONSERVATION VALUE too steep of a slope for agricultural operations. The analysis that created the Habitat Represen- tation Biodiversity Value layer was augmented The oil and gas industrial expansion model sim- to include the concept of threat to create a ply mapped out the two most likely oil extrac- new layer, Habitat Representation Conserva- tion scenarios being planned for national forest tion Value. Thus, the Habitat Representation land (USDA Forest Service 2001). The areas Conservation Value of a site is a function of the that occur in both scenarios are given a higher following: likelihood of development. -the habitat types at the site and their corresponding weights, The urban, suburban, agriculture and industrial -the amount of each habitat type at the site layers were overlaid to create the Human Im- -the amount of human impact of land in the pact Layer 2050. For an illustration of this GIS site, layer, and a comparison with the 2000 layer, see -and the amount of human impact at all Figure 19: Comparison of Current and Predicted other sites where the habitat occurs Human Impact within the Conception Coast -projected threat to the habitat on the site in Region. 2050 if no conservation occurs -and the threat on the total amount of that The above two layers were used to create the habitat in the region in 2050 if no conserva- “threat” layer. Threat to an area is based on tion occurs. predicted change between now and a half-century from now and is quantiﬁed by subtracting For an illustration of the results, see Figure 21: the Human Impact Value of that area in 2000 Habitat Representation Conservation Value from the predicted value in 2050. The layer within the Conception Coast Region (C2). that results from this difference is called the threat layer for the remainder of the document, CONSERVATION OBJECTIVE C4: WILD LANDS CON- and is depicted as Figure 20: Predicted Change SERVATION VALUE in Human Impact within the Conception Coast The Wild Lands mapped for B4 were used Region (i.e. Threat). along with the threat layer to create a value for C4. The value of a site is a function of the fol- CONSERVATION OBJECTIVE C1: LISTED SPECIES lowing: HOTSPOTS CONSERVATION VALUE -the amount of land of the site that is within Due to the fact that rare and threatened spe- a wild land

Conception Coast Regional Conservation Guide Chapter 4 Methods & Results

-amount of human impact on that land reserves is considered more valuable to the re- -the threat at the site if no conservation oc- gion’s overall biodiversity than adding to larger curs reserves. Thus, the value of a site is a function --the cumulative threat on the entire wild of the following considerations: land the overlaps that site if no conservation -distance to the nearest reserve occurs -size of the nearest reserve -threat at that site if no conservation occurs For a map of the resulting layer see Figure 22: Wild Lands Conservation Value within the Con- For a map of the resulting layer, see Figure 23: ception Coast Region (C4). Reserve Adjacency Conservation Value within the Conception Coast Region (C5). CONSERVATION OBJECTIVE C5: RESERVE ADJA- CENCY CONSERVATION VALUE CONSERVATION OBJECTIVE C6: LANDSCAPE CON- Expanding small reserves is an efﬁcient, low NECTIVITY CONSERVATION VALUE cost option to advance maintenance of species The importance of landscape connectivity was diversity. The species area curve derived from explained in Part 1. To produce the layer for island biogeography indicates that the number this objective, the connectivity layer that was of species that can co-exist in an area increases created for B6 was multiplied by the threat layer when the size of the area increases, but this in- to produce the landscape connectivity conserva- crease in an inverse exponential manner. For an tion value layer. example, if a 100 acre area is conserved directly adjacent to a 100 acre reserve, the reserve area The connectivity conservation value of a site is is doubled. Subsequently, the number of ver- thus a function of tebrates that this combined reserve can harbor -the quality of the landscape linkage that the may increase by 50%, say from 100 to 150. At site lies within a later date, 200 more acres are conserved di- -the mountain lion habitat suitability of the rectly adjacent, and the reserve is again dou- site bled. However, due to the species area curve, it -the amount of human impact on the land in is unlikely that 50% more species will be able to the site live solely in that reserve. A more likely result -the threat at that site if no conservation would be a 25% increase, from 150 to about occurs 190 species. The second conservation action required a bigger land purchase and provided For an illustration of the resulting layer, please refuge for less species. Thus, conserving areas see Figure 24: Landscape Connectivity Con- adjacent to small reserves is one of the effective servation Values within the Conception Coast strategies for biodiversity conservation. Region (C6).

The Reserve Adjacency Conservation Value SYNTHESIS PART 2: OVERALL CONSERVATION assigns value to regional sites that are close to PRIORITY existing reserves. Further, adding to smaller To produce the Conservation Priority Value

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map, the ﬁve GIS layers representing the ecological objectives were combined with the threat value layer. The resulting site values were then smoothed, as per the methodology described in B1. The ﬁnal results represent part two of the Major Findings of the Regional Conservation Guide, and indicate the conservation priorities for the region. Please see Figure 25: Estimated Conservation Priorities within the Conception Coast Region.

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Figure 19: Comparison of Current and Predicted Human Impact within the Conception Coast Region FRONT

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Figure 19: Comparison of Current and Predicted Human Impact within the Conception Coast Region BACK

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Figure 20: Predicted Change in Human Impact within the Conception Coast Region (i.e. “Threat”) FRONT

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Figure 20: Predicted Change in Human Impact within the Conception Coast Region (i.e. “Threat”) BACK

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Figure 21: Habitat Representation Conservation Value within the Conception Coast Region (C2) FRONT

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Figure 21: Habitat Representation Conservation Value within the Conception Coast Region (C2) BACK

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Figure 22: Wild Lands Conservation Value within the Conception Coast Region (C4) FRONT

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Figure 22: Wild Lands Conservation Value within the Conception Coast Region (C4) BACK

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Figure 23: Reserve Adjacency Conservation Value within the Conception Coast Region (C5) FRONT

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Figure 23: Reserve Adjacency Conservation Value within the Conception Coast Region (C5) BACK

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Figure 24: Landscape Connectivity Conservation Values within the Conception Coast Region (C6) FRONT

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Figure 24: Landscape Connectivity Conservation Values within the Conception Coast Region (C6) BACK

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Figure 25: Estimated Conservation Priorities within the Conception Coast Region FRONT

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Figure 25: Estimated Conservation Priorities within the Conception Coast Region BACK

Conception Coast Regional Conservation Guide Interpreting the Major RCG Findings Chapter 5

Chapter 5 Interpreting the Major RCG Findings

Conception Coast Regional Conservation Guide Chapter 5 Interpreting the Major RCG Findings Interpreting the Major RCG Findings Regarding the findings of the Regional Conser- their priority in contributing to regional ecologi- vation Guide, it should be noted that the map cal requirements. outputs representing individual objectives such as connectivity and listed species hotspots are BIODIVERSITY VALUE ANALYSIS also valuable by themselves as an aid to conser- A wide array of places were identified as ar- vation. It is also important to recognize that the eas of importance in the Biodiversity Value RCG does not intend to suggest that those areas Analysis. As one might expect, areas such as not receiving high value rankings should not be the Gaviota Coast, the Sespe Watershed and considered for conservation, nor that they be Vandenberg Air Force Base were identified as considered as good areas for development. especially biologically important, given these locations’ large wild expanses and/or relatively The Conservation Priorities Analysis presents low-density development. However, other less options for a region-wide system of protected well-known areas such as Buckhorn Ridge, areas that meet the needs of the landscape for Mount Pinos, and Mountclef Ridge were ranked long-term ecological sustainability. To be clear, especially high in biodiversity value as well. all of the areas identified as conservation priorities need not be secured in “reserves” – or high- Areas mapped as high biodiversity value re- ly protected status such as wilderness— in order ceived elevated rankings due to some combina- to maintain the region’s ecological integrity. tion of the following: status as a listed species “Stewardship zones” —areas of quality habitat hotspot, value in adding to full habitat represen- that allow for human use of the landscape si- tation, value as a wild area, or the site’s role in multaneous to managing for biodiversity—may contributing to connectivity of habitats. These be used as part of an effective network of re- rankings also consider the current land-use and gional conservation designations. Stewardship human density in determining ecological value, zones can occur on public and private lands and but they do not consider the notion of threat; include certain types of agricultural and graz- thus, for example, areas with a high likelihood ing practices, ecologically sustainable forestry, of development in the near future are treated and recreational use such as hunting and fishing. similarly to areas without threat. As shown in Methods for securing protection for such zones Figure 16, areas of high biodiversity value are are discussed in the final chapter of this docu- numerous and widely distributed. Some areas ment. show up as high biodiversity value because they are exceptionally high in a single criteria, while This section first discusses the Biodiversity other such areas rank well under several critera. Value Analysis map (Figure 16: Estimated Biodiversity Value within the Conception Coast To illustrate, consider the Gaviota Coast and Region), which identifies regional high biodiver- Western Santa Ynez Mountains in the south- sity areas, followed by a discussion of the Con- western part of the region, one of the largest servation Priorities map (Figure 25: Estimated areas of contiguous high and very high biodi- Conservation Priorities within the Conception versity value. This large swath of green extends Coast Region), which ranks regional sites for from the Jalama Watershed in the West to the

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mountains above Goleta in the East. By ex- By examining the geographic extent of high and amining Figures 9, 10, 12, and 15, it becomes very high conservation priority values, five key apparent that this high biodiversity value area areas were identified as conservation priority derives its score from many medium high to areas: very high scores from all four objectives. There 1. Caliente Range is a large Wild Land in the mountains between 2. San Rafael Mountains near Figeroa Refugio Road and Highway 154 (Figure 11). A Mountain high quality landscape linkage provides con- 3. Gaviota Coast and Western Santa Ynez nectivity between this Wild Land and the one on Mountains Vandenberg Air force Base (Figure 12). In addi- 4. Santa Susanna Mountains to the Simi tion, there are numerous listed species along the Hills and Conejo Grade Gaviota Coast, and many of the quality occur- 5. Vandenberg Air Force Base region rences of these species occur in this sub-region, which explains the many high scores in Figure By definition, these areas have important biodi- 9. Habitat representation scores are medium- versity features and are in areas predicted to be high in many places due primarily to coastal oak affected by human land conversion in the future. woodland and coastal scrub, and are high in a For a more nuanced discussion of this statement, few places due to the closed-cone pine cypress see the brief summaries below. (Figure 3 and Figure 10). These pine/cypress forests are rare throughout the region, so even CALIENTE RANGE small forests are of high biodiversity value. In The Caliente Range stretches along the northern summary, the intermediate analyses and result- part of the CCP Region and is bordered to the ing figures can indicate how the model allocates south by the Cuyama Valley. This remote range biodiversity value. is an important Wild Land and is home to many listed species. To the south of the Caliente SELECTED KEY CONSERVATION PRIORITY Range, agriculture is heavily established in the AREAS Cuyama Valley and growth scenarios indicate an The Conservation Priority Analysis builds outward expansion of agriculture into sensitive upon the Biodiversity Value Analysis. An habitat. As a result of the agriculture expan- additional consideration in the analysis is the sion, habitats that are underrepresented such as value assigned to expanding protected areas of juniper and blue oak woodland, as well as large the region, termed Reserve Adjacency. Also, expanses of coastal sage scrub are under threat. the Conservation Priority Analysis includes a Also, this area received an elevated score in threat layer that identifies areas most likely to the expanding reserve module as natural areas be affected by urban, suburban, agricultural and around the protected portions of the Caliente oil expansion. This threat layer focuses higher Range. As a result of its high biodiversity values on areas that are predicted to have a large importance coupled with the anticipated agri- degree of increase in human impact over the cultural expansion from the Cuyama Valley, the next half century (See Chapter 4). Caliente Range is an example of a large contiguous area of high conservation priority.

Conception Coast Regional Conservation Guide Chapter 5 Interpreting the Major RCG Findings

SAN RAFAEL MOUNTAINS NEAR FIGUEROA lighted as important areas for reserve expansion. MOUNTAIN In summary, the Gaviota Coast is identified as On the outskirts of the San Rafael Wilderness, another important conservation priority for the the Figueroa Mountain area is one of the high- region. lighted conservation priorities for the region. This area is not especially large, but has a very SANTA SUSANNA MOUNTAINS TO THE SIMI high conservation value. The area has a wide HILLS AND CONEJO GRADE variety of montane hardwood and conifer forests The highest amount of urban and suburban and is home to numerous listed species. Due to development in the region is expected in the a low amount of roads or other human impact, areas surrounding Thousand Oaks, Camarillo, the area is considered a Wild Land. The area also Moorpark, Simi Valley and Santa Clarita. The ranks high in the Reserve Adjacency objective, urban outgrowth model indicated these areas in as it is next to the small Sedgwick Reserve and the southeastern part of the region should expect the larger San Rafael Wilderness. The driving significant growth in the coming decades. The force behind its very high score is the threat suburban outgrowth model highlighted these layer, as Figueroa Mountain has also been identi- areas as well; furthermore, Santa Clarita is ex- fied as a priority area for oil and gas drilling by pected to have a major burst of suburban growth the United States Forest Service (USDA Forest to its west, creating unbroken suburban sprawl Service 2001). In summary, the high degree of connecting Santa Clarita to Simi Valley and threatened change in human impact coupled with Thousand Oaks. Areas surrounding these cities high scores in four of the five ecological objec- are also likely areas for agricultural expansion. tives results in this area being a high conserva- Meanwhile, the remaining undeveloped parts of tion priority. this area are also very important ecologically. This area provides a landscape linkage between GAVIOTA COAST the Santa Monica Mountains and the San Ber- The Gaviota Coast is among the world’s shining nardino Mountains in the East, and the Topatopa examples of a large undeveloped coastal area of Mountains in the north. If the Santa Monica the Mediterranean climate type. It is identified Mountains were to lose these linkages and in as a conservation priority because of the impor- effect become an island of habitat, it is likely tance to biodiversity, discussed above, as well as that the small mountain lion population would the moderate degree of threat. In the analysis, suffer from inbreeding, and very easily become portions of coastline were identified as under extant (locally extinct). As discussed earlier, threat from urban, suburban and oil expansion. losing this and other top carnivores would have The Forest Service identified Gaviota Peak and negative repercussions throughout the food portions of the Santa Ynez ridgeline as priority web. Further, many of the areas that are key to areas for oil expansion (USDA Forest Service maintaining this landscape connectivity are also 2001). In addition to the biodiversity values home to important listed species. These are the discussed above, the expanding reserves analysis two ecological objectives that score the highest ranks high as well, as areas surrounding Gaviota, of the five. The habitat representation objectives El Capitan and Refugio State Parks were high- scores moderately due mainly to expanses of

