Plantalytics: Developing Assistive Technology for Designing Multi-Hazard Resilient Food Production Systems

Plantalytics provides rapid site analysis that can be easily translated into design, helping those in the business of planting reduce the planning time required to develop multi-hazard resilient ecosystems.

The relationship between human activity, environmental quality, and ecosystem services is only growing more complex and pressing with climate change. Whether working to address concerns over food insecurity, environmental hazards, or habitat loss, information is a primary barrier to informed environmental decision making. 

Through years of work in ecological site design a pattern of site analysis and species selection developed into a routine and perfunctory design process, leading to the understanding that the process could become streamlined, automated, and built upon. In this process relevant data from landscape (e.g., elevation, slope), climate (e.g., precipitation, temperature), and soil (e.g. type, pH), would be used to determine a master species list that could be further honed with data about environmental hazards (e.g., wildfire, flood) and climate change (e.g., forecasted precipitation). This preliminary site analysis process enables one to learn much about a site without ever having stepped foot on it; providing not only considerable site data relevant to many fields (e.g., engineering, architecture) but also a palette of plants tailored to current environmental conditions and those species tolerant to likely shifts in site conditions.

Primary target audiences for Plantalytics are those involved with the establishment and management of landscapes, namely gardeners, farmers, and those who facilitate their work such as university extension offices and conservation district managers. Restoration ecologists and homeowners alike can rapidly determine site parameters and identify species tailored for their sites. Other potential users are developers, architects and landscape architects seeking to streamline pre-occupancy species selection for new homes to capitalize on the burgeoning interest in edible landscaping and pseudo-agricultural residential developments.

Learn More

Learn Even More

Written by Hunter Heaivilin as part of coursework in the Disaster Management and Humanitarian Assistance (DMHA) graduate certificate program at the Department of Urban and Regional Planning at the University of Hawaii at Manoa , 2013.

Plantalytics: Developing Assistive Technology for Designing Multi-Hazard Resilient Food Production Systems

This era is typified by a growing awareness and consideration of the increasingly global food system by which our world is fed. While there is more food grown now than at any other time in history (FAOSTAT Gateway, 2014), the once siloed systems of local production have become increasingly subsumed and even eliminated by global market forces (De Schutter, 2011). With growing concerns over food access, quality, and sustainability, localized production has become increasingly viewed as a foil for the perceived vagaries of a global food system (Morgan, 2010). This trend has extended across the Pacific to the island state of Hawaii, where popular media (Brown, 2010; Hawaii Independent Staff, 2011) parrots the dubious number of 85% imported food (Page, Bony, & Schewel, 2007). No matter the unknown realities (Leung, & Loke, 2008; Harmon, 2014) or the perceived problems (The Kohala Center, 2014), there is a clear demand for increasing productivity in the state, from both producer (Plasch Econ Pacific, 2011; Kanu Hawaii, 2014) and consumer (OmniTrak, 2011) perspectives. Based on the authors years of experience, in environmental education, agricultural development, and ecological design, one of the primary barriers to increased production, particularly for those new to growing, is concern over having sufficient information to make informed decisions about planting. Such apprehensiveness over the planting of context and climate appropriate species can be, at least in part, remedied through assistive technology. The Plantalytics application, outlined in this paper, offers a means to perform basic site analysis from a distance, compile species lists, and assist in the design of multi-hazard resilient agro-ecosystems. While those are the three primary functions that form the core services of the technology there are other potential extensions that have been identified which will also be addressed. 

This paper will outline the story of foundational ideas and experience that led to the inception and development of the Plantalytics software concept. Following the history is a brief overview of other existing technologies with similar functions. An outline of the functionality of Plantalytics as well as the data sets required to perform those functions will be articulated. Next there is a review of some of the potential users and the impacts of their applications of Plantalytics. Finally this paper is concluded by addressing some of the gaps and barriers, additional functionality extensions, and next steps to realize the program. 

