Global land use of diets in a small island community: a case study of Palau in the Pacific

The target community was Ollei Village in Ngarchelong State, located at the northern end of Babeldaob Island in the Republic of Palau. Palau is an island country in the western Pacific Ocean with a rich natural environment. The country comprises approximately 340 islands, including Babeldaob Island, the largest, and Koror, the economic center. The population of Palau was 17 661 in 2016 [29], and there are no major food-related industries. The GDP values for agriculture/forestry and fishing were 2.2 and 3.9 million USD in 2015, respectively, accounting for 1% and 2% of the total GDP, respectively; these activities are much smaller than the import of food/beverages, which amounted to 40.7 million USD in 2015 [29]. Ollei Village is a rural community 65 km away from Koror; it comprises 21 households and 86 residents (figure 1). Traditionally, the diets of these residents have been based on self-sufficiency and the sharing food, such as taro and fish [30]. A fishing port is located at the west end of the village and most local seafood consumed in the village arrives through this port. Several well-maintained traditional croplands, known as mesei, are located along the river and coast, where the traditional staple food (taro) is planted [30]. Three local stores sell commodities purchased from Koror.

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We stayed in the village from 24–30 September 2015 and distributed a food frequency questionnaire (table S1 (available online at stacks.iop.org/ERL/16/065016/mmedia)) to all households. This questionnaire included the following questions: (a) 'which meal was eaten?', (b) 'which ingredients were used?', (c) 'how and where was each ingredient obtained (purchased, locally shared or through subsistence)?' and (d) 'how many family members did the meal serve?'. We visited all the households, recalled the questionnaire in person daily, and asked the participants to fill out the form directly if anything was unclear. In addition, we distributed a camera to each household to record and identify all meals. This survey was conducted in accordance with the research guidelines of the Japan Sociological Society Code and the ethical policy of Nagoya University. The state governor and all subjects provided consent prior to participating in the anonymous dietary survey.

We calculated the quantity of consumed ingredients based on the average per capita consumption of ingredients in each dish, the number of dishes and family members. The types of dishes were identified from the names and photos of dishes provided in the survey. The average number of ingredients per capita in dishes was estimated by referring to typical (standardized) local recipes that were provided by local residents. We adopted similar recipes in other Pacific Islands, Japan and the United States (USA) if the local recipe was unavailable; this was because the culinary practices in Palau were strongly affected by these recipes. For grains, such as rice and taro, we estimated the average per capita consumption of each grain based on the average caloric consumption of grain (650 kcal⁻¹ capita⁻¹ d⁻¹) in Palau [31]. The condiments were not considered in the calculation because their small percentage varied among individuals and families. Imported foods were identified among purchased ingredients, based on the food production and import situation in Palau. Specifically, purchased fish, pounded taro, tapioca and certain vegetables, such as cucumbers, aubergines and spinach, were considered to have been domestically produced. Other foods, primarily consisting of grains, meat, eggs and dairy products were regarded to have been imported (see table S2 in the supplementary material). When necessary, we confirmed the production of each ingredient by consulting local residents and researchers.

To reveal the link between local food consumption and external land use, we adopted globally normalized land-use areas, measured in global hectares (gha), as an indicator of agricultural land appropriated as a resource. The gha was used for the National Footprint Accounts [32] to represent the amount of land (in ha) required to produce agricultural products under the world average yield of each product. Land-use areas associated with the annual consumption of imported food in Ollei Village were determined by food category, trading partner, land user and land category. A trading partner is a country/region that directly exports primary or processed food products to Palau. By contrast, a land user represents a country/region from where agricultural land is appropriated to cultivate primary products. These are either directly exported to Palau or used as raw materials for food products (including livestock feed) that are exported to Palau in the global supply chain. A country/region that cultivates primary products and exports primary or processed food products to Palau can be both a land user and trade partner (see figure S1 in the supplementary material for a schematic of the trading relationship among land users, trading partners, Palau and Ollei Village).

Land-use areas in land-user country/region $i$ (gha) associated with the annual import of product $k{^{^{\prime}}}$ (USD) from the country/region (trading partner) $j$ to Palau, $L_{ij}^{Pl}\left( {k{^{^{\prime}}}} \right)$, were determined using equation (1) where $l$ is the land category. Global land-use areas were calculated by multiplying the import values for each food category (USD) by the land footprint intensities (gha USD⁻¹) of the trading partners. Subsequently, land-use areas (gha) associated with the annual consumption of imported foods in Ollei Village, $L_{ij}^{Ol}\left( k \right),$ were determined using equation (2),