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coastal sage scrub, as well as small pockets of tifies many areas on the base threatened with oak woodland and montane riparian. In summa- increased human impact. With the possibility ry, with the anticipated shift in land use coupled for conversion to agriculture along with its high with the many listed species and high connectiv- scores in the listed species, underrepresented ity value highlight this area is a major conserva- habitat and important wild lands objectives, the tion priority for the region. Vandenberg Air Force Base region is identified as an important conservation priority area. VANDENBERG AIR FORCE BASE REGION Vandenberg Air Force Base is a large, mostly LIMITATIONS AND OPPORTUNITIES undeveloped coastal area on the western edge The products of the Regional Conservation of the study area. It starts to the north of Point Guide are meant to provide decision support, but Conception at Jalama Creek and stretches nearly are not meant to be the final word on any issue. to Point Sal, and is used by the Air Force as a Models are representations of the world, and major military base. Thanks in part to a military should be treated as such. This first iteration of mandate emphasizing environmental steward- the RCG combines a great wealth of data, the- ship, the area contains a wealth of biodiversity ory, and analyses to provide an unprecedented and areas of pristine natural resources. The base resource for the regional community. However, has two Wild Lands: the mountainous area in nature is inherently complex, so any attempt to and around Honda Creek Watershed on South model its conservation priorities will be a best Base, and the coastal dunes and lowlands around estimate. There are undoubtedly areas that are a the San Antonio Terrace on North Base. Land- high conservation priority although they are not scape linkages exist adjacent to these areas. The mapped as such, and vice versa. The reliability entire base is also home to a large variety and of such an estimate improves as the number of high density of listed species, yielding very high input data and ecological sub-analyses are in- scores for the listed species objective. Habitat creased. While these may be considered limita- representation has high scores, with extensive tions of the model, we prefer to consider these riparian habitat, forests of closed cone pine/cy- as opportunities. For instance, a more explicit press, oak woodlands, and expanses of coastal treatment of the aquatic resources in the region sage scrub and mixed chaparral. Vandenberg could be performed. Similarly, a focal species is not a permanently protected area and is thus approach of conservation planning could be open for alteration in the future. The threat utilized more heavily. In such an approach, one model does not assume that the exemplary en- to three dozen focal species are carefully chosen vironmental stewardship on the base will auto- based on characteristics such as ecological func- matically continue for the next half century. The tion or rarity. The distribution and habitat needs base is subject to the political winds in Wash- of these species are mapped and overlaid, and ington DC, and there has been an effort in recent combined with the other objectives. For both years to lessen the environmental stewardship of these opportunities for model refinement, a mandate of military installations. To indicate “regional eco-database” could be created from this threat, and because agriculture and grazing pre-existing observations and knowledge, as are already allowed on the base, the model iden- well as data gathered over time. Creation of

Conception Coast Regional Conservation Guide Chapter 5 Interpreting the Major RCG Findings

such a database would not only augment all the objectives, but would also enrich the sense of place of all participants. Inter-organizational collaborations are also possible, such as combining a “Regional Impacts of Growth” type study for the region to reﬁne the threat model (Santa Barbara Region Economic Community Project, 2003). In short, iteration one of the Regional Conservation Guide is an invaluable resource, with many opportunities available for incremental improvement.

Conception Coast Regional Conservation Guide Interpreting the Major RCG Findings Chapter 5

Conception Coast Regional Conservation Guide Conception Coast Regional Conservation Guide Implementing The Regional Conservation Guide Chapter 6

Chapter 6 Implementing The Regional Conservation Guide

Barn Owl - Tyto Alba

Conception Coast Regional Conservation Guide Chapter 6 Implementing The Regional Conservation Guide Implementing The Regional Conservation Guide The findings of the RCG present options for a (EDAW 2002). The Land Trust for Santa Bar- region wide system of protected areas that meet bara County initiated talks with receptive land- the needs of the landscape for long-term ecolog- owner J.J. Hollister, which resulted in the Land ical sustainability. To be clear, all of the areas Trust agreeing to purchase the land the 782-acre identified as conservation priorities need not ranch for seven million dollars in late 2001. be secured in “reserves” – or highly protected status such as wilderness— in order to maintain EASEMENTS FOR CONSERVATION, OPEN SPACE, the region’s ecological integrity. “Stewardship AGRICULTURAL PROTECTION zones” —areas of quality habitat that allow for Conservation easements are voluntary deed re- human use of the landscape simultaneous to strictions put on land and inhibit certain activi- managing for biodiversity—may be used as part ties that may affect the natural or agricultural of an effective network of regional conserva- resources of the land. The easement is often tion designations. Stewardship zones can occur purchased by a designated non-profit organiza- on public and private lands and include certain tion or local government agency usually for types of agricultural and grazing practices, eco- the difference between its market value and the logically sustainable forestry, and recreational value of its current use. The landowner receives use such as hunting and fishing. either a payment or tax benefit for entering into a conservation easement. The cost for the Land trusts, government agencies, landowners, easements can be expensive but is often much nonprofits and the conservation community may less than outright purchase of land (Casterline, utilize the Regional Conservation Guide to aid Fegraus et al. 2003). in protecting natural areas. Conception Coast Project will be reaching out with this document CHANGE IN MANAGEMENT OF PUBLIC PROPERTY to all of these parties through presentations and Public policy can be changed in numerous ways dialogue. Prioritizing areas for conservation to ensure that public health and ecologically will aid organizations in efficiently conserving significant areas are protected. Limiting extrac- the region’s most biologically important areas. tive uses, reducing or eliminating the use of pesticides and herbicides and designating nature RELEVANT PROGRAMS, ACTIVITIES AND preserves are some examples in which public METHODS FOR CONSERVATION policy can positively aid ecosystems. The use of science and new technologies can often assist PURCHASE OF PRIVATE PROPERTY Important areas for conservation are sometimes these efforts. The cost and effectiveness are purchased outright to ensure protection of natu- variable. ral resources. The financial cost is often high but the land will be preserved in perpetuity. The RESTORATION OF DEGRADED AREAS Gaviota Coast serves as a local example of such Restoration efforts can be effective in trans- efforts. Rancho Arroyo Hondo was identified as forming ecologically disturbed areas to func- one of the most ecologically significant water- tioning natural areas. In the Conception Coast sheds of the Gaviota Coast in CCP’s ecological region, many riparian restoration projects analysis for the Gaviota Coast Resource Study remove nonnative arrundo and other invasive

Conception Coast Regional Conservation Guide Implementing The Regional Conservation Guide Chapter 6

exotics to allow natural conditions to return to can be used to detail the above concepts and as the creek. The cost varies from expensive large- a reference for any road construction or modifi- scale projects to smaller volunteer projects. The cation in the region. effectiveness of projects is variable. TRANSFERABLE DEVELOPMENT RIGHTS (TDR) LAND EXCHANGE A Transfer of Development Rights program Land exchanges occur when a public or private transfers entitlements to develop one parcel to a agency designates land for resource protection different parcel of land. TDR programs are of- through legal commitment, or donates the parcel ten created by local zoning ordinances. The land to a land trust. Alternatively, land owned by a where the rights originate is called the “send- large public or private landowner, which is not ing” parcel, and the parcel of land to which the as desirable for conservation, is made available rights are transferred is called the “receiving” to exchange for private lands needed for conser- parcel. When the rights are transferred, the vation. In addition, landowners can receive tax sending parcel is restricted with a permanent benefits by donating land suitable for conserva- conservation easement. These programs are tion to a public or nonprofit entity. Performing based on the concept that property owners hold a land exchange secures development permits many different rights, including the right to and may be more cost effective than searching develop, and some or all of those rights can be for individual private landowners willing to sell transferred or sold (Casterline, Fegraus et al. mitigation land (Casterline, Fegraus et al. 2003). 2003). Further, a group of masters students at the Bren School at UCSB have evaluated the WILDLIFE CROSSINGS potential of a market-based transfer of develop- The Transportation Equity Act for the 21st ments program to preserve open space in Santa Century (TEA-21) authorizes over $200 bil- Barbara County (Carrol, Chen, et al 2005). This lion to improve the Nation’s transportation is an informative document and also considers infrastructure, and protect the environment. The the socio-political context of the region. Act allows new opportunities to improve water quality, restore wetlands, and rejuvenate urban FARM BILL areas. The U.S. Department of Transportation’s The Farm Security and Rural Investment Act of Federal Highway Administration has a program 2002 (Farm Bill) provides funding for a range called Critter Crossings, which addresses issues of emerging natural resource challenges faced of habitat loss and habitat fragmentation due by farmers. These issues include soil erosion, to public roads. The program works on vari- wetlands, wildlife habitat, and farmland protec- ous projects such as under and overpasses for tion. The 2002 Farm Bill places a strong empha- wildlife (Casterline, Fegraus et al. 2003). The sis on the conservation of working lands. Imple- County of Ventura has initiated work on wild- mented through the United States Department life crossings and is designing guidelines based of Agriculture (USDA) the Farm Bills provides on work by a group of graduate students at the landowners with various programs with their Bren School of UC Santa Barbara (Cavallaro, own incentives. These programs include: Sanden, et al 2005). This informative document

Conception Coast Regional Conservation Guide Chapter 6 Implementing The Regional Conservation Guide

· Conservation of Private Grazing Land FARMLAND SECURITY ZONE (CPGL) The California Division of Land Resource · Conservation Reserve Program (CRP) Protection handles the Farmland Security Zone · Agriculture Management Assistance program. This voluntary program provides ad- (AMA) ditional tax reduction by the basic Williamson · Conservation Corridor Program Act. The program requirements are similar to · Conservation Security Program (CSP) those for the Williamson Act, however eligibil- · Desert Terminal Lakes ity for these ‘Super Williamson Act’ requires · Environmental Quality Incentives Program landowners to join the program for at least 20 (EQIP) years. In exchange for longer participation the · Grasslands Reserve Program (GPR) landowner is given an additional 35% tax reduc- · Grassroots Source Water Protection Pro- tion above the initial Williamson Act assessed gram value, or Proposition 13 valuation, whichever is · Great Lakes Basin Program for Soil Ero- lower (Casterline, Fegraus et al. 2003). sion and Sediment Control · Ground and Surface Water Conservation PROPERTY TAX BENEFITS FOR WILDLILFE HABITAT · Partnerships and Cooperation AND NATIVE PASTURE CONSERVATION · Farmland Protection Program (FPP) California Revenue and Tax Code §421 indi- · Resource Conservation and Development cates that landowners with 150 acres or more Program (RC&D) can join into a wildlife habitat contract with · Small Watershed Rehabilitation various federal and state agencies. The con- · Wetlands Reserve Program (WRP) tract limits the land uses to habitat for native or · Wildlife Habitat Incentives Program migratory wildlife and native pasture for at least (WHIP) ten years. According to the tax code, “Land subject to a wildlife habitat contract is valued by THE LAND CONSERVATION ACT (LCA) using the average current per acre value based The Land Conservation Act or Williamson Act on recent sales including the sale of an undivid- is a California state regulation passed in 1965 in ed interest therein, of lands subject to a wildlife response to development driven agricultural and habitat contract within the same county (CA open space lands conversion. The act identiﬁes Revenue and Tax Code §421). The decrease in ‘agricultural preserves’ as areas in which lo- value of the land translates into lower property cal governments can enter into contracts with taxes (Casterline, Fegraus et al. 2003). landowners that only allows agricultural, recreational or open space. The program assesses the eligible lands based upon the land’s agricultural, open space or recreational values, and not on potential market value. The smaller assessed value allows landowners to lower their property taxes (Casterline, Fegraus et al. 2003).

Conception Coast Regional Conservation Guide Implementing The Regional Conservation Guide Chapter 6

Conception Coast Regional Conservation Guide References References Abbitt, R. J. F., J. M. Scott and D. S. Wilcove (2000). The geography of vulnerability: incorporating spe cies geography and human development patterns into conservation planning. Biological Conser vation 96: 169- 175.

Beier, P. (1995). Dispersal of Juvenile Cougars in Fragmented Habitat. Journal of Wildlife Management 59(2): 228-237.

Beier, P., D. Choate and R. H. Barrett (1995). “Movement Patterns of Mountain Lions During Different Behaviors.” Journal of Mammalogy 76(4): 1056-1070.

Bruntland, G. (ed.) (1987). “Our common future: The World Commission on Environment and Develop ment”, Oxford University Press, Oxford.

Burgess, R.L., and D.M. Sharpe, eds. (1981). “Forest Island Dynamics in Man-Dominated Land scapes.” Springer-Verlag, New York.

California Department of Conservation (2002). “Farmland Mapping and Monitoring Program,” Division of Land Resource Protection. California.

California Legislative Analyst’s Ofﬁce, website. (2002). http://www.lao.ca.gov/2002/cal_facts/econ. html. Retrieved June 6, 2004.

Carrol, T., C. Chen, J. Dunbar, R. Gore, D. Greve, and C. Kolstad (2005). Evaluating the Potential of a Market-Based Transfer of Developments Program to Preserve Open Space in Santa Barbara County. Bren School at University of California, Santa Barbara. http://www.bren.ucsb.edu/re search/documents/tdr_ﬁnal.pdf

Casterline, M., E., Fegraus, E., Fujioka, L. Hagan, C., Mangiardi, M., Riley, H., Tiwari (2003). Wildlife Corridor Design and Implementation in Southern Ventura County. Bren School at University of California, Santa Barbara. http://www.bren.ucsb.edu/research/2003Group_Projects/links/Final/ links_ﬁnal.pdf

Cavallaro, L, K. Sanden, J. Schellhase, M. Tanaka, F. Davis (2005). Designing Road Crossings for Safe Wildlife Passage: Ventura County Guidelines. Bren School at University of California, Santa Barbara. http://www.bren.ucsb.edu/research/documents/corridors_ﬁnal.pdf

Chaplin, S. J., R. A. Gerrard, H. M. Watson, L. L. Master and S. R. Flack (2000). The geography of imperilment: Targeting conservation toward critical biodiversity areas. Pages in Precious heri tage: The status of biodiversity in the United States.

Davis, F. W., C. J. Costello and D. M. Stoms. Efﬁcient conservation in a utility-maximization frame work. Submitted to Ecology and Society.

Conception Coast Regional Conservation Guide References

Davis, F. W., D. M. Stoms, et al. (2003). A framework for setting land conservation priorities using multi-criteria scoring and an optimal fund allocation strategy. Santa Barbara, CA, Univer sity of California, Santa Barbara; National Center for Ecological Analysis and Synthesis; Report to The Resources Agency of California.

Department of Finance (2004). Population Projections by Race/Ethnicity, Gender and Age for California and Its Counties 2000-2050. Sacramento, California, State of California. http://www.dof.ca.gov/ HTML/DEMOGRAP/DRU_Publications/Projections/P3/P3.htm

Dickson, B. (2001). Home range and habitat selection by adult cougars in the Santa Ana Mountain range of Southern California, Northern Arizona University.

Dobson, A. P., J. P. Rodriguez, W. M. Roberts and D. S. Wilcove (1997). Geographic distribution of en dangered species in the United States. Science 275: 550-553.

EDAW, Inc. (2002). Gaviota Coast Resource Study. Prepared for County of Santa Barbara, Planning and Development Department. Santa Barbara, CA.