Concept Development

Through years of work in ecological design, agroforestry, and community development there evolved a pattern of site analysis and species selection that become codified and consistently followed. The process began with determining the annual and seasonal rainfall for the site and researching plant species that would perform well within the precipitation spectrum; these were then compiled into a species master list. Over time this list would be pared down by cross-referencing the filtering information found in soil data, client needs, and site microclimates (e.g. areas of ponding, etc). Alongside the species data compilation and processing there would be a parallel track data collection involving the determination of site data related to the parcel based on the tax map key. The data would include lot size and shape, sale price and history, building footprints, potential hazards and the use and management history. This preliminary site analysis process became a routine and enabled one to learn a fair amount about a property without ever having stepped foot on it. As this routine became a relatively perfunctory design process, it became apparent that the process could become streamlined, automated, and built upon. 

Multi-hazard Agro-Ecosystems and Food Security

Through previous academic and professional research there a theoretical approach to building multi-hazard resilient food security was developed (Heaivilin, 2011; Heaivilin, 2013). While Plantalytics itself is not solely focused on food crops, there is functionality suited to those looking to create agro-ecosystems tailored towards bolstering food security. Multi-hazard agro-ecosystems are defined as polycultural production that incorporates a broad species diversity that has been selected based upon the natural hazards likely to be faced onsite. Multi-hazard agro-ecosystems are seen as being nested within but distinct from multi-hazard food security, which involves aspects of the supply chain that extend beyond production into distribution and exchange.

Growing interest and concern over sustained food provision has led to food security having a suite of definitions relating to human welfare, self sufficiency, and caloric energy requirements (Pinstrup-Andersen, 2009). In multi-hazard agro-ecosystems the benefit to food security is on providing a buffer to keep communities from dipping below baseline nutritional and caloric intake during times of crisis. While not intended as a means of daily sustenance multi-hazard agro-ecosystems can easily be integrated with, or provide a skeletal framework for highly productive and durable agricultural systems. The keys to the durability of food security are found in the three main tiers of cultivar classification in the multi-hazard agro-ecosystems approach for multi-hazard food security that underpins the Plantalytics software: nutritive groups, functional groups, and response groups. Additionally another suite of species oriented towards management amelioration and diversification of production may be added as a fourth tier of establishment groups. 

Nutritive groups. The nutritive groups consist of perennial species (most frequently trees) that are high in either fats, proteins, or carbohydrates. While consuming a diet void of vitamins and micronutrients is not ideal, the extent of selection parameters to address every human nutritive need would be exhaustive. Hence emphasis is placed on the three aspects of nutrition needed in greatest quantity. Species are allocated to a nutritive group based on the dominant nutrition provided per yield. Though each plant yield contains a diversity of macro and micronutrients, which should further reduce any concern over the narrow (three nutritive group) intake parameters. Species are placed in a group based on relative rather than absolute characteristics, in order to allow for variances within species found in different climatic niches. For example avocado (Persea americana) may be selected for its fat content in tropical areas whereas pistachio (Pistacia vera) would be only suited for mediterranean climes; even though pistachios provide nearly three times as much fat by weight. The number of species in each group will vary based on climate, other selection criteria, and species data set population. The importance of making nutritive groups an explicit part of multi-hazard agro-ecosystems is in the need for dietary diversity and in the importance of polycultural plantings.

Functional groups. Once the three nutritive groups (fats, proteins, carbohydrates) have been populated with various species, the groups are then further selected into functional groups, which are cohorts of species that perform similar ecosystem functions. Functional groups can categorized in various ways like vertical strata (e.g. canopy species, ground-covers, etc), successional needs (e.g. shade tolerances), functional traits (e.g. nitrogen fixation), size, speed, and even architecture of growth (Messier, Puettmann, & Coates, 2013). The collections of species in each functional group provide the same basic services, though they may go about doing so in different ways (Walker & Salt, 2006). This diversity of service provision ensures a continuity of ecosystem function even if individual species are lost to system, and thus acts as a form a redundancy.