$$\begin{align}L_{ij}^{Pl}\left( {k{^{^{\prime}}}} \right) = \sum\limits_{{k^*}} Q_{ij}^l\left( {{k^*}} \right) \cdot \frac{1}{{1 + {T_j}\left( {{k^*}} \right)}} \cdot {C_{{k^*}k{^{^{\prime}}}}} \cdot {M_j}\left( {k{^{^{\prime}}}} \right). \end{align} \tag{ 1 }$$

$$\begin{align}L_{ij}^{Ol}\left( k \right) = \mathop \sum \limits_{k{^{^{\prime}}}} \frac{{L_{ij}^{Pl}\left( {k{^{^{\prime}}}} \right)}}{{\tilde M\left( {k{^{^{\prime}}}} \right)}} \cdot {C_{k{^{^{\prime}}}k}} \cdot X\left( k \right),\end{align} \tag{ 2 }$$

where ${M_j}\left( {k{^{^{\prime}}}} \right)$ is the annual import value (USD) of product $k{^{^{\prime}}}$ from country/region $j$ to Palau; and $\tilde M\left( {k{^{^{\prime}}}} \right)$ is the annual import quantity (kg) of product $k{^{^{\prime}}}$. $X\left( k \right)$ is the annual equivalent quantity of the weekly consumption of imported food $k$ in Ollei Village (kg). $Q_{ij}^l\left( {{k^*}} \right)$ represents the land footprint intensity of land category $l$ in the land-user country/region $i$ (gha USD⁻¹) associated with the production in sector ${k^*}$ in the country/region (trading partner) $j$. $Q_{ij}^l\left( {{k^*}} \right)$ describes the linkage through trade between countries/regions $j$ that produce (and partly export) food products and the countries/regions $i$ where agricultural land is appropriated to produce primary products, including food and feed crops used as raw materials for food products. ${T_j}\left( {{k^*}} \right)$ indicates the trade margin rate of imports from countries/regions $j$. Product category $k{^{^{\prime}}}$ corresponds to the four-digit harmonized commodity description and coding system (HS) code, and $k$ denotes the food category adopted in the field survey. The land footprint intensities were linked to the four-digit HS codes using the binary variable, ${C_{{k^*}k{^{^{\prime}}}}}$. This variable allows the conversion of the sector in the land footprint database ${k^*}$ into product category $k{^{^{\prime}}}$. Similarly, we linked each imported food to a single four-digit HS code using the binary variable, ${C_{k{^{^{\prime}}}k}}$, which coordinates the food category $k$ with the corresponding product category $k{^{^{\prime}}}$.

In equation (1), global land-use areas were calculated by multiplying the import values for each food category (USD) by the land footprint intensities (gha USD⁻¹) of the trading partners. Equations (1) and (2) assume that the breakdown of trading partners ($j$) of Palauan food imports in each food category ($k{^{^{\prime}}}$) was reflected in the imported food consumption in Ollei Village. The survey results confirm that households in Ollei Village purchased food from the economic capital, Koror, partially through local stores.

We used the annual equivalent quantity of the weekly consumption of imported foods obtained from the survey in Ollei Village $X\left( k \right)$. For ${M_j}\left( {k{^{^{\prime}}}} \right)$ and $\tilde M\left( {k{^{^{\prime}}}} \right)$, the annual values and quantities in 2015 were obtained from the International Trade Centre (ITC) Trade Map [33]. We used land footprint intensities provided by the Eora database (as of 2012) for $Q_{ij}^l\left( {{k^*}} \right)$. The largest multi-region input-output (MRIO) table in the world consists of 14 839 industrial sectors that trade within and among 190 countries/regions [34, 35]. Based on the Leontief inverse matrix calculated from the MRIO table, Lenzen et al [34, 35] analyzed the environmental emissions and resource consumption directly and indirectly induced by the production in each of the 14 839 sectors. This included agricultural land use directly and indirectly induced in the 190 countries/regions through trade, including domestic and international transactions. We cited cropland and grazing land areas (gha) appropriated in countries/regions $i$ induced by 1 USD of production in sector ${k^*}$ in country/region $j$, and used them for $Q_{ij}^l\left( {{k^*}} \right)$. The food-related sectors in some Palauan trading partners in the Eora database were coarse; therefore, some of the imported foods linked to broadly classified sectors, such as 'other food products,' were sources of uncertainty. This database includes land footprint intensities as components of the ecological footprint of the five land categories (cropland, grazing land, fishing grounds, built-up land and forest land), according to the National Footprint Accounts [32]. This paper presents the results for agricultural land use, including cropland and grazing land, which accounts for approximately 76% and 83% of the total global land use associated with food imports to Palau and Ollei Village in 2015, respectively. Based on critical debate [36], we excluded land used for carbon dioxide (CO₂) sequestration. Examples of how global land-use areas were calculated are presented in tables S3 and S4 in the supplementary material. Trade flows between Ollei, Palau, trading partners and land users were illustrated on a world map using ArcGIS. Trade flows were also illustrated in a Sankey diagram using the web-based software, 'Sankey diagrams from Excel' (http://ramblings.mcpher.com; currently unavailable). All calculations were conducted using Microsoft Excel.