Fulton, W., J. Wilson, C. Ryan, E. Kancler and A. Harrison (2003). Recent Growth Trends And Future Growth Policy Choices For Ventura County. Los Angeles, CA, Southern California Studies Cen ter, University of Southern California and Solimar Research Group: 57.http://www.solimar.org/ pdfs/Final_VCOG_Paper.pdf

Landis, J., C. Cogan, P. Monzon and M. Reilly (1998). Development and Pilot Application of the Cali fornia Urban and Biodiversity Analysis (CURBA) Model. Berkeley, CA, Institute of Urban & Regional Development: 88

Lehman, Paul (1994). The Birds of Santa Barbara County, California. Museum of Systematics and Ecol- ogy, Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara. Santa Barbara, CA

Noss, R.F (1991). Landscape linkages and biodiversity. W.E. Hudson. Washington D.C. pp. 27-39.

Miles, S. and C. Goudey (1998). Ecological Subsections of California: Section and Subsection Descrip tions, USDA Forest Service, Paciﬁc Southwest Region and Natural Resources Conservation Service, & Bureau of Land Management. 2005. http://www.fs.fed.us/r5/projects/ecoregions/title_ page.htm

Noss, R.F., and L.D. Harris (1986). Nodes, networks, and MUMs: Preserving diversity at all scales. En vironmental Management 10: 299-309.

Conception Coast Regional Conservation Guide References

Noss, R.F., and M.E. Soule (1999). Rewilding and biodiversity: complementary goals for continental conservation. Wild Earth 8(3):18-28.

SBRECP (2003). South Coast Regional Impacts of Growth Study. Santa Barbara Region Economic Community Project. Santa Barbara CA. October.

Soule, M. E. and J. Terborgh (1999). Continental conservation : scientiﬁc foundations of regional re serve networks. Washington, D.C., Island Press.

Theobald, D. M. (2001). A brief description of the Western Futures development maps, Natural Re source Ecology Laboratory Colorado State University.http://www.centerwest.org/futures/devel opment/white_paper_dev.html

Union of Concerned Scientists, website (2003). http://www.ucsusa.org/global_environment/global_ warming/index.cfm. Retrieved June 6, 2004.

USDA Forest Service (2001). Draft Environmental Impact Statement: Oil and Gas Leasing, Los Padres National Forest. Goleta, CA, United States Department of Agriculture, Forest Service, Los Pa dres National Forest

Conception Coast Regional Conservation Guide References

Conception Coast Regional Conservation Guide Conception Coast Regional Conservation Guide Appendices

Appendices

Black Bear Cub - Ursus americanus

Conception Coast Regional Conservation Guide Appendix A Appendix A - Detailed Methodology

INTRODUCTION gated half way through the analysis to create the 1. BACKGROUND value of the candidate site. 1.1. CONTEXT This technical appendix is written to comple- The current draft of the RCG is referred to as ment the Regional Conservation Guide (RCG). the first “iteration” or RCG version 1.0. An This provides more detail on the analytical iteration is a computational procedure in which methodology, which was intentionally kept brief a suite of operations is performed again with and simple in the guide itself. In turn, there is a small improvements in order to approximate more detailed methodological write-up that this the desired result more closely. There are many document refers to (Davis, Stoms et al. 2003) improvements that can be made for version 1.1 which has been refined and submitted for publi- or 2.0. If you as a reader have any suggestions, cation in Ecology and Society (Davis, Costello please submit them as we are compiling a list et al. Submitted). of potential improvements. However, another iteration will only be performed if there is 1.2. KEY TERMINOLOGY enough interest from community organizations Each of the six ecological objectives are repre- and individuals, and if the resources for such an sented as Geographic Information System (GIS) endeavor are available. “layers” that are overlaid on top of each other in a “multi-criteria analysis.” As a metaphori- [Occasionally minor technical notes will be cal description of a layer, imagine a piece of provided in brackets. These notes are not neces- clear plastic Mylar with a square grid drawn on sary for understanding the methodology, but are it. Each of those squares can have a color and useful in exactly replicating the methodology.] number associated with it that represents the importance of that square with respect to the 1.3.ADVISORY GROUPS particular ecological objective, say listed spe- Advisory groups were used to guide develop- cies hotspots. Then all of the layers are overlaid ment of the RCG. Please see Chapter 1 for a with “map algebra” and at a particular location description of these groups. on the landscape, the sum of the corresponding square of all the layers can be determined. PART 1: MAP “BIODIVERSITY VALUE” Similarly any other algebraic manipulation can For an introduction to this objective and an be performed, such as multiplication. overview of the methodology, please see Chap- ter 4 of the RCG. In the above metaphor, the square will be termed the “candidate site” for the rest of the document. Both Ecological and Land-Use advisors saw the Candidate sites are 1.5 km by 1.5 km. Further, preliminary results of the model and requested there are often many smaller squares embed- that the results are also shown without the ef- ded within one of these larger squares. These fects of “threat” (predicted land use change). smaller squares are called “cells” and are 100 This would show the raw biodiversity value m by 100 m unless otherwise specified. Most of the land, irrespective of human politics. analyses are started on the cells, and then aggre- “Threat” is embedded deep within the Davis,

Conception Coast Regional Conservation Guide Appendix A

Stoms et al. (2003) analysis. The request of each layer is detailed below, and the ﬁnal classes the advisors was able to be met by making the and values are summarized on Table A1: Human model assume that all lands had an equal likeli- Impact Categories and Values. hood of being completely degraded by the year 2050. The result is the map of “Biodiversity 2.1.1. MAP AND CLASSIFY URBAN, SUBURBAN, RU- Value.” The objectives for this analysis are B1, RAL AND OTHER DEVELOPMENT DENSITIES B2, B4, and B6, and for the conservation value This layer was created by combining two data analysis the objectives are C1, C2, C4,C5, and sources: the CA Department of Conserva- C6. For an overview diagram of this analysis, tion “Development Footprint” which is census see Figure 4 of the RCG, on the following page. based, and the Farmland Mapping and Monitor- [Note: Davis, Stoms, et al. (2003) refer to the ing Program (FMMP) data which are aerial pho- objectives as M1, M2, etc.] tography and map based (See Table A2: Source Data for the Regional Conservation Guide for 2. HUMAN IMPACT INDEX 2000 more information). High density urban class This is the layer indicating the human land-use was determined by the FMMP data as land oc- impact on the landscape during the year 2000. cupied by structures with a building density of To understand the context of this layer in the at least 1 unit to 1.5 acres, or approximately 6 analysis, please review at least the introduction structures to a 10-acre parcel. All other classes of Chapter 4 of the RCG. [Note: Davis, Stoms were determined by the development footprint et al (2003) refer to this layer as “Ecological layer, see Table A1 for class categories and Conditions Index,” but after presenting this con- values. The density class threshold values were cept to local advisors, confusion ensued, and the used to correlate with the density classes used in name has been changed to the “Human Impact the urban outgrowth model results of the Human Index” and the values reversed.] Impact Index 2050 analysis, described later.

2.1. MAP AND CLASSIFY DIFFERENT HUMAN 2.1.2. MAP AND CLASSIFY DIFFERENT TYPES OF IMPACT LAYERS INDUSTRIAL LANDS Six different layers of data were created, each For this iteration of the RCG, industrial lands with a variety of classes. These layers were as are deﬁned as lands used for oil development follows: 1) development densities, 2) industrial and processing. There are two data sources for lands, 3) agricultural lands, 4) grazing lands, 5) this layer: the US Forest Service draft EIS for roads, and 6) reserves and known conservation the proposed oil development expansion in the easements. All of the classes of these six layers national forest(USDA_Forest_Service 2001), were then combined onto one spreadsheet, and and the Department of Conservation Well Loca- were assigned relative values at an ecological tions Database (See Table A2). The area of cur- advisor workshop and subsequent e-mail poll- rently utilized oil leases was determined using ing. The six layers were then overlaid, and the the USFS data. The well locations database had highest potential human impact value for every 130 speciﬁc types of wells in our region which cell was mapped. The cell size of each layer is were then re-classed into 6 subclasses, which 30 m by 30 m. Methodology of the creation of were then re-classed into three classes for analy-

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Figure 4: Diagram of the Biodiversity Value Analysis

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Table A1: Human Impact Categories and Values

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Table A2:Source Data for the Regional Conservation Guide

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Table A2 continued: Source Data for the Regional Conservation Guide

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sis, see Table A2. minor road coverage cells were determined by the distance from the road, as well as by nearby 2.1.3. MAP AND CLASSIFY AGRICULTURE LANDS housing density. The assumption is that minor The data source for this layer is the Farmlands roads near urban or suburban areas will have a Mapping and Monitoring Program. See Tables higher traffic volume, and thus a higher impact, 1 and 2 for data source description, and the than those that are in rural areas (Davis, Stoms resulting data layer classes and values. et al. 2003). The data were then resampled to 30 m cells and clipped to the Conception Coast 2.1.4. MAP AND CLASSIFY GRAZING LANDS region. There were four data sources for this layer that were grouped into two different classes: Grazing 2.1.6. MAP AND CLASSIFY RESERVES allotments and visible grazing (See Tables 1 and All classes of reserves designated by the man- 2). “Visible grazing” is derived from analysis of agement landscape data source were used satellite imagery, and identifies actual locations (sparse and rural, public and private reserves). within and outside of allotments that grazing is These are lands permanently protected from occurring. However, there are some areas, es- conversion of natural land cover and having pecially those in oak woodlands, that are grazed a mandated management plan in operation to but not visible from the air. It is assumed that maintain a primarily natural state, but which most of these areas will show up in the grazing may receive management practices that degrade allotments category. Further, C-CAP (the vis- the quality of existing natural communities ible grazing) did not include San Luis Obispo at (equivalent to GAP Management Status classes the time of analysis. 1 and 2). Further, we had two data sources for conservation easements, which were also 2.1.5. MAP AND CLASSIFY ROADS classed as reserves. See Tables 1 and 2 for data The roads data used were the same as those source description, and the resulting data layer derived by Davis, Stoms et al. (2003) white classes and values. paper. “To model road impacts we used 2000 TIGER data developed by the U.S. Census 2.2. MERGE LAYERS INTO HUMAN IMPACTS AT THE Bureau. TIGER road classes 1,2,3, and 6 were YEAR 2000 LAYER considered major roads and road class 4 was The above six layers were merged and the high- treated as minor roads. Major and minor roads est potential human impact value for every cell were extracted as two separate GIS coverages was mapped. For example, if a particular 30 m and a 100 m grid of distance to road was created by 30 m area on the landscape is 200 m from a for each coverage using 500m as the maximum minor road, is in a rural 60 acre parcel area, and distance for major roads and 300m for minor has some visible grazing, it will have human roads.” The human impact values of the major impact values for all of these layers. In this road coverage cells were determined by the in- case, the visible grazing has the highest human verse distance from the road, with cells adjacent impact score of .46, so in the final composite to the road having a higher impact than those layer, this cell will have a value of .46. 500 m away. The human impact values of the

Conception Coast Regional Conservation Guide Appendix A

2.3. VISUALIZE RESULTS 4. OBJECTIVE B1: ESTIMATE LISTED The layer was mapped such that every human SPECIES HOTSPOTS BIODIVERSITY VALUE impact type had a unique color. Because there 4.1. DETERMINE THE LIST OF SPECIES THAT WILL BE are so many categories, a continuous color ramp USED could not be used. Road impacts have variable Three lists of species that are found in our re- values, so would require too many colors to be gion were created and presented at an ecological mapped. They were selected out of the layer advisor workshop: and added as their own layer, and ramped as a List 1: “Listed Species” Includes Federal various shades of black grey and white. See and State-- Endangered, Threatened, Pro- Figure 6: Human Impact Types within the Con- posed Endangered, Proposed Threatened, ception Coast Region. To see the relative im- Candidate, and CA Rare species. pact on the landscape, see Figure 7: Estimated Degree of Human Impact within the Conception List 2: “Global Rank, Not Listed” Species Coast Region. or sub-species that are globally rare (G1, G2, T1, or T2) according to the Natural 3. CONDITION WEIGHTED AREA Heritage listing system, but that are not One of the fundamental assumptions of this included in Group 1. model is that a habitat in a pristine area has more biodiversity value than the same type List 3: “Special Concern Only” Species that of habitat in a degraded area. As mentioned are State or Federal Species of Concern, or in chapter 4, the Human Impact 2000 layer is California Native Plant Society Rare; and used to address this issue. This is done using a that are not included in Group 1 or 2. concept called Condition Weighted Area (CWA) (Davis, Stoms et al. 2003). The CWA, in acres, Species that are found only on the Channel of an individual 100 m cell is simply the acre- Islands, or that there is no digital data about, age of the cell (~0.222 acres ) multiplied by the were not included in the draft lists. The lists ecological condition of the cell. The ecological were then shown to the ecological advisors, condition is simply 1 minus the human impact and some other regionally important species value (Table A1). Thus, a cell of pristine habitat were added. It was decided to include all three will have a CWA of 0.222 [i.e. 0.222 X (1-0)] lists in the analysis. Further, it was determined condition weighted acres; an acre of agricul- to not weigh occurrences of species from one tural land will have a CWA of 0.0666 condition list higher than occurrences of species from weighted acres [i.e. (1-0.7) X 0.222]; and an another list. This was for several reasons, the acre of urban land will have a CWA of 0.002 most prominent being that there are significantly acres. The CWA layer is combined later with more digital data for species from list 1, and that the ecological data of the various objectives to political listing does not necessarily correlate yield the partial and final estimates of biodiver- with ecological importance or rarity. The final sity and conservation value. “target” list of species used for RCG Iteration 1.0 is provided in Table A3: Species used for the Listed Species Hotspots Analysis of the RCG.