Response groups. Transforming redundancy into resilience occurs through each functional group contain species with a range of responses to changes in environmental conditions. In multi-hazard agro-ecosystems the diversity of tolerances by species within a functional group are classified into response groups. In this selection tier the species which share tolerance to certain disturbances such as fire, drought or flooding are grouped. For example, while both cashew (Anacardium occidentale) and macadamia (Macadamia tetraphylla) could both be classified in the fat nutritive group, only cashew would be selected as part of a fire response group, due to its relative tolerance (Campbell, Hodgson, & Gill, 1999). The diversity of responses enables a functional group to persist in the face of varying conditions. In the case of multi-hazard agro-ecosystems, response groups represent the multi-hazard resilience facet of the broader multi-hazard food security. 

Establishment groups. An adjunct selection of species can be compiled to plant along with each of the tree selections; these cohorts are known as guilds in permaculture design (Mollison, 1988) and ecological community morphology (Simberloff & Dayan, 1991), and termed establishment groups in multi-hazard agro-ecosystems. Each establishment group is arranged as a team of support species to increase the success of tree out-plantings, as well as to diversify material yields. Akin to companion planting, the crux of an establishment group is symbiotic interaction. Guilds are unique in that while companion planting is most commonly about the relationship between two species, an establishment group “is an harmonious assembly of species to support a central element [such as a selected tree species in multi-hazard agro-ecosystems]. This assembly acts in relation to the element to assist in its health, aid our work in management, or buffer adverse environmental effects” (Mollison, 1988, p. 60). The establishment group provides yields to system managers (like short term food crops, or decreased labor) as well as to the tree (i.e. central element) around which the guild has been built. These yields occur in various spatial niches to make each outplanting more like the microcosm of an ecosystem with species of different habits. The spatial range covered by establishment groups will reach from horizontal ground-covers to vertical climbers and everywhere in between. The temporal range can run from short term vegetable crops, making use of sunlight available before the central tree creates much shade, up to nitrogen fixing nurse trees which will be used as in situ mulch and fertilizer for years to follow. 

The establishment group surrounding a given planting is designed to provide for various functions that, though found in functional groups, may not be in close proximity due to the distances required for successful tree and perennial species plantings. 

Sample selection process. To demonstrate the selection process the subtropical tree Tahitian Chestnut (Inocarpus fagifer) will be explored. Looking at the nutritional, functional, and tolerance information for the Inocarpus sp. (Pauku, 2006), it can be noted that this traditional tree crop of the South Pacific is high in carbohydrates (22% by volume of edible nut), which places it into the carbohydrate nutritional group. Due in part to being a member of the Fabaceae (Legume family) this species is noted in some locations for having root association with Rhizobium spp. bacteria that fix atmospheric nitrogen, making Inocarpus sp. part of the nitrogen-fixing functional group. Through assessing its native range and adaptations, the species has shown to be tolerant of seasonal flooding, making it part of the flooding response group. Seedlings planted today are not likely to bear fruit for another three to five years (Janick & Paull, 2008), but young trees can be intercropped with an establishment group of the ground-cover sweet potato (Ipomea batatas), climbing yam (Dioscorea alata), the herbaceous taro (Colocasia esculenta), short lived perennial pigeon pea (Cajanus cajan), and banana (Musa spp.). The Cajanus sp. will provide additional nitrogen fixation in the soil and can be coppiced for nutrient rich mulches, while the Musa spp. can be used as an emergency water source due to the high moisture content of the pseudostem (banana stalk). Outside of just providing sustenance for the Inocarpus, as a group these species will provide immediate food yields (as quickly as a few months to a bit over a year) that will persist until the Inocarpus sp. matures and shades out the area. The diversity of the establishment group yields function not only to provide materials for system managers but also increase the likelihood of visitations to young tree out-plantings as there are immediate crop yields to be harvested.