We calculated the biocapacity of agricultural land in Ollei Village (${B^{\text{O}}}$) using equation (3), according to the formula for the country-level biocapacity in the National Footprint Accounts [32]. Biocapacity is a measure of the biologically productive land area available to provide ecosystem services in gha. As such, it is comparable to land-use areas demanded for food consumption in Ollei Village and Palau.

$$\begin{align}{B^{\text{O}}} = {A_{Wk}} \cdot {\text{EQF}} = {A_{Nk}} \cdot \frac{{{Y_{Nk}}}}{{{Y_{Wk}}}} \cdot {\text{EQF}}{\text{.}}\end{align} \tag{ 3 }$$

First, we divided the agricultural land areas in Ollei Village measured by a field survey in 2014 (taro patch, 1.16 ha; home garden, 1.73 ha; and farmland, 1.30 ha) into bio-productive areas used to produce each product ($k$), ${A_{Nk}}$; this was based on the current production share of Palau cropland. Then, ${A_{Nk}}$ was converted into the equivalent area of world-average cropland yielding each product ($k$), ${A_{Wk}}$, by multiplying the ratio of the yield in Micronesia (${Y_{Nk}}$) to the world yield (${Y_{Wk}}$) available in the ProdSTAT database provided by the Food and Agriculture Organization [37]. The cropland equivalence factor, ${\text{EQF}} = 2.52$ [26], was multiplied by the agricultural land area in Ollei Village to determine the agricultural land biocapacity. Similarly, we determined the biocapacity of agricultural land in Palau, ${B^{\text{P}}}$, based on the cropland areas surveyed in 2011 (agroforestry, including taro patches and home gardens, 1,570 ha; and farmland, 317 ha).

Weekly diets were compiled from 724 ingredients in the 208 meals consumed by 38 people in the 11 households of Ollei Village during the survey period. The results of the survey (figure 2 and table S2) show that local residents largely depend on grains (e.g. rice, bread, ramen, pasta) and meat (e.g. beef, pork, chicken) more than traditional taro and fish-based diets. However, traditional foods, such as bats (upper middle picture in figure 3) and bird meat were still consumed by some villagers (figure 2). Subsistence foods from the ocean and agricultural products, such as taros and fruits, have contributed to self-sufficiency in Ollei Village. However, nearly 100% of the animal-husbandry products (meat, eggs and dairy) and grains were imported from other countries and obtained by purchase; Palau has no large livestock industry. The survey revealed that dietary habits in Ollei have shifted towards an imported food-oriented lifestyle dependent on the global supply chain; this is despite Ollei being a small and remote island community.

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The estimated global agricultural land-use area associated with the annual equivalent consumption of imported foods in Ollei Village reached 10.9 gha (0.29 gha capita⁻¹). This area is 37% larger than the biocapacity of agricultural land in Ollei Village, which is estimated at 7.94 gha (figure 4(a) and table S2). By contrast, the global agricultural land-use area associated with the annual Palauan food imports was 14 508 gha (0.82 gha capita⁻¹) in 2015. This was four times larger than the biocapacity of the agricultural land in Palau, estimated at 3663 gha (figure 4(b)). This difference in global agricultural land-use area between Ollei Village and the country of Palau can be considered as traditional diets based on ingredients from traditional croplands and inshore fishing remain in Ollei Village and all imported and processed foods consumed in Ollei Village were transported through Koror, resulting in high transportation and purchasing costs.

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For Ollei and Palau, most global agricultural land-use areas were occupied by meat and grain products; the USA accounted for the largest share in cropland and grazing land (pie charts in figures 4(a) and (b)). The large difference in the share of Australia between grazing land and cropland use is explained by the large import value of processed meat products from the country. Similarly, the comparably large share of Thailand's cropland use is associated with the second largest import value of rice, following the USA.

Trade flows and consequent agricultural land-use areas associated with imported food consumption in Ollei Village (figure 5) indicate that the rural village is strongly connected to countries worldwide, particularly to the USA, Australia and Asian countries. In addition to direct trading partners, the analysis highlighted the countries where agricultural land use was induced by imported food consumption in Ollei through the global food supply chain (land users in figure 5). For instance, Japan accounted for 23% of the Palauan import value of bakery products and noodles in 2015 (figure 6). However, Japan used little domestic cropland to produce grains as raw materials and used foreign land through the import of grains from major agricultural countries, such as Australia and the USA.

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