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Table A3: Species Used for the Listed Species Hotspots Analysis of the RCG - key located on page 117

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Table A3 continued: Species Used for the Listed Species Hotspots Analysis of the RCG

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Table A3 continued: Species Used for the Listed Species Hotspots Analysis of the RCG

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Table A3 continued: Species Used for the Listed Species Hotspots Analysis of the RCG

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It should be noted that the Ventura County Plan- the herpetile database, and John Gallo cross- ning department has spent a year determining walked the other three databases. For unclear a similar list with much input from ecological occurrences that did not provide enough clues advisors. That list, or slight additions if need be, as to the proper subspecies, the original data is recommended if iteration 2.0 is performed. were left as is and not crosswalked. Often this meant the data would not be used in the analysis 4.2. GATHER AND PROCESS SPECIES DATA because they denominated the subspecies that was not on the list. 4.2.1. PROCESS THE CALIFORNIA NATURAL DIVER- SITY DATABASE (CNDDB) 4.2.3. CREATE AND PROCESS THE LOCAL EXPERT There were 1,128 occurrences of a target list LISTED SPECIES DATABASE species in the Conception Coast Region (See At a local expert workshop, our region was Table A2 for more information about the CND- mapped out in 60 square feet (mostly at DB). These occurrences were then assigned to 1:50,000) and the known locations of the target the RCG candidate sites. species were mapped (2,750 records from the local databases, as well as 1,128 records from 4.2.2. PROCESS THE LOCAL DATABASES CNDDB). The experts then “filled in the gaps” Four pre-existing local digital databases were by mapping known species occurrences not al- collected and processed. They were the Bird ready mapped. 125 new records were mapped. Database developed by Conception Coast Proj- ect (CCP) and the Museum of Systematics and 4.2.4. MAP ALL DATASETS Ecology (MSE) at UCSB, the Vertebrates Data- See Figure 8 of Chapter 4 of the RCG: Listed base developed by CCP, the Vertebrates Data- Species Locations within the Conception Coast base II developed by the Los Padres office of the Region. U.S. Forest Service, and the Herpetile Database developed by the MSE (Table A2). Together, 4.3. DETERMINE THE B1 (LISTED SPECIES HOT- these databases combined for 2,750 occurrences SPOTS) VALUE FOR EACH CANDIDATE SITE of a target list species in the Conception Coast The site’s hotspot value is a function of the fol- Region. Each dataset had a different temporal lowing: range, and it was assumed that all observa- · number of species of special concern at the tions are still valid. All four databases did not site, exactly “crosswalk” (merge) with the CNDDB · the spatial accuracy of the observations of due to inconsistencies with common and sci- each species at the site, entific names. For instance, an observation of · the degree of endemism (rarity) of each a savannah sparrow in a coastal salt marsh in species based on the total area of known oc- the database is likely the endangered Belding’s currence in the region, savannah sparrow subspecies, Passerculus · the condition weighted area of the site (i.e. sandwichensis beldingi, but was incompletely the amount of human impact on the site), entered as the common upland species. John · and the condition weighted area of all LaBonte of the MSE assisted in crosswalking other sites where the species occurs (Davis, Stoms et al. 2003).

Conception Coast Regional Conservation Guide Appendix A

Some of the speciﬁcs are as follows, and for Due to the complexity of the analysis, the units more information and the mathematical rep- of the ﬁnal answer for B1 do not make intuitive resentation, see Davis, Stoms et al. (2003). If sense. What is important is the relative scores a species is relatively common throughout among sites. These will be normalized between the region, then the relative importance of an ecological objectives in the next step. individual observation is less than for a species that is more rare. This relative rarity of a spe- An alternative methodology that accounts for cies is higher if most of the occurrences are in species density was explored, evaluated, and areas of high human impact, than if they were in discarded. In the discarded approach, the sum areas with lower human impact. Once the rela- of all the quality of occurrences of a species tive rarity of the species is determined, then the for each site was used instead of the best oc- importance of each observation can be deter- currence. However, some of the datasets were mined. In this case, if an individual observation much more careful to not include duplicate of a species is in a site with high human impact, sightings (sightings of the same individual or the value of that observation to the site will be territory at different times) then others. Due to lower than the same species in a site with low this discrepancy, only the best observation of a human impact. species within a site was the value used.

A challenge arose due to the convention of spe- 4.4. NORMALIZE THE LAYER cies databases known as “accuracy class.” If the Each of the following ecological objectives exact location of the observation is known, it will also develop a value for each site, and then has a higher accuracy class, and is mapped with be synthesized at a later stage. However, they a very tight circle. If the location of the ob- will be in different units. Further, if the lay- servation is less exact, it has a lower accuracy, ers were added together as is, then there would and is mapped with a large circle, up to 8 km be a strong bias towards the layers that do not in radius. The larger circle does NOT repre- have a very large geographic distribution. This sent a larger population of the species, rather it is because for these layers, each site that has a indicates the species if found somewhere in the value has a large proportion of the value of the circle. To account for this in the analysis, the entire layer, and thus a very large value com- observation was multiplied by a weight that was pared to the more ubiquitous layers like Habitat inversely proportional to the size of the circle. Representation. It was suggested by John Gallo, The resulting weighted value could then be used John Storrer, and Ralph Philbrick, and approved in determining the B1 value of each candidate by the CCP Board that the relative impact of site. Thus, a low accuracy observation of a each objective at each site should be determined species will have a small value for 26 candidate by the weights developed at an advisor work- sites, that when added up, will equal the value shop only, or as Ralph put it, true to the classical for high accuracy observation in one site. This “McHargian” approach to combining GIS layers way a low accuracy observation does not inﬂu- (McHarg 1971). ence the model up to 26 times more than a high accuracy observation of the same species. In summary, each objective needed to be nor-

Conception Coast Regional Conservation Guide Appendix A

malized such that the following criteria were objectives in the RCG. The simple take home met: message is that the higher the score, the higher 1) The units across all criteria need to be the importance. The B1 normalized value of a comparable for examination of the relative site is the B1 Listed Species Hotspots Biodiver- importance of a specific criteria for a spe- sity Value of the site. cific location, 2) When the objectives are added together 4.5. VISUALIZE RESULTS using map algebra, the synthesized biodiver- Advisors recommended that the final output sity value of a site is based on the relative did not use the blocky, 1.5 km pixels, but rather values of the objectives for that site, and was a smoother graphical representation. It their relative weights, was felt that such a result would communicate 3) Sites on the boundary of the study area the contiguity of ecological processes better as are not the full size, but if they have a lot of well as the inherent uncertainty of the results. value for that objective considering their The idea is to have no boundaries on the final small size, they should get a high score. maps. To do this, two analyses were performed and compared. One was chosen, and is as fol- Thus, to normalize the site values for objective lows. The sites layer was converted to a 100 m B1 the following variables were defined. The grid, and a neighborhood mean was performed, site value will be termed B1Value, and the sum using a radius of 10 cells. (In this analysis, all of all the site values is SumB1. The acreage of the cells in a 10 cell radius around a cell are the site is termed Site Acres, and the total num- averaged, and this average value is the value ber of acres of all the sites that have a non zero assigned to the cell. This is performed for every value for the objective are termed SumAcresB1. cell on the landscape.) The resulting output was The value of the site was normalized according a contoured landscape mapped using a “quan- to the following equation. tile” classification scheme and 6 classes. In this scheme, the range of values of each class is chosen mathematically such that the number of sites in each class is equal. Thus, some classes have a wide range of values, and others a small range. The site will get a normalization value of 1 if For a map of the final results, see Figure 9 of the value of the site relative to the total value Chapter 4 of the RCG: Listed Species Hotspots of all the non-zero sites is equal to the area of Biodiversity Value within the Conception Coast the site relative to the total area of all the non- Region (B1). zero sites. One way to interpret this normalized value score is that any site will have a non-zero 5. OBJECTIVE B2: ESTIMATE HABITAT value if it has any known listed species observa- REPRESENTATION BIODIVERSITY VALUE tions, and of all such sites, the ones with a value For an introduction to this objective and an of greater than 1 will have an above average overview of the methodology, please see Chap- listed species hotspot value. This normalized ter 4 of the RCG. value scale will be the same for all of the other

Conception Coast Regional Conservation Guide Appendix A

5.1. MAP THE HABITATS OF THE REGION Several data sources were evaluated, and the 5.2.2. ECOREGIONAL CONTEXT one chosen was the Multi-Source Land Cover Habitats that are more common in our region, Data (MLCD) (See Table A2 for more infor- yet rare elsewhere in the contextual region mation). These data were clipped to the CCP (the central western and south western Jepson Region. Of the 77 land cover types found ecoregions of California), deserve a higher level statewide, 32 habitat types are found in our of protection then pure rarity would indicate. region, and are mapped. See Figure 3 of the The percentage of our region a particular habitat RCG: Habitat Types and Distribution within the covered was divided by the percentage of the Conception Coast Region. contextual region the habitat covered. Thus a habitat relatively common in our region, but not 5.2. DETERMINE THE RELATIVE WEIGHT OF EACH found that much outside of our region would get HABITAT TYPE a score greater than 1. Again, the list of scores The relative weight of each habitat type is a was then standardized by dividing by the maxi- function of the rarity of the habitat, the Ecore- mum score, thus the habitat with the highest gional context, the estimate of historical habitat ecoregional ratio gets a score of 1 (Table A4). loss, and the inherent habitat value. Inherent habitat value was determined via local expert One minor problem arose because the CCP knowledge, and the other values were deter- region (watershed deﬁned) includes a very small mined via GIS queries. These factors are further sliver of the central valley ecoregion. Alkali described below. Desert Scrub is thus able to have more acreage in the CCP region than in the contextual 5.2.1. RARITY INDEX region. To correct for this apparent paradox, the The total number of acres of all habitats was ratio was set at 4.55 instead of 21.9. 4.55 is the divided by the number of habitats to get the answer that would occur if all of a habitat was number of acres of each habitat if they were in the CCP region, within the contextual region. all equally distributed. This number was then The precise way to correct for this minor error divided by the actual acreage of each habitat would be to redraw the contextual region to in- to get the raw rarity score. Thus, a raw score clude the sliver of the central valley ecoregion. of greater than 1 indicates increasing degree of 5.2.3. Estimate of Historical Habitat Loss rarity. The list of scores was then standardized If a certain habitat type has lost a lot of it’s his- by dividing by the maximum score, thus the rar- torical cover then it arguably deserves a higher est habitat gets a score of 1 and the most com- level of protection than pure rarity would indi- mon gets a score very close to 0 (See Table A4: cate. The primary data used for this were from Input Values and Output Habitat Weights for the a map developed by Kuchler (1977), which in- Regional Conservation Guide). [Note that the dicates the potential cover of each habitat. The total acreage of the habitats does not equal the assumption is that potential habitat coverage is total acreage of the region because urban and similar to the historical habitat coverage. The agricultural land cover types were not included 14 Kuchler categories were crosswalked with in this analysis.] the 32 MLCD categories. The total acreage

Conception Coast Regional Conservation Guide Appendix A Table A4: Input Values and Output Habitat Weights for the Regional Conservation Guide Weights and Output Habitat Values A4: Input Table

Conception Coast Regional Conservation Guide Appendix A

of each Kuchler category was determined, and habitat weights. Dr. Philbrick and John Gallo divided by the sum of the MLCD categories that came to a consensus that rarity and inherent crosswalked with the Kuchler category. Four of habitat value were both much more important the MLCD categories did not crosswalk at all, than ecoregional context and historical habitat so the ratios between potential and current were loss. Thus, these two important indices were estimated as follows: Barren = 1, Desert Wash given a weight of 3, and the other two were giv- = 1, Eucalyptus = 0.01 (Eucalyptus is an exotic en a weight of 1. The weights were multiplied species), and Freshwater Emergent Wetland = by the index, and the resulting products were 20 (California has lost about 95% of its coastal multiplied. (Multiplication was used so that wetlands) (Table A4). ubiquitous habitats would get a proportionally lower weight. If a sum were used instead, the 5.2.4. ESTIMATE OF INHERENT HABITAT VALUE common habitat types such as chaparral would It was determined at an Ecological Advisor not be down weighted for prevalence, and end workshop that there is an inherent habitat value up with higher weights then less common but to various habitats that is not reflected by the important habitats such as blue oak woodland.) above ratios. This was loosely defined as the The final product was then standardized by relative importance to biodiversity of a particu- dividing by the maximum score, thus the highest lar habitat type. Namely, it is an estimate of weight gets a 1 and the lowest is close to 0. how much life, i.e. ecological niches, it sustains. Each advisor was asked to shed their taxonomic Because three of the four indices have an expo- biases and to rank each of the 32 habitats as nential type distribution, with most of the values high, medium, or low inherent habitat value. clustered around 0, the weighted product had All the votes were then compiled and displayed an exponential type distribution with a max of and a consensus was attained. In this consensus, 1, a mean of 0.05, and a standard deviation of two new categories were allowed: medium- 0.17. In essence this was giving a huge bias to high or medium low. Subsequently, this was the linear index of inherent habitat value which sent to other advisors that could not attend the had a mean of 0.59. To compensate for this and workshop. Three more responses were tallied to have a more linear set of weights to be used that had very similar findings. Dr. Philbrick in the next step of the model, (but not to clump and John Gallo then examined all of the votes, the values too close to 1), the above weighted keeping in mind what participants had said at product was then re-scaled by taking the fifth the workshop and the phone, and came to a final root of each result. (Taking a root of an expo- value. The five categories were then classed nential distribution rescales the distribution to numerically as 0.01, 0.25, 0.5, 0.75, and 1 (0 be more linear). The fifth root was used because cannot be used because a weighted product is it appeared balance the conflicting issues best used later)(Table A4). (exponential versus inverse exponential curves), and also because of the eight weighted units, 5.2.5. COMBINE THE FOUR INDICES five are exponential. This final result was the It was determined that the above four indices weight used for the B2 analysis (Table A4). should not be treated equally in determining the

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5.3. Determine the B2 (Habitat Representation) approach outlined above were actually used. Value for each Candidate Site Thus, we will wait to the later section to ex- Similar to B1, the habitat representation value of plain the marginal value approach itself. Also, a site is a function of the following: because that approach was used, we could not · the habitat types at the site and their cor- combine the different components at the habitat responding weights, level as described above, but instead had to do · and the condition weighted area (human it at the site level. A Condition Weighted Area impact) of the site. value for the site was attained, and a similar habitat weighted area was also attained. But In essence, the methodology is as follows. The the original results of a raw average had an Habitat Representation Biodiversity Value of extremely high correlation with the human a particular habitat in a site is the Condition impact 2000 map. This is because the sum of Weighted Area of that habitat in the site multi- the distribution of values across the landscape of plied by the habitat weight. The Habitat Rep- Condition Weighted Area is 3.005 times higher resentation Biodiversity Value for a site is then than the sum of the distribution of values of simply the sum of the Habitat Representation habitat weighted area. To compensate for this Biodiversity Values of all the habitats in that and to make the two factors equal impact on the site. final results, habitat weighted area was given a weight of 3.005, before being averaged with The final units are such that if an acre of land human impact value.] had the habitat with a weight of 1, and no human impact, then that acre would have a score 5.4. VISUALIZE RESULTS of 1. Therefore, for a full 1.5 km square (555 The normalized site values were then smoothed acre) site, the best possible score would be 555. as per the methodology described for B1. For a If the human impact value is greater than 0, or a map of results, see Figure 10 of Chapter 4 of the habitat is present with a weight less than 1, then RCG: Habitat Representation Biodiversity Value the site score would be less than 555. What is within the Conception Coast Region (B2). most important, however is the relative scores among sites. To get these relative scores in a 6. OBJECTIVE B4: ESTIMATE WILD LANDS scale that is most useful the site values were BIODIVERSITY VALUE normalized, as per the procedure defined in ob- For an introduction to this objective and an jective B1, to create the Habitat Representation overview of the methodology, please see Chap- Biodiversity Value. ter 4 of the RCG. [Technical Note: The actual process for de- 6.1. IDENTIFY WILD LANDS termining the above was more complicated, To determine the locations of wild lands, the as we used the “marginal value” equations of Human Impact Layer was “smoothed” using a Davis, Stoms et al. (2003) that are overviewed neighborhood analysis of 500 meter search rain Objective C2. Because threat is not an issue, dius. (All the cells within 500 m of a cell were the results are nearly identical to if the simple averaged, and this average value becomes the