Application Inception

Subsequent to the development of the multi-hazard agro-ecosystem model and the initial musings regarding design process streamlining a search began for appropriate and accessible data sets. This process began with contacting the self-publishing primary author of a three book set (titled Permacopia) on cultivated species of various human utility for use in the Hawaiian islands (Beyer & Martin, 2006). This book set was chosen for its breadth which covers native, indigenous, cultivated, and weedy species. The book set also goes into considerable depth with each species, articulated climatic niche, soil preferences, and in some cases a limited set of hazard tolerances. After some time of communication with the publisher free access to all of the written data within the books has been offered; with the hope that the information be shared and propagated and the condition that should profit be garnered from such endeavors that funds be shared accordingly. Other early data sets that were sought after included the Online Rainfall Atlas of Hawaii (Giambelluca, et al., 2013), and that from SoilWeb (by the California Soil Resource Lab at UC Davis and UC-ANR in collaboration with the USDA Natural Resources Conservation Service). After speaking with the developers of those programs data pathways were found to their open sourced data. The rainfall, soil, and Permacopia data sets composed the totality of the initial concept of the Plantalytics application but over time it became apparent that the program could offer much greater functionality. 

Market Study

Through previous searches for plant database analysis tools and searching for mobile applications it has been found that there exist numerous mobile and web based plant selection applications. The three primary parameters for analysis, based on desired outcomes for Plantalytics, are that applications have (1) a broad species list, (2) contain function and tolerance analysis of those species, and (3) be able to perform a sort of ground truthing (albeit remote) of species suggestions via site data. Of the applications assessed those that offer broad species lists with good user interfaces (often for mobile devices) are most commonly focused on ornamental species are often limited to certain (frequently temperate) climatic niches (e.g. Plant Picks, available in the iTunes store) . Of those applications with broad species lists, in depth species data, and beyond ornamental species functionality (e.g. Agroforestree Database, http://www.worldagroforestry.org/resources/databases/agroforestree) there are only two that allow for cross collation with site data: The FAO’s EcoCrop (2007) and Plants for A Future (2014); all of which are web applications with no mobile accessability. In using each of the exceedingly useful web applications it was found that in order to determine species sets with greater value to planting a variety of site condition information was required to be known, for example soil pH, precipitation regime, and so forth. For the many novices who are interested in knowing what to plant and how, knowledge of this information or even where to find such data is limited. Because of this information deficit a good user interface that automatically determines site conditions is required for the application to be of use to those with limited working knowledge of site conditions or species. 

Based on this analysis there is a clear opportunity for an application that is robust enough to provide useful information to experts, but is also able to package that information in a manner that is also be accessible to those with limited experience. 

Functionality

The Plantalytics application activity process begins with site identification, in the case of mobile use the internal GPS of smartphones will be used while in the case of web applications the user will navigate to the site via a map interface (likely using Google Maps or Google Earth API). Once the location point has been identified data recall processes commence to determine the following: precipitation values, solar radiation (peak sun hours), elevation, soil type, and parcel data (via Tax Map Key). The parcel data sets will include TMK number, zoning information, area, and parcel boundaries. The parcel boundary data layer will then be cross referenced with hazard data layers (e.g. tsunami inundation zones, fire risk, etc) to compile a list of hazards and, when applicable, the risk or likelihood ratings. This broad suite of climatic and related site data is used to automatically populate the query fields of a plant database. The extensive species list produced as a result will then be able to be filtered manually by the application user to explore suites of species by characteristics such as spatial niche (e.g. canopy tree, understory tree, etc), nutritional makeup (i.e. nutritive group), functional niche (i.e. function group), hazard tolerance (i.e. response group), and associates (i.e. establishment groups). The majority of the Hawaii based data sets required to perform these various functions have been identified and, when possible, converted into Google Earth format for the purpose of application process mock-ups. 