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new value of the cell). This smoothed surface wild lands. Thus, contiguous areas that have was then queried to identify areas that have a very low human impact and meet the above contiguous area with a human impact value threshold parameters, but with habitat that is not greater than 0.8 and that are greater than 30 suitable habitat for mountain lions, are still iden- square kilometers. tified as Wild Lands. See Figure 11 of Chapter 4 of the RCG: Locations of Large Wild Lands The process for choosing the above size and hu- within the Conception Coast Region. man impact thresholds was as follows. Because it is a large carnivore, and because it is used in 6.2. ASSIGN WILD LANDS VALUE TO EACH SITE the connectivity (B6) analysis, the mountain The Wild Lands value for a site is simply the lion was chosen as a focal species for param- condition weighted area of the cells in that site eterizing the size of wild lands. In southern that are part of a Wild Land polygon. A full California, the average home range for females sized site in the lowest human impact land that was about 93 square km, while in central is completely within a Wild Land had a value California it was about 60 square km (Dickson of 555 (the number of acres per full sized site). 2001). However, when the mean of these values [Note that because threat is not considered was used, the output showed mountain lions in this run there is no extra importance given territories only in the central wilderness area to small wild lands versus large wild lands of the region, contrary to local knowledge and as originally intended by Davis, Stoms, et al. data. (A database of known sightings has been (2003).] The Wild Lands site values were then initiated by Conception Coast Project, see www. normalized as per the procedure describe in conceptioncoast.org for more information and to objective B1. add observations). 6.3. VISUALIZE RESULTS The discrepancy between the initial model- The site values were then smoothed as per the ing approach and the observations database methodology described for B1. See Figure 12 is because lions do not need all of their home of Chapter 4 of the RCG: Wild Lands Biodiver- range to be contiguous high quality habitat, just sity Value within the Conception Coast Region a portion of it. Thus, a data driven methodology (B4). for setting the parameters was employed. It is known that there is a breeding territory on South 7. OBJECTIVE B6: ESTIMATE LANDSCAPE Vandenberg Air Force Base (VAFB) and in the CONNECTIVITY BIODIVERSITY VALUE Santa Monica Mountains. Both of these areas For an introduction to this objective and an had slightly more than 30 square km of contigu- overview of the “gated least cost path methodol- ous, smoothed, 0.8 human impact value. Thus, ogy”, please see Chapter 4 of the RCG. these were chosen as the threshold parameters. There is a much more rigorous approach to de- 7.1. METHODOLOGICAL ASSUMPTIONS fining core patches that could be employed at a · It is assumed that it is important to main- later date. It should also be noted that mountain tain the connectivity between all pairs of lion habitat suitability was not used in defining wild lands, not just the ones that have high

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quality linkages already in place. This is based on the principle that all populations of 7.3. CREATE MOVEMENT “COST” SURFACE mountain lion need to be connected to other In this analysis, movement cost is a function of populations. However, it is also important mountain lion habitat suitability, human impact to give a higher value to these higher quality value in general, roadedness speciﬁcally, and a linkages as a matter of pragmatism. constant.

· If two linkages are equal in all respects 7.3.1. MOUNTAIN LION HABITAT SUITABILITY except for the distance they span between The California Wildlife Habitat Relationships core wild lands, then they will be valued as (CWHR) model was used in conjunction with equals (i.e. standardize by distance). the Multi-Source Land Cover Data (See Table A2). This model predicts the suitability of a · To account for the “stepping stone effect,” habitat for mountain lions, based on expert it is assumed that all cells along a linkage knowledge and literature review. Of the three are not considered equal value. The con- categories of habitat suitability (cover, feeding, nectivity value of a cell is a function of the and reproduction), cover was the factor used habitat suitability and human impact value because the model is looking at mountain lion of that cell, as well as the quality of the dispersal. See Figure 13: Habitat Quality for overall linkage that the cell lies in. Mountain Lion Dispersal.

· “Landscape Connectivity” addresses 7.3.2. HUMAN IMPACT VALUE coarse scale connectivity for large, wide The human impact value layer developed earlier ranging species; not the equally important was used. fine scale connectivity for smaller species. 7.3.3. A SPECIFIC CONSIDERATION OF 7.2. IDENTIFY CORE AND “DESTINATION” ZONES ROADEDNESS The first step in the connectivity analysis is to The roadedness layer that went into the human identify the pieces of land that will be connect- impact layer was used on its own as well. This ed. To be consistent with the rest of the RCG, is because roads are the primary source of death these lands will be the Wild Lands identified in to mountain lions in southern California (Beier objective B4. Due to the time consuming nature 1995; Beier, Choate et al. 1995). of analyzing pairs of wild lands, the large wild lands in the center of the region that are nearly 7.3.4. RELATIVE DISTANCE OF A PARTICULAR touching were combined together into one wild ROUTE land. All the other wild lands are considered After initial runs of the model it was realized “destination” wild lands. These are often called that even ideal habitat has a small cost for cores and sinks, but because a metapopulation movement. Otherwise lions would be able to analysis has not been performed, it is not known move an infinite amount of distance through if the smaller, peripheral zones are indeed clas- ideal habitat. Thus, a mathematical constant sic sinks, thus the term “destination” is used. was added to the movement cost equation. This

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constant simulates the energetic cost of move- subtracted. Next the layer was divided by the ment, and that dispersal through perfect habitat Euclidian distance between the two wild lands also has a cost because it is likely through a so that the analysis did not bias against linkages hostile male’s territory. Several values were that had to span a large distance. evaluated (0.03, 0.05, 0.07, 0.1,and 0.15), and the one (0.05) that balanced the benefits and At this point the layer had a linkage value for detriments of using such a factor was used. every cell on the landscape, even the cells in the middle of cities. In order to highlight the The other three factors were combined with feasible wildlife linkages, a new layer was cre- even weight for a contiguous 90 m cell resolu- ated that selected just the good (low) values. tion “movement cost” layer: After evaluating several threshold values and comparing them to knowledge of the landscape, all values 1.04 times the minimum value were selected. (In this analysis, lower cost is a better 7.4. ENHANCE MOVEMENT COST LAYER FOR linkage). This selected about a quarter to a half ANALYSIS of the landscape, depending on the pair of wild The conventional gated least cost path analy- lands analyzed. This layer for each wild land sis has a flaw that allows cells not in a linkage, pair was called a paired raw linkage layer. All but close to a core zone to get a high score. To of the paired raw linkage layers were combined, account for this flaw, the movement cost sur- and where values from two linkages overlapped, face and core and destination zones needed to the minimum value was chosen. The combined be modified. The two outer, boundary cells of raw linkage layer had a wide variance in values each core and destination zone was given a very between linkages, and a narrow variance within high value. The new core zone was then drawn a linkage. For instance, one linkage had values inside this buffer, or “moat” of cost. This way, ranging from 606-630 cost units, while another every gated least cost path enters each zone just had values ranging from 100-104. once rather than multiple times, which caused the flaw. To address this variance, the paired raw linkage layers were also classified into 5 categories of 7.5. PERFORM GATED LEAST COST PATH ANALYSIS equal classes (high, medium-high, medium, me- For each core/destination wild land pair the dium-low, and low linkage value) to create the following analysis was performed. (It was paired relative linkage value layers. The paired also performed between two “destination” wild relative linkage layers were combined in a simi- lands: the Santa Monica Mountains and the San lar fashion to create the relative linkage value. Gabriel Mountains.) The enhanced movement cost layer was used to create a cost distance It was decided that rather than use one or the surface to each wild land. The pair of cost dis- other technique, a combination would be used, tance surfaces were then used for the “corridor” with a higher emphasis on the relative linkage analysis using ESRI ArcGIS 9.0 software. The layer (see Theoretical Overview and Assump- cost of traveling through the “moats” was then tions for justification). There are many math-

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ematical approaches to combining these, but score, the highest possible habitat suitability because the variance of the raw linkage layer score, and the lowest possible human impact needed to be decreased, the square root was score, then it will receive a value of 1. All other used, along with multiplication. cells will receive scores less than 1.

7.7. ASSIGN CONNECTIVITY VALUE TO EACH SITE AND VISUALIZE RESULTS It was noticed after the analysis that seven im- The raw connectivity site value is the sum of portant but short linkages had not been mapped the values of all the connectivity layer cells in because the corresponding pair of wild lands the site, multiplied by the number of acres of had been grouped together as the central core each cell. Thus, the maximum score for a site is zone or had not been analyzed. These short equal to the number of acres of the site, which linkages were digitized by hand using the move- for the full sized sites is 555. The final con- ment cost layer as a guide. These are classified nectivity site value is determined by the normal- as “estimated linkages” and given a value of the ization procedure as described in B1. The site mean plus one standard deviation of the linkage values were then smoothed as per the meth- layer and added to that layer. Finally, the link- odology described for B1 to get the final Con- age layer was inverted and standardized, such nectivity Biodiversity Value. See Figure 15 of that the best linkage value is 1 and the worst Chapter 4 of the RCG: Landscape Connectivity is 0. See Figure 14 of Chapter 4 of the RCG: Biodiversity Value within the Conception Coast Large Wildlife Linkages within the Conception Region (B4). Coast Region. 8. SYNTHESIS PART 1: OVERALL 7.6. COMBINE RESULTS WITH HABITAT SUITABILITY BIODIVERSITY VALUE AND HUMAN IMPACT LAYERS For an introduction to this objective and an The “connectivity value” of a cell is a func- overview of the methodology, please see Chap- tion of the linkage value as well as the habitat ter 4 of the RCG. quality value of the cell and the human impact score of that cell (See Theoretical Overview and 8.1. WEIGHT EACH LAYER Assumptions). A variety of different weighted The relative weight of the four objectives were combinations were evaluated, and the one determined at an ecological advisor workshop, chosen had a good balance between maintaining and are as follows: Listed Species Hotspots: the integrity of linkages, but also allowing for 15, Habitat Representation: 20, Wild Lands and the site specific importance to be accounted for, Connectivity: 10. These weights were res- with a slight bias toward habitat suitability as caled so they added up to 1 and called Weight1, opposed to human impact: Weight2, etc.

8.2. COMBINE THE LAYERS The formula for determining the ecological Thus, if a cell has the highest possible linkage value of a site is as follows:

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Biodiversity Value of a Site = Weight1 X B1 is a “trend” model that seeks to predict future Relative Value + Weight2 X B2 Relative Value growth patterns based on indicators of past + Weight4 X B4 Relative Value + Weight6 X B6 growth patterns. It does not predict growth Relative Value based on current zoning or general plans (Lan- dis, Cogan et al. 1998 ; Fulton, Wilson et al. Thus, a site with a value greater than 1 could 2003). The model compares observed changes be “above average” for all the non-zero sites of in urbanized land during a specific time period each objective, or way above average for one with a variety of spatial and non-spatial factors, objective and slightly below average for anoth- such as site variables (land cover, political sta- er, and so on. It is important to recognize that tus, slope, etc.) and neighborhood characteristics several of the objectives have many sites that (distance to nearest major highway, percentage are zero, therefore a site that can muster a value of neighboring cells that are urbanized, etc.). It of 1 despite this handicap is very important then uses these changes to predict where on the ecologically. landscape the projected growth in human population will occur. 8.3. VISUALIZE RESULTS The site values were smoothed as per the meth- The model run used in the RCG was performed odology described for B1 to get the final Biodi- by the model creator, Dr. John Landis, for the versity Value. See Figure 16 of Chapter 4 of the entire state of California (but calibrated by re- RCG: Estimated Biodiversity Value within the gion) (Landis and Reilly 2004), and then clipped Conception Coast Region. to the Conception Coast Region. Despite the statewide scope, the resolution was quite high, PART 2: MAP “CONSERVATION VALUE” with analysis performed using a one hectare (INCLUDES THREAT) grid. The calibration model evaluated actual For an overview description of this analysis see growth for each region from 1988 to 1998 using Chapter 4 of the RCG, for an overview diagram, a stepwise logit regression model with regards see Figure 5, on the following page. to the following variables: distance to freeway( km – squared), regional job accessibility as of 1990, ratio of 1990 city-to-region median 9. PROJECTED HUMAN IMPACT FOR THE household income, FMMP- designated prime YEAR 2050 farmland, FEMA floodzone, floodzone in next For an introduction to this objective and an cell, flood zone 2 to 3 cells away, site slope, overview of the methodology, please see Chap- average slope of next cell, average slope of cells ter 4 of the RCG. 2 sites away, and within or outside of incorporated city. In this way the probability of devel- 9.1. MAP AND CLASSIFY PREDICTED URBAN opment for non-developed sites was determined. OUTGROWTH This probability is then combined with several The California Urban and Biodiversity As- factors: a forecasting scenario for the year 2020 sessment (CURBA) model was used to pre- for population growth by county, estimates of dict urban outgrowth in the region. CURBA development densities by areas, and estimates of

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Figure 5: Diagram of the Conservation Priorities Analysis

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inﬁll development versus development of open 9.2. MAP AND CLASSIFY PREDICTED RURAL AND space. All of the above factors are then estimat- SUBURBAN GROWTH ed again for the period between 2020 and 2050, To model the rural and suburban growth in and an output is derived for 2050 that shows the CCP region, we used the Western Futures which open space hectares are predicted to be Growth Model (WFGM) developed by David developed. This is the output used for the RCG. Theobald of the natural Resource Ecology Lab (A similar output was created and is available at Colorado State University (Theobald 2001; for the year 2100.) Theobald).