Usage Potential 

While the utility of Plantalytics is explicitly oriented towards productive landscapes, there is also considerable opportunity for use in the realm of conservation as a tool that would allow restoration ecologists and homeowners alike a means to rapidly determine site parameters and select native species tailored for the location. The scale of potential ramifications of increased successful out-planting of native species is considerable and extends beyond flora into fauna as patch size and continuity has impacts on animal life (Bender, Contreras, & Fahrig, 1998). In the case of Hawaii there has been developed an online native plant selection tool by the Oahu Board of Water Supply (http://www.hbws.org/cssweb/display.cfm?sid=1360) that while useful is not an application but solely lists of species by area (collated via rainfall regime and elevation) which is not a very finely grained analysis. While this is of some use for homeowners, in the case of applied ecology the immobility of the tool is a sticking point as field work is frequently an itinerant process. Other potential users are developers, architects and landscape architects seeking to streamline pre-occupancy species selection for new homes to capitalize on the burgeoning interest in edible landscaping and pseudo-agricultural residential developments (Bennet Group, 2012). Lastly the primary target audiences for Plantalytics are those involved with the establishment and management of production landscapes, namely gardeners, farmers, and those who facilitate their work such as university extension offices and conservation district managers. Plantalytics will provide a means by which rapid site analysis can be easily translated into design, to help those in the business of planting to reduce the time required for the planning that is critical to developing multi-hazard agro-ecosystems able to sustain production in the face of various disturbances. 

Conclusions

While the possibilities of Plantalytics remain vast, there remain gaps and barriers that will need to be addressed before further progress can be made. The primary gap is in the knowledge of how to design and integrate the myriad database sets into a cohesive application. The need for software architecture coding skills to produce a robust but slim operation protocol set parallels the need for an effective graphical user interface wherein users are able to intuitively navigate the considerable wealth of information that is proposed. Volunteer groups have been found who, in support of the proposed application, are will to do some of database populating from text based documents, such as is the case of the Permacopia books. This though has yet to happen due to knowledge gaps related to the type of database to be used and manner in which data types should be compiled. At current the primary barrier to closing these gaps is a funding source which would allow for the recruitment of qualified developers to code the multi-database communication series needed to accomplish the complexity of the proposed functions. Some potential public funding sources have been identified such as the Kaulunani Urban and Community Forestry Grant program funded by the Hawaii Department of Land and Natural Resources, the federally funded Small Business Innovation Research program, and the United States Department of Agriculture’s Specialty Crop Block Grants. Other opportunities, such as private funding via crowd-fundraising websites or private investors remain present but less feasible due to the desire for the application to be as accessible cost wise to the public as possible, and the admittedly small market share of users that preclude venture capital investment. 

Once these gaps and barriers have been addressed the potential for additional functionality extensions can be explored. Due to the value of a feedback loop in the species selection system the incorporation of a multi-user accessible (i.e. Wiki-type) plant database would allow for users to input their own data to modify, extend, and when needed curtail the species suggestions based on actual out-planting success. This is of importance as diversity of species is critical to the success of the multi-hazard agro-ecosystems and the application should support experimentation in the field as opposed to bounding and hence narrowing the species palette. For example if a user has coconuts (Cocos nucifera) growing successfully in an area outside of the predetermined site condition value set (e.g. elevation band) the multi-user access system would allow for the input of the that information so that other users can also trial the species in their location. Furthermore the integration of functionality to facilitate spatial arrangement design between species would meet the growing interest in the food forestry production style (Clark, & Nicholas, 2013) and permacultural approaches (Ferguson, & Lovell, 2014) which are increasingly recognized to have multifunctional outcomes from food security to ecosystem services.  In looking to the future, the relatively slow variable (in contrast to other hazards) of climate change is expected to produce large shifts in precipitation amounts and distribution (Lauer, Zhang, Elison-Timm, Wang, & Hamilton, 2013). Once completed the addition of a data set with the expected climate changes in decades to come will be a critical aspect to the longevity of multi-hazard agro-ecosystems, particularly those that are tree based. The forecasting of wet areas becoming wetter and dry areas becoming dryer (Zhang, Wang, Lauer, & Hamilton, 2012) necessitates the out-planting of species that are successful in today’s climate regime, those that will be successful in coming decades, and finally identifying the species which fit both characteristics. This last set of species is of greatest importance because after they are identified further research can be performed to analyze the potential shifts to agro-ecosystem productivity as crop opportunities narrow or change. This will enable and understanding of the the impact to human diets that can then be addressed and ameliorated through the discovery or horticultural development of species that meet the climate realities while providing for human needs.