For a variety of pragmatic and logistical rea- The technical notes of the actual model run used sons, the following assumptions were employed were provided by Professor Theobald along in the model run: with the data, and are as follows: · The same factors that shaped land develop- “The purpose of the Western Futures ment patterns in the recent past will con- Growth Model (WFGM) is to develop broad- tinue to do so in the future, and in the same scale housing density maps to examine ways. the baseline patterns of exurban and rural · Jobs will continue decentralizing from Cal- development in the western US. The maps ifornia’s four major urban regions—South- are based on 2000 US Census Bureau block- ern California, the greater San Francisco group and block level geography. Housing Bay Area, the Sacramento region, and the density was computed by using the centers of southern San Joaquin Valley. block polygons and calculating the average · California’s population will continue to density within a 1,000 acre window (~1135 grow, and at more or less the same rate and m radius), using 200 m resolution. The in the same spatial pattern as projected by centers were computed from blocks that had the California Department of Finance (De- the undeveloped portions removed (mostly partment of Finance 2004). public but also includes water bodies). Cur- · Average inﬁll rates and population densi- rent (2000) patterns of housing density were ties will increase with additional develop- based directly on the block-level estimates of ment. housing units. Historical patterns (decades · No new freeways or intra- and inter-re- prior to 2000) of housing density were based gional rapid transit systems will be predict- on block-group level estimates of the number ed and modeled. Freeway road travel speeds of houses, which were then spread to blocks will remain at current levels. based on the 2000 distribution. Density was computed for the entire western 11 states For a map of the Urban Outgrowth Model Re- simultaneously to remove boundary effects sults, please see Figure 17 of Chapter 4 of the that would have been introduced in a state- RCG: Comparison of Current and Predicted Ur- by-state analysis. ban Extent within the Conception Coast Region. Density patterns for forecast (2010-2040) were based on county-level population pro-

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jections by state demographers. The main computed in terms of minutes of travel time assumptions of the model are as follows: from urban core areas (here deﬁned as >= 1. new growth within a county is most likely 1.5 housing units per acre), as one would to occur in locations where it has grown in travel along the transportation network (ma- the past decade (time step). jor roads and highways [2]) – not simply the Euclidean distance. 2. growth is computed as the average growth in each of 4 density classes (urban, sub- 5. Housing density will not decline over time urban, exurban, and rural), and these are (therefore areas undergoing urban decay are computed locally with each 1135 m radius. not modeled well). These local growth estimates are then spread throughout the entire surface so that The units of the data are # housing units per future growth is not constrained to occur acre, divided by 1000 (to make an integer where it had previously. There are two main grid), thus “25” = 40 acres per unit; and advantages of this approach. First, growth “625” = 1.7 acres per unit.” rates occur in a similar way as they have in the past. Second, growth rates are param- For a map of the Rural and Suburban growth eterized locally, not within some artiﬁcial Model Results, please see Figure 18 of Chapter analytical unit (e.g., state or county). This 4 of the RCG: Comparison of Current and Pre- allows different valleys or regions within a dicted Housing Density within the Conception county to grow individually. Coast Region

3. The number of housing units is forced 9.3. MAP AND CLASSIFY PREDICTED AGRICULTURAL to meet the demands of the new population EXPANSION within a county. That is, the number of new All of the obvious areas that agriculture could units in a county is proportional to the num- not expand to were mapped, and everything else ber of additional people in a decade. The was considered potential agricultural expan- model adjusts the overall numbers of hous- sion by the year 2050. The areas not available ing units to be constrained to the ratio of were already urban lands, reserves, conservation new housing units to old housing units (e.g., easements, current industrial lands, roads, water, for 2010: ((Pop2010 – Pop2000) / (Pop2000 creeks, and areas with too steep of a slope. The – Pop1990)) ). urban lands, reserves, conservation easements, roads, and oil development were selected from 4. The distribution of new growth is also ad- the layers developed for Human Impact 2000. justed according to accessibility to the near- Creeks and reservoirs were selected from the est urban core. That is, urbanization and Water Bodies and Water Courses databases (See conversion to urban and exurban land use Table A2). To determine what “too steep of a typically occurs in locations that are nearer slope” was, all of the agricultural lands from the urban core areas, but that are on the fringe agricultural layer used for Human Impacts 2000 where land is undeveloped. Accessibility is were selected and overlaid on a slope map, and

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the maximum slope for each agricultural poly- top of each other, and where two different lay- gon was determined. The slope map was de- ers overlapped, the one with the higher impact rived from a Digital Elevation Model (see Table prevailed. A dual map was created that shows A2). The mean, maximum slope of all agricul- the Human Impact Layer 2000 and the Human tural operations was 44.7 degrees, with a stan- Impact layer 2050 side by side. Each legend dard deviation of 16. The extreme outlier was is classified using an equal interval scale, and 73.57 degrees, which is likely an anomaly of the the same color ramp is used. See Figure 19 of data overlay procedure. Rather than using the Chapter 4 of the RCG: Comparison of Current max value as a threshold of developable agri- and Predicted Human Impact within the Con- cultural land as originally planned, we used the ception Coast Region. The resulting layer can is mean maximum, plus the standard deviation, or transformed into the Condition Weighted Area 60.7 degrees. Although not the maximum value for 2050 for later analyses, as per the earlier of 73.57, this is still a very inclusive value. It methodology. is recommended that if iteration 1.1 or 2.0 is performed, then this threshold is determined by 10. MAP THE HUMAN IMPACT “THREAT” local expert knowledge. Also, in this analysis, To better prioritize which cells to conserve, we areas that are in national forests were not con- considered which ones were under the high- sidered as potential agricultural lands. est degree of “threat.” Threat is in quotation marks, because there are several concepts of 9.4. MAP AND CLASSIFY PREDICTED INDUSTRIAL threat. The concept used here is the magnitude EXPANSION of change to the particular cell that is predicted We modeled the expansion which will most between now and a half century from now. In likely occur in the national forest if society RCG Version 1.0 we do not look at the probabil- continues its current paradigm of oil consump- ity that this change will occur for most of the tion. The draft EIS for oil and gas leasing of land-use change types (industrial expansion is the national forest overviews several alternative the only type that incorporates probability, and oil extraction scenarios (USDA Forest Service that is very coarse). In all other cases the land is 2001). Through some informal discussions with either predicted to change to a certain state, or to Forest Service employees, Alternative 5 was stay the same. Threat is quantified by subtract- considered as a low probability of occurring, ing the Human Impact Value of a cell in 2000 and the smaller geographic area alternative, 5a, from the predicted value in 2050. is considered a higher probability. After discussion at an advisory workshop, all lands of Al- To illustrate the issue, a couple examples are ternative 5a are given a human impact value of provided. If a cell is “ExUrban20” in 2000 0.84, and those of Alternative 5 a score of 0.25. (rural housing between 20-40 acres per unit), then it has a Human Impact Value of 0.26. If 9.5. OVERLAY THE ABOVE LAYERS that cell is predicted to convert to “Low Density All of the above layers were classified accord- Urban” (1.5-5 acres per unit), then it will have ing to the Human Impact Index Table A1, unless a value of 0.9 in 2050. The threat score is thus otherwise noted. They were then overlaid on 0.9 minus 0.26, or 0.64. The higher the threat

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score value, the higher the magnitude of the · the condition weighted area (human impact threat. If there is a Low Density Urban cell that values) of land in the site, is predicted to convert to High Density Urban, · and the condition weighted area of all then the threat value is only 0.1, even though the other sites where the habitat occurs probability is very high and the resulting human · projected condition weighted area of the impact is very high. The magnitude of ecologi- habitat in the site in 2050 if no conservation cal change, however, is pretty minimal, thus the occurs low threat score. · and the condition weighted area of the habitat in the region in 2050 if no conserva- The layer that results from this difference be- tion occurs. (Davis, Stoms et al. 2003). tween Human Impact 2000 and Human Impact 2050, i.e. predicted change in human impact, is A characteristic of the Legacy model is that it called the threat layer for the rest of the docu- allows ranking of sites by their marginal conser- ment. A map of the threat layer was created. vation value (or additional conservation con- See Figure 20 of Chapter 4 of the RCG: Predict- tribution) which acknowledges the reality that ed Change in Human Impact within the Concep- implementation of conservation plans happens tion Coast Region (i.e. “Threat”). on an opportunistic basis. In contrast to the typical threshold approach (such as SITES) that 11. OBJECTIVE C1: LISTED SPECIES HOT- requires a difficult determination of the mini- SPOTS CONSERVATION VALUE mum amount of habitat type that is “enough” for As per Davis, Stoms et al. (2003), listed spe- long term protection. The threshold approach cies are by definition threatened. It is reasoned also makes no distinction between the conser- that conservation of habitat that contains listed vation value of the first acre conserved for a species is important regardless of if that habitat habitat versus the 1,000th if the targeted goal is threatened or not. However, the ecological has not been met. In other words, the Legacy condition of the different sites of a listed species framework maximizes the amount of overall is an important factor to consider. As a result of biodiversity protection that can occur with a these two assumptions, the results of Objective given budget. The RCG model was originally B1 will be used for Objective C1 when synthe- developed to perform this site selection proce- sis of the conservation values occurs. dure, but then it was determined that such an analysis is problematic and too complicated for the audience, and it was not performed. How- 12. OBJECTIVE C2: HABITAT REPRESENTA- ever, the framework for the approach had al- TION CONSERVATION VALUE ready been built, so it was used to determine the 12.1. DETERMINE HABITAT REPRESENTATION WITH habitat representation biodiversity value needed THREAT VALUE for Part 2. This value could be determined in The site’s habitat representation conservation a much more straightforward approach if it is value is a function of the following: known in advance that site selection is not going · the habitat types at the site and their cor- to be performed. responding weights,

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An illustration of this distinction between mar- tion Value” of a site is the standardized* aver- ginal value and the threshold approach is pro- age between the Habitat Representation Threat vided on the following page as Figure A-1. Value for the site and the Habitat Representation Biodiversity Value for the site, determined in In this iteration of the RCG, “G” or long term objective B2. There are two reasons for in- conservation trajectory goal (Figure A-1) is corporating habitat weights. First, so that the 100% of the total Condition Weighted Area in results can be consistent and comparable to B2. 2000 (CWA 2000) of the habitat. (It is not a Secondly, without habitat weights, rarity is not goal in the traditional sense of the word in that really addressed by the Legacy model when it is it is not truly expected to be achieved; it is the only used to identify initial marginal value. direction we want to head.) For this iteration of [*Technical detail: To be consistent with the the RCG, “A” is assumed to be 0 for every habi- methodology for B2, a small adjustment was tat. In other words, the first acre conserved is made. The sum of all the weighted habitat more important than the second acre conserved, values for the region is 342150; the sum for the and so on. The total CWA 2050 for a habitat representation values for the region is 309012 or will be the “X” of Figure A-1. 0.90314 times. Thus, all of the weighted habitat values were multiplied by 0.90314 before being Once A, G and X had been determined for averaged with the representation values. It is every habitat, the habitat representation value recommended that this adjustment is not per- of a site was determined. For each habitat formed if iteration 2 occurs.] type in the site, the threat layer is overlaid and summed. This sum is little “x” of Figure A-1. The final units are similar to B2. A full 1.5 km In other words, it is the amount of CWA of the square site would receive the maximum value habitat the would be conserved if the site were of 555 if it is all threatened to go from pristine conserved. The representation value for that to urban, and is comprised solely of the most habitat in that site is thus the area under the blue threatened habitat type, with the highest weight. marginal value line and between X and X + x. All other sites would receive a lower score. The total area is much smaller for the habitats in What is most important, however, is the rela- which X is close to G, or when x is very small. tive scores among sites. These were normalized This procedure is done for every habitat in the for analysis between ecological objectives as site, and the results are added together to get the described in objective B1. “Habitat Representation Threat Value” for that site. It is possible to query the database to see 12.2. VISUALIZE RESULTS where big X is on the curve for each habitat (in The site values were smoothed, as per the a percentage, relative to G), and thereby get an methodology described for B1, to get the final indication of the degree of threat facing each habitat representation conservation values. See habitat type in the region. Figure 21 of the RCG: Habitat Representation Conservation Value within the Conception Coast Habitat weights were then incorporated into Region (C2). the analysis. The final “Habitat Representa-

Conception Coast Regional Conservation Guide Appendix A

Figure A-1: Utility Function Curves

Figure A-1. Utility functions and associated marginal utility functions for estimating site conservation value: (a) a utility function for target-based conservation where utility accumulates linearly until the speciﬁed conservation target (in this case 25% of current resource amount) is reached and then remains constant; (b) marginal utility function associated with (a); (c) the utility function used here for evaluating terrestrial biodiversity in the Sierra bioregion; (d) the marginal utility function associated with (c); (e) Change in marginal value associated with a conservation action today that increases the predicted future level of the resource from X to X+x. The total beneﬁt of the conservation action is calculated as the area under the marginal value curve. Figure courtesy of David Stoms.

Conception Coast Regional Conservation Guide Appendix A

13. OBJECTIVE C3: BIOPHYSICAL REPRE- and across all types of soils, substrates and topo- SENTATION CONSERVATION VALUE climates (Hunter et al. 1988, Noss 1991a). [This objective was not addressed within the fi- Unfortunately, there is a lack of digital bio- nal results of the Conservation Priorities Model. physical data for the Conception Coast Region. However, the preliminary data gathering and There are no soils map or geology map avail- analysis results are useful for potential future re- able as GIS layers. Therefore, an analysis was finements to the Regional Conservation Guide, performed using the “Ecological Subregions and are described below. of California: Section and Subsection Descrip- tions” developed by the United States Forest Concern for maintaining species and natural Service (Miles and Goudey 1998), were used communities should be accompanied by an (See Table 2). effort to maintain the ecological and evolutionary processes that will allow them to persist However, it was found that these subsections do and evolve over the long term. Fundamental not map the actual biophysical properties, and processes critical to ecosystem function include because some slivers of subsections occur in our cycling of nutrients and flow of energy, distur- region, the analysis lead to spurious results, and bance regimes and recovery processes (suc- was not used in the synthesis. The methods for cession), hydrological cycles, weathering and the analysis are provided below, as is a sample erosion, decomposition, pollination and seed of the biophysical description. The resource dispersal. Evolutionary processes, such as mu- itself can be very useful for regional conserva- tation, gene flow, and differentiation of population planning. tions, must be maintained if the biota is to adapt to changing conditions. 13.1. GATHER AND PROCESS DATA There is a lack of digital biophysical data for the Long-term change (decades to millennia) occurs Conception Coast Region. It was thereby not largely as a result of climate change. Plant and possible to perform a fine scale biophysical rep- animal response to climate change over time has resentation analysis similar to C2. Rather, the been to migrate with shifting climate areas. In- “Ecological Subregions of California: Section terestingly, plants and animals have migrated to and Subsection Descriptions” developed by the suit their own individualistic needs (Davis 1981, United States Forest Service (Miles and Goudey Graham 1986). 1998), were used. The subsections were clipped to the Conception Coast Region. Four subsec- A useful way to incorporate the needs of evo- tions had very small slivers that overlapped with lutionary processes into conservation planning the study region. These slivers were joined to is to represent the different ecosystem types of the most similar subsection that was well repre- the region in reserves. One of the best ways to sented in the region. represent all ecosystems is to maintain the full array of physical habitats and environmental 13.2. DETERMINE BIOPHYSICAL REPRESENTATION gradients in reserves, from the highest to the CONSERVATION VALUE lowest elevations, the driest to the wettest areas, The site’s biophysical representation conserva-

Conception Coast Regional Conservation Guide Appendix A

tion value is a function of the following: along the Cuyama River. It is between the Car- · the subsection type most common at the rizo Plain and the Sierra Madre Mountains. site, The climate is hot and subhumid to arid. ML- · the condition weighted area of the site, RAs 15f, 15g, 17f, and 17g. · the condition weighted area of all the sites for that subsection, LITHOLOGY AND STRATIGRAPHY. · projected condition weighted area in 2040 This subsection is dominated by clastic sedimen- if no conservation occurs, tary rocks and weakly consolidated deposits. · and the total condition weighted area for There are large proportions of upper Cretaceous the sites of that subsection in 2040 if no con- sedimentary rocks, Miocene marine sediments, servation occurs. (Davis, Stoms et al. 2003). Pliocene and Pleistocene nonmarine sediments, and Quaternary alluvium. Each site was assigned a subsection type. For sites that had more than one subsection over- GEOMORPHOLOGY lap with them, the most common subsection in This subsection contains steep mountains with the site was assigned. This objective also uses narrow canyons in the Caliente Range and low the marginal value framework of objective C2 hills, alluvial fans, pediments, and terraces (Figure A-1). The ﬁnal result was problem- along the Cuyama River. The mountains are atic, however. One medium size sliver (about oriented from northwest to southeast, curv- 50 sites) had been left as its own subsection ing around toward the east-southeast at the rather than joined with another subsection. The southeastern end where the mountains of this threat in this area is consistent and moderately subsection bend around on the southwest side of high—land predicted to move from agriculture a curve in the San Andreas fault. The Cuyama to urban. As a result of these circumstances, River runs lengthwise through the subsection, this objective was very strongly skewed to- along the southwest side of the Caliente Range. wards protecting this sliver at the expense of the The alluvial plain of the Cuyama River is broad region. It was determined that this sliver should in the southeastern part of the subsection, where have been joined with another subsection before it is about 5 or 6 miles across, with a fault on the analysis was performed. The current result the north-northeast side and Tertiary sediments was deemed to far removed from the theory and dissected Quaternary alluvial fans on the driving the objective, and was not included in south-southwest side of the valley. The eleva- the synthesis of the objectives. For an example tion range is from just under 2000 feet up to description to indicate the resource, the Caliente about 5000 feet. It is about 2000 to 2600 feet in Range – Cuyama Valley sub regional descrip- Cuyama Valley. Mass wasting and ﬂuvial ero- tion is pasted below. sion are the main geomorphic processes.