The next step in the development of the Plantalytics application is the production of a software design document that will provide a further detailed blueprint for dataset interactivity and informational output characteristics. Once such a document has been produced the funding barriers will be easier to address and potential partnerships with some of the organizations interested in using Plantalytics can move forward. One bright opportunity for the design process to achieve financial parity with investment costs is to step back from the possibility of mass marketing the application in various regions (which will incur greater overhead to find location specific data sets) and instead to license the application architecture. This backbone architecture would be marketed to parties interested in working with their own developers to affix data sets from own specific regions to produce their own marketable application. In this way communities and organizations with an eye to the future who are interested in developing multi-hazard agro-ecosystems will be supported to translate their risks into resilience outcomes and economic returns while building multi-hazard resilient food security.  

References

Bender, D. J., Contreras, T. A., & Fahrig, L. (1998). Habitat loss and population decline: a meta-analysis of the patch size effect. Ecology, 79(2), 517–533.

Bennet Group. (2012, May 16). D.R. Horton – Schuler Division to Offer Urban Food Gardens at Kahiwelo at Makakilo. Kapolei News. Retrieved March 25, 2014, from http://kapolei.hawaiinewsnow.com/news/business/94097-dr-horton-schuler-division-offer-urban-food-gardens-kahiwelo-makakilo

Beyer, D.H. & Martin, F. W. (2006). Permacopia (Ninth Edition., Vols. 1-3). D. Hunter Beyer. Retrieved from https://books.google.com/books/about/Permacopia.html?id=-II2HAAACAAJ

Brown, R. (2010, September 27). Aiona: 10 Percent Increase In Locally Grown Food Will Generate $188 Million, Create 2,300 Jobs. Honolulu Civil Beat. Retrieved from http://www.civilbeat.com/fact_checks/2010/09/27/5005-aiona-10-percent-increase-in-locally-grown-food-will-generate-188-million-create-2300-jobs/

Campbell, K. L. I., Hodgson, N. H., & Gill, M. (1999). Livestock and Environment Toolbox. Livestock, Environment and Development (LEAD) Initiative. Food and Agriculture Organisation of the United Nations FAO. Rome.

Clark, K. H., & Nicholas, K. A. (2013). Introducing urban food forestry: a multifunctional approach to increase food security and provide ecosystem services. Landscape Ecology, 28(9), 1649–1669. doi:10.1007/s10980-013-9903-z

De Schutter, O. (2011). The World Trade Organization and the Post-Global Food Crisis Agenda: Putting Food Security First in the International Food System. Louvain-La-Neuve, Belgium, UN Special Rapporteur on the Right to Food.

FAO. (2007). EcoCrop. http://ecocrop.fao.org/ecocrop/srv/en/home

FAOSTAT Gateway. (2014). FAOSTAT Gateway. Retrieved April 15, 2014, from http://faostat3.fao.org/faostat-gateway/go/to/browse/Q/*/E

Ferguson, R. S., & Lovell, S. T. (2014). Permaculture for agroecology: design, movement, practice, and worldview. A review. Agronomy for Sustainable Development, 34(2), 251–274. doi:10.1007/s13593-013-0181-6

Giambelluca, T.W., Q. Chen, A.G. Frazier, J.P. Price, Y.-L. Chen, P.-S. Chu, J.K. Eischeid, and D.M. Delparte, 2013: Online Rainfall Atlas of Hawai‘i. Bull. Amer. Meteor. Soc. 94, 313-316, doi: 10.1175/BAMS-D-11-00228.1.

Harmon, A. (2014, January 4). A Lonely Quest for Facts on Genetically Modified Crops. The New York Times. Retrieved from www.nytimes.com/2014/01/05/us/on-hawaii-a-lonely-quest-for-facts-about-gmos.html

Hawaii Independent Staff. (2011). Hawaii’s path to a better food system: Where we’re at by the numbers. Retrieved April 15, 2014, from http://hawaiiindependent.net/story/hawaiis-path-to-a-better-food-system-where-were-at-by-the-numbers

Heaivilin, H. (2011). Community Agroforestry and Subsistence. Unpublished. https://docs.google.com/file/d/0BwMnB-Mth0zlVERkS2hoeFJkcFE/edit?usp=drive_web

Heaivilin, H (2013). Distributed Community Forestry for Multi-Hazard Food Security. Unpublished. https://docs.google.com/document/d/19m3DUizBD6fKEPzqXcwQbGRpXqOtfwYQFnNrGhrtiHE/edit

Janick, J., & Paull, R. E. (2008). The encyclopedia of fruits and nuts. CABI.

Kanu Hawaii. (2014). Kanu Hawaii’s Grow Local Challenge. Kanu Hawaii. Retrieved April 15, 2014, from www.kanuhawaii.org/growlocal/

The Kohala Center. (2014). Growing Organics: Moving Hawai“i”s Organic Industry Forward. The Kohala Center. Retrieved from www.kohalacenter.org/laulima/organic_group.html

Lauer, A., Zhang, C., Elison-Timm, O., Wang, Y., & Hamilton, K. (2013). Downscaling of Climate Change in the Hawaii Region Using CMIP5 Results: On the Choice of the Forcing Fields*. Journal of Climate, 26(24). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=08948755&AN=92672665&h=dh7npltNjSMq0QXuHe292ubWuyD3Tc66R8QJXMh79zXL3gIIK55y6138mAYwW6lFjwhs8qkfYyAjxewxRkMARA%3D%3D&crl=c

Leung, P., & Loke, M. (2008). Economic Impacts of Improving Hawaii’s Food Self-sufficiency. Economic Issues. Retrieved from http://scholarspace.manoa.hawaii.edu/handle/10125/12200

Messier, C., Puettmann, K. J., & Coates, K. D. (2013, February 11). Managing Forests as Complex Adaptive Systems: Building Resilience to the Challenge of Global Change. Routledge.

Mollison, B. (1988). Permaculture: A Designers’ Manual. Tagari Publications.

Morgan, K. (2010). Local and green, global and fair: The ethical foodscape and the politics of care. Environment and Planning. A, 42(8), 1852.

OmniTrak. (2011, December). Local Food Market Demand Study Executive Summary. Ulupono Initiative.

Pinstrup-Andersen, P. (2009). Food security: definition and measurement. Food Security, 1(1), 5–7.

Plasch Econ Pacific, LLC. (2011, February). O’ahu Agriculture: Situation, Outlook and Issues.        The Department of Planning and Permitting City and County of Honolulu.

Page, C., Bony, L., & Schewel, L. (2007). Island of Hawaii whole system project phase I report. Rocky Mountain Institute. Retrieved from http://sustainablemaui.org/wp-content/uploads/2012/05/BigIslandFoodSecurity.pdf

Pauku, R. (2006). Inocarpus fagifer (Tahitian chestnut), ver 2.1. Species profiles for Pacific Island agroforestry. Permanent Agriculture Resources (PAR), Holualoa. www.traditionaltree.org

Plants For A Future Foundation. (2014). Plants For A Future. www.pfaf.org/user/plantsearch.aspx

Simberloff, D., & Dayan, T. (1991). The guild concept and the structure of ecological communities. Annual Review of Ecology and Systematics, 22(1), 115–143.

Walker, B., & Salt, D. (2006, August 22). Resilience thinking: sustaining ecosystems and people in a changing world. Island Press.

Zhang, C., Wang, Y., Lauer, A., & Hamilton, K. (2012). Configuration and Evaluation of the WRF Model for the Study of Hawaiian Regional Climate. Monthly Weather Review, 140(10). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=00270644&AN=82113197&h=PeTqtDqxjj8lKrLf26ZPeJ4HIiUtnUg5rdppnL8pb7woCi5O7BQ4XJeVnBL%2BPc8oSifzFw82%2B1k%2FF1vBm7q4pQ%3D%3D&crl=c