SUBSECTION M262AJ SOILS CALIENTE RANGE - CUYAMA VALLEY On upper Cretaceous sedimentary rocks, the This subsection comprises the mountains of the soils are mostly rocky Lithic Xerorthents and Caliente Range and hills and an alluvial plain Mollic Haploxeralfs. On Miocene marine

Conception Coast Regional Conservation Guide Appendix A

sediments, associated with badlands, the soils CLIMATE are mostly shallow Typic Xerorthents, Pachic The mean annual precipitation is from 6 to 10 Haploxerolls, and Mollic Haploxeralfs. On inches in Cuyama Valley up to about 15 inches Pliocene and Pleistocene nonmarine sediments, in the mountains. The precipitation is mostly the soils are mostly shallow Xeric Torriorthents, rain, with a little snow at higher elevations. Typic Xerorthents, and Typic Haploxeralfs. On Mean annual temperature is about 50° to 60° F. Quaternary alluvial fans, the soils are mostly The mean freeze-free period is about 175 to 225 Xerorthents, Typic and Mollic Haploxeralfs, days. and Pachic Argixerolls. On recent alluvium, they are Typic Xeroﬂuvents and Xerorthents and SURFACE WATER Typic Salorthids. The soils are well drained, Runoff from the mountains and hills is rapid, but but the Salorthids are exceptions. Calcium drainage is slow from some of the soils in the carbonates accumulate in the subsoils, and Cuyama Valley. The Cuyama River runs north- more soluble salts accumulate in some soils in westward through this subsection then, after Quaternary alluvium. Soil temperature regimes leaving the subsection, southwestward across are mostly thermic, with some mesic on north- the Coast Ranges toward the Paciﬁc Ocean. All facing slopes at higher elevations. Soil moisture streams other than the Cuyama River and its regimes are mostly xeric, but aridic in much of larger tributaries are dry through the summer. the Cuyama Valley. There are no natural lakes in the subsection. (Miles and Goudey 1998) ] VEGETATION The predominant natural plant communities 14. OBJECTIVE C4: WILD LANDS are Blue oak series, Needlegrass grasslands, CONSERVATION VALUE Chamise series on shallow soils, and California 14.1. IDENTIFY WILD AREAS annual grassland series around Cuyama Valley. The Wild Lands mapped in B4 were used as a Around Cuyama Valley, Allscale series is pres- starting point. ent on salty soils and Iodine bush series on very salty soils. California juniper series is present 14.2. DETERMINE WILD LANDS VALUE FOR EACH on the south side of Cuyama Valley. CANDIDATE SITE Characteristic series by lifeform include: This value is a function of the following: Grasslands: California annual grassland series, · the current and predicted condition weight- purple needlegrass series, Saltgrass series. ed area of the Wild Land in the candidate Shrublands: Allscale series, Arrow weed series, site, Bladderpod - California ephedra - narrowleaf · and the current and predicted condition goldenbush series, Chamise series, Cupleaf weighted area the entire Wild Land(s) that ceanothus - fremontia - oak series, Fourwing intersects the candidate site (Davis, Stoms et saltbrush series, Iodine bush series, Shadescale al. 2003). series, Spinescale series. Forests and woodlands: Blue oak series. California juniper series, This objective also uses the marginal value Mesquite series. framework of objective C2 (Figure A-1). “A”

Conception Coast Regional Conservation Guide Appendix A

is set at 25,000 condition weighted acres be- nario to play out, so anything above 100 is very cause this was the value used by Davis, Stoms important. What is most important is the rela- et al. (2003) and seemed to be an appropriate tive score among sites. These were normalized assumption. [One condition weighted acre is for analysis between objectives as described in 1 acre of land with a human impact value of 0 objective B1 (greater than 1 is above average for (highest condition), or 2 acres of land with a the non-zero sites of the layer.) human impact value of .5, and so on]. G was set at 1,000,000 condition weighted acres. This 14.3. VISUALIZE RESULTS is double the value used by Davis, Stoms et The site values were smoothed, as per the meth- al. (2003) for two reasons. First of all, 1 fe- odology described for B1, to get the contours of male mountain lion territory is about 76 square wild lands conservation value. See Figure 22 of kilometers or 18,780 acres (Dickson 2001), so 1 Chapter 4 of the RCG: Wild Lands Conserva- million acres is about 50 female territories, and tion Value within the Conception Coast Region male territories are sometimes more than double (C4). the female territories, so this is only about 20-30 male territories. There are a variety of mini- 15. OBJECTIVE C5: RESERVE ADJACENCY mum viable population thresholds cited in the CONSERVATION VALUE population viability analysis literature, which is For an introduction to this objective and an species speciﬁc, and 20-30 males is on the small overview of the methodology, please see Chap- side (no formal PVA analysis was performed ter 4 of the RCG. however). Secondly, this threshold allows the larger wild lands in the region to have at least a 15.1. METHODOLOGICAL ASSUMPTIONS small conservation value. · It is a higher priority to expand smaller reserves than larger reserves. The sum of the condition weighted acres for · Sites closer to the reserve boundary are 2050 for a particular wild land is the big X of more important than sites far from the re- Figure A-1. The sum of the condition weighted serve boundary. threat acres (the difference in CWA between · Only areas 1 km or less from current re- 2000 and 2050) for the portion of the site that serves should be considered. the wild land intersects (the whole site for a ma- · Cells that are more threatened with devel- jority of the sites) is the little “x” of the ﬁgure. opment are a higher priority for conserva- The area under the curve, between X and X + x tion. is the wild lands value for the site.

15.2. DETERMINE RESERVE ADJACENCY A site will get a full value of 555 if it is a full CONSERVATION VALUE sized site, the wild land that the site belongs to First, a “demand layer” was created. This is the has less than 25,000 condition weighted acres demand of a given cell for conservation based total in 2050, and all of the acres of that site on the reserve it is near. Smaller reserves have are predicted to go from pristine to completely a higher demand than larger reserves. Again, degraded. It is near impossible for such a sce- the detailed equation is in Davis, Stoms et al.

Conception Coast Regional Conservation Guide Appendix A

(2003). The area of each reserve was calcu- the value for a site, the connectivity conserva- lated. We assumed that a reserve twice as big tion values of all of the cells in that site were as the largest reserve in the region would have summed. a demand of 0. Thus we used c = .0001845. Each reserve was then buffered by 1 km, and all A site will get a full value of 555 if it is a full the cells in each buffer were assigned a value 1.5 km square, every cell in it has the high- resulting from the demand equation. Second, est possible linkage score, the highest possible an inverse distance surface was created which habitat suitability score, no human impact in simulates the assumption that cells closer to the 2000, and full human impact by the year 2050. reserve are more important than cells away from All other sites will receive scores less than 555. the reserve. The demand layer was then multi- It is near impossible for such a scenario to play plied by the distance layer to create the supply out, so anything above 100 is very important. layer. This indicates how important a cell is for What is most important is the relative score conservation based on these criteria, irrespec- among sites, as they will be normalized before tive of the threat to that cell. The supply layer combining with the other objectives. These was then multiplied by the threat layer to get the were normalized for analysis between objectives “C5 marginal value” layer. To get the value for as described in objective B1. a site, the C5 marginal values of all of the cells in the site were summed. The resulting units do 16.2. VISUALIZE RESULTS not make any intuitive sense, but after the values The site values were smoothed, as per the meth- are normalized as per B1, the resulting units are odology described for B1. See Figure 24 of the in the same scale as all of the other objectives RCG: Landscape Connectivity Conservation (greater than 1 is above average for the non-zero Value within the Conception Coast Region (C6). sites of the layer). 17. SYNTHESIS PART 2: CONSERVATION 15.3. VISUALIZE RESULTS PRIORITIES The site values were smoothed, as per the meth- For an introduction to this objective and an odology described for B1, to get the Reserve overview of the methodology, please see Chap- Adjacency Conservation Value Map. See Figure ter 4 of the RCG. 23 of Chapter 4 of the RCG—Reserve Adjacen- cy Conservation Value within the Conception The new objectives with threat included were Coast Region (C5). combined in the same way that the objectives were combined for Synthesis Part 1. The weight 16. OBJECTIVE C6: LANDSCAPE for C5 is the same as for C4 and C6, and is CONNECTIVITY CONSERVATION VALUE equal to 10. Since there are now ﬁve weights, 16.1. DETERMINE LANDSCAPE CONNECTIVITY CON- the actual weights used in the calculations SERVATION VALUE changed since they must sum to one, but their The connectivity layer that was created in B6 relative values stayed the same. The resulting was multiplied by the threat layer to get the site values were smoothed, as per the methodol- connectivity conservation value layer. To get ogy described in B1. See Figure 25 of Chapter

Conception Coast Regional Conservation Guide Appendix A

4 of the RCG: Estimated Conservation Priorities within the Conception Coast Region.

Conception Coast Regional Conservation Guide Appendix B Appendix B - Focal Species Profiles MOUNTAIN LION (FELIS CONCOLOR) of about 96 days. A newborn kitten weighs less The mountain lion is one of the few remaining than a pound at birth and is buff colored with large predators in the western ranges and inhab- black spots. The male does not participate in its the rugged and remote nature of mountain- raising the young. At 6-8 weeks of age, the kit- ous regions. Difficulties in establishing human tens may go on their first kill as observers. The settlements in the steep and rocky topography young stay with the mother until they are 1-2 have allowed mountain lions to endure. Moun- years old at which time they wander up to 100 tain lions play an important role as a top preda- miles before establishing their own range. They tor in the ecosystems of the Conception Coast can survive over eleven years in the wild. They Region. This species is vital in keeping deer use “scrapes” to mark territory, which consist populations in check as rampant deer popula- of mounds of dirt, leaves, and other debris piled tions can overgraze grasslands causing erosion into a heap and soaked with urine and/or scat. and a decline in water quality. However, altera- The diet varies according to season, availability, tion of habitat through urban development and appetite and hunting skill. They feed primarily road construction is occurring frequently in on large mammals such as deer, but also eat rab- remote, wild areas, which impacts the range and bits, rodents, porcupines, beavers, peccaries and number of this species. birds. After a kill, what the mountain lion does not eat right away, it will partially bury with Full-grown mountain lions tend to weigh 75 sticks, dirt or snow so it may return to feed for to 200 lbs with length ranging from 6 ½ feet several days (Cornett, 1982). for females up to 8 feet for males (including tail), and tail length ranges from 21-36 inches. Generally, these are cats found in mountainous Mountain lions have golden brown body with areas, but can range from open woodlands to dark stripes around muzzle. The back of their dense forests. Mountain lion habitats locally in- ears and tip of tail are blackish brown with their clude the hills of the Gaviota Coast, Los Padres chest and throats white. Kittens are spotted with Forest, Vandenberg Air Force Base and Santa dark rings on tail that vanish by six months of Monica Mountains. Linkages from large wild age. The long, thick tails provide balance during areas are necessary to allow gene flow to occur, leaps and climbs. These athletic cats are excel- as inbreeding of populations can cause decline lent climbers and jumpers, capable of leaping in numbers or local extinction.. Roads and 12 feet and jumping safely from a height of 60 human development constrict or clog major cor- feet. Mountain lions can outrun a deer, but only ridors for the mountain lion, reducing longev- for short distances. ity for the species. It is necessary to maintain linkages between the Southern Los Padres to Mountain lions tend to be a solitary animal that Northern Los Padres, Angeles National Forest pairs only for 2 weeks during breeding season. and Sequoia National Forest. Other corridors of Males are polygamous, mating with more than concern are the Vandenberg Air Force Base to one female. There is no fixed mating season, the Gaviota Coast as well as the Southern Los although births occur most often in midsummer. Padres. A full identification of corridor priori- 1 to 6 kittens are born after a gestation period ties is indicated in the results of the Regional

Conception Coast Regional Conservation Guide Appendix B

Conservation Guide. greatest limiting factor for steelhead in our region. CCP has done extensive work on barrier Conception Coast Project has also launched a analysis on the South Coast of Santa Barbara mountain lion sightings page on its website; this and is doing a coarse regional level analysis for will allow citizens to input where mountain lion the Regional Conservation Guide (see Appendix sightings occurred. This information will aug- C). ment future Conception Coast Project analyses. Mountain lion habitat and linkages are useful Steelhead were once abundant in almost all in identifying crucial areas for protection in of the major watersheds within Santa Barbara regional conservation. and Ventura Counties, with the largest runs of adult steelhead occurring in the Santa Ynez, SOUTHERN STEELHEAD (ONCORHYNCHUS Santa Clara, Santa Maria and Ventura Rivers. MYKISS) The Santa Ynez had the largest population of Southern steelhead inhabited many creeks of the steelhead in all of southern California with es- Conception Coast Region at the beginning of timates of 13,000 to 25,000 adults returning in the 1900’s; however, human modiﬁcation in the the 1943, 1944 run (Titus, et al. 2000). past 50 years have brought populations to less than 1% of its historic population size. The Na- Steelhead have an amazing life span, spawning tional Marine Fisheries Service (NMFS) listed in cool, well oxygenated streams. This habitat the unique southern steelhead as a federally type is usually associated with the upper reaches endangered species in 1997. Steelhead are an of many streams. Steelhead utilize eggs incu- important barometer of a stream’s health and an bated in gravel; eggs hatch into a larval stage important part of our natural heritage (Stoecker, (alevin) where they remain and feed on their et al. 2002). attached yolk sack.

Steelhead are migratory rainbow trout that are Smolts which are steelhead changing from born in freshwater streams, migrate to live in a freshwater to saltwater species leave their the ocean and return to creeks to spawn. Steel- stream habitat and may spend a period of time head’s range starts in northwestern Mexico and in an estuary before entering the ocean. During continue to Alaska. Genetic studies have con- life at sea, southern steelhead can attain large cluded the evolutionary significant unit (ESU) sizes while feeding off of squid, and amphipods. from Santa Barbara County to Mexico is a distinct from northern populations. The south- Drought and human activities often impair ern species have the ability to survive in warmer southern steelhead from accessing their natal waters. This species also grows faster and streams. Southern steelhead will adapt or delay migrates more rapidly than its northern ancestor. their upstream spawning migration until adequate flows exist or they may choose another Conception Coast Project has been examining stream to inhabit. When favorable flow condi- barriers to steelhead migration, as construction tions exist, adult steelhead enter the lagoon for of migration barriers such as road crossings, their upstream migration. Usually, steelhead dams, and flood control structures is the single enter the streams during periods of large rainfall

Conception Coast Regional Conservation Guide Appendix B

such as fall, winter, and early spring.

After adjusting to the freshwater, steelhead navigate upstream toward the higher quality spawning and rearing habitat. Shade is important during this navigation with trees and bank side vegetation being useful for shade and protective cover. The ﬁsh use rocks and boulders to rest behind as they navigate upstream to once again spawn (Stoecker, et al 2002).

Conception Coast Regional Conservation Guide Appendix C Appendix C - Steelhead Analysis INTRODUCTION Creek in the west to Rincon Creek in the east. Conception Coast’s Region has traditionally had The report has been successful in identifying runs of southern steelhead in its creeks. Popula- critical barriers for removal to open up prime tions of southern steelhead existed in almost habitat for endangered steelhead. Successful all of the significant watersheds within Santa work has been completed and is on going on Barbara and Ventura Counties, with the largest priority watersheds that include Carpinteria, San runs of adult steelhead occurring in the Santa Ysidro, Rincon and Mission. Ynez, Santa Clara, Santa Maria and Ventura Rivers. Thousands of steelhead left the hunt- Conception Coast Project has expanded its ing grounds of the Pacific Ocean to ascend the steelhead analysis to look at the critical water- coastal streams before rapid alteration of our sheds of the entire region. This analysis uses creeks occurred from the 1940’s onward. The existing information on the watersheds that was modification of our region’s streams through transferred to a GIS in order to identify critical migration barriers, water extraction, and altera- watersheds and barriers in our region. The re- tion of riparian and aquatic habitats led to the sults of this regional analysis will aid in locating elimination of steelhead in most of southern the most biologically important watersheds as California’s streams. During the past fifty years, well as the barriers that block access to spawn- the decline has been most dramatic as steelhead ing habitat for steelhead. This information will were no longer able to navigate the streams lead to more efficient actions towards restoring that they once inhabited because of extensive steelhead. modifications to stream habitat (Stoecker, et al. 2002). METHODOLOGY Conception Coast Project utilized spawning As stated in the previously, due to the unique- substrate, substrate embeddedness, surface ness of the southern steelhead and their near ex- flows, pool abundance, in-stream cover and tinction, the National Marine Fisheries Service riparian canopy cover to form the basis of the listed the southern California steelhead Evolu- watershed habitat score. The values of each tionarily Significant Unit (ESU) as endangered category are explained below in further detail. in 1997. The southern steelhead is currently the The analysis was similar to Conception Coast most endangered steelhead ESU in all of Cali- Project’s prior steelhead analysis on the South fornia. Estimates of the current steelhead popu- Coast in 2002. Existing reports were utilized lation size in southern California is less than 1% with special attention to descriptions to these of its historical size (Stoecker, et al. 2002). topics.

Conception Coast Project completed an ex- ABUNDANCE OF SPAWNING SUBSTRATE tensive study of the coastal watersheds of the The relative abundance of adequately sized South Coast that identiﬁed the most biologically spawning substrate within a given stream reach important watersheds for steelhead and prior- was identiﬁed from existing reports (Kelley, ity barriers for removal that block access to the 2004; Allen, et al. 2003; Titus, et al. 2000; Santa watersheds. The study extended from Jalama Ynez River Tech., 2000, NMFS, 2005). Indica-

Conception Coast Regional Conservation Guide Appendix C

tion of significant spawning substrate was given 0.5= Minimal Surface Flows a score of 0 to 1.5. The scores were based on Reach has indications of minimal surface this criteria: flows throughout the year. 0= Adequately sized spawning substrate 1.0= Adequate Surface Flows scarce or absent. Adequate surface flow conditions are be- 0.5= Low abundance of adequately sized lieved to occur in this reach ranging from spawning substrate present. minimal to perennial flows. 1.0= Moderate abundance of adequately 1.5= Adequate to Perennial sized spawning substrate present. Reach ranges often has perennial flow in 1.5= High abundance of adequately sized most years with indications of slightly di- spawning substrate present. minished flows in other years 2.0= Perennial SUBSTRATE EMBEDDEDNESS Indications that surface flows exist continu- Research on substrate embeddedness was ously throughout the year in this reach. utilized to build the GIS database. It is important that substrate not be embedded to allow POOL ABUNDANCE steelhead spawning. Indication within existing The relative abundance of pools (greater than reports of substrate embeddedness occurring 2 feet in depth) was researched from existing with a habitat reach was recorded. The scores reports. The following scoring categories were were based on this criteria: given: 0= Greater than 75% substrate embedded- 0= Pools scarce or absent. ness 0.5= Relatively low abundance of pools 0.5= 75%-50% substrate embeddedness present. 1.0= 50%-25% substrate embeddedness 1.0= Relatively moderate abundance of 1.5= Less than 25% substrate embeddedness pools present. 1.5= Relatively high abundance of pools SURFACE FLOW present. Surface water flows can be highly variable in 2.0= Relatively high abundance of pools stream reaches of the Conception Coast Region. present with multiple “refuge pools” (great- These fluctuations are often due to annual pre- er than 5 feet deep) present. cipitation and water extractions. Stream reaches that sustain some surface water throughout the IN-STREAM COVER year are critical for salmonids. Steelhead reside CCP staff researched in-stream cover with in fresh water for at least the first year of their emphasis on cover from large substrate, bedrock lives and spawn in fresh water. Information ledges, large woody debris, roots and undercut from existing reports was utilized with these bank. The criteria is as follows: criteria: 0= Scarce or Absent 0.0= Dry 0.25= Low Prolonged dry streambed conditions gener- 0.5= Moderate ally occur in this throughout the year. 0.75= Moderate to High 1.0= High

Conception Coast Regional Conservation Guide Appendix C

RIPARIAN CANOPY COVER Riparian canopy cover is crucial as it provides SANTA MARIA WATERSHED shade keeping water temperatures cool for The major steelhead habitat within the Santa steelhead. Riparian canopy cover densities Maria Watershed is deep within the Sisquoc were then given the following scores: River. 4 partial barriers (gravel operation, dam 0= representing no riparian canopy cover structure, road crossing and culvert crossing) 0.5= canopy cover minimally present block roughly 50 miles of the highest quality 1.0= canopy cover present habitat. These barriers block the largest amount 1.5= corresponding to very significant ri- of high quality habitat within the region. The parian canopy cover. upper reaches of the Sisquoc River is of extremely high value for with its large quality and SYNTHESIS quantity. The categories just explained were then added for each stream and divided by ten. The pos- SANTA YNEZ WATERSHED sible high score was .95. The streams were On the Santa Ynez River, Bradbury Dam, which then categorized by value as low quality (0-.25) forms Lake Cachuma, blocks roughly 35 miles medium (.3-.55), medium high (.6-.75) and high of the highest quality habitat on the Santa Ynez. (.75 to .95) with values able to be seen on the Santa Cruz Creek and its west fork have the following maps. largest stretches of high quality habitat within the watershed. RESULTS OF PRIORITY BARRIERS AND VENTURA WATERSHED HIGH QUALITY HABITAT There are smaller stretches of high quality habi- Major stretches of high quality steelhead habitat tat on the Ventura River compared to the other were found located within the Santa Ynez Wa- watersheds analyzed within the region. There tershed, Santa Clara, Santa Maria and Ventura. is a high quality lower stretch of the Ventura The following paragraphs and maps indicate the River. This 2.5 mile stretch is blocked by only areas with the highest quality steelhead habitat one partial barrier. and barriers along the streams. Further up the watershed, the North Fork of SANTA CLARA WATERSHED the Matilija has roughly 5 miles of high quality The analysis on the Santa Clara Watershed indi- habitat that is blocked by the partial barrier pre- cated that Vern Freeman Diversion Dam is the viously mentioned plus one total barrier (Robles priority barrier identified that blocks roughly 25 Diversion Dam) and one partial barrier. miles of high quality habitat on the Sespe River. The Vern Freeman Diversion Dam has a fish Santa Antonio Creek has roughly 11 miles of ladder installed aiding passage; however, it is high quality habitat; however, 5 temporal, 4 considered a partial barrier. The highest quality partial and 2 total barriers are littered on this stretch of the Sespe River is from Devil’s Gate stretch, blocking much of this habitat. north to where the river bends sharply west.

Conception Coast Regional Conservation Guide Appendix C

Figure C-1: Steelhead Barrier and Habitat Quality Map of Santa Clara Watershed FRONT

Conception Coast Regional Conservation Guide Appendix C

Figure C-1: Steelhead Barrier and Habitat Quality Map of Santa Clara Watershed BACK

Conception Coast Regional Conservation Guide Appendix C

Figure C-2: Steelhead Barrier and Habitat Quality Map of Santa Maria Watershed FRONT

Conception Coast Regional Conservation Guide Appendix C

Figure C-2: Steelhead Barrier and Habitat Quality Map of Santa Maria Watershed BACK

Conception Coast Regional Conservation Guide Appendix C

Figure C-3: Steelhead Barrier and Habitat Quality Map of Santa Ynez Watershed FRONT

Conception Coast Regional Conservation Guide Appendix C

Figure C-3: Steelhead Barrier and Habitat Quality Map of Santa Ynez Watershed BACK

Conception Coast Regional Conservation Guide Appendix C

Figure C-4: Steelhead Barrier and Habitat Quality Map of Ventura Watershed FRONT

Conception Coast Regional Conservation Guide Appendix C

Figure C-4: Steelhead Barrier and Habitat Quality Map of Ventura Watershed BACK

Conception Coast Regional Conservation Guide Appendices References For Appendices Allen, M., S. Riley, S. Thobaben (2003). Assessment of Steelhead Habitat in Upper Matilija Creek Ba sin. Prepared for Ventura County Flood Control Division.

Beier, P. (1995). “Dispersal of Juvenile Cougars in Fragmented Habitat.” Journal of Wildlife Manage ment 59(2): 228-237.

Beier, P., D. Choate and R. H. Barrett (1995). “Movement Patterns of Mountain Lions During Different Behaviors.” Journal of Mammalogy 76(4): 1056-1070.

Cornett, Jim (1982). Wildlife of the Western Mountains. Nature Trails Press. Palm Springs, Ca.

Davis, F. W., C. J. Costello and D. M. Stoms. (Submitted). “Efﬁcient conservation in a utility-maximiza tion framework.” Ecology and Society.

Davis, F. W., D. M. Stoms, C. J. Costello, E. A. Machado, J. Metz, R. Gerrard, S. Andelman, H. Regan and R. Church (2003). A framework for setting land conservation priorities using multi-crite ria scoring and an optimal fund allocation strategy. Santa Barbara, CA, University of California, Santa Barbara; National Center for Ecological Analysis and Synthesis; Report to The Resources Agency of California.ftp://ftp.biogeog.ucsb.edu/pub/users/stoms/CLP/Reports

Department of Finance (2004). Population Projections by Race/Ethnicity, Gender and Age for California and Its Counties 2000-2050. Sacramento, California, State of California.http://www.dof.ca.gov/ HTML/DEMOGRAP/DRU_Publications/Projections/P3/P3.htm

Dickson, B. (2001). Home range and habitat selection by adult cougars in the Santa Ana Mountain range of Southern California, Northern Arizona University.

Kelley, E. (2004). Information synthesis and priorities regarding steelhead trout (Oncorhynchus mykiss) on the Santa Clara River. Prepared for The Nature Conservancy.

Kuchler, A. W. (1977). A map of the natural vegetation of California. Terrestrial Vegetation of Califor nia. M. G. Barbour and J. Major. New York, John Wiley and Sons.: 909-938.

Conception Coast Regional Conservation Guide Appendices

Landis, J. D. and M. Reilly (2004). How We Will Grow: Baseline Projections of the Growth of Califor- nia’s Urban Footprint through the Year 2100. Department of City and Regional Planning, Uni- versity of California, Berkeley, Support provided by the California Resource Agency and the California Energy Commission.http://www-iurd.ced.berkeley.edu/pub/WP-2003-04-screen.pdf

McHarg, I. L. (1971). Design with nature. Garden City, N.Y., Published for American Museum of Natu ral History; Doubleday/Natural History Press.

Miles, S. and C. Goudey (1998). Ecological Subsections of California: Section and Subsection Descriptions, USDA Forest Service, Paciﬁc Southwest Region and Natural Resources Conserva tion Service, and Bureau of Land Management. 2005.http://www.fs.fed.us/r5/projects/ecore gions/title_page.htm

National Marine Fisheries Service (2005). Southern California Steelhead ESU, Current Stream Habitat Distribution Table. http://swr.ucsd.edu/hcd/SoCalDistrib.htm

Santa Ynez River Technical Advisory Committee (2000). Lower Santa Ynez Fish Management Plan. Prepared for Santa Ynez River Consensus Committee

Stoecker, Matt and Conception Coast Project (2002). Steelhead Assessment and Recovery Opportunities in Southern Santa Barbara County, California. Santa Barbara, Ca.

Theobald, D. M. (2004). Technical description of mapping historical, current, and future housing densi ties in the US using Census block-groups, Natural Resource Ecology Laboratory Colorado State University.http://nrel.colostate.edu/~davet/western_futures1990_data_tech-readme.pdf

Titus, R.G., D.C. Erman, and W.M. Snider (2000). History and status of steelhead in California coastal drainages south of San Francisco Bay. Draft. California Department of Fish and Game, Sacra mento.

Conception Coast Regional Conservation Guide