Research Article |
Corresponding author: Ana Picanço ( analcp@gmail.com ) Academic editor: Peter May
© 2017 Ana Picanço, Artur Gil, François Rigal, Paulo A.V. Borges.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Picanço A, Gil A, Rigal F, Borges PAV (2017) Pollination services mapping and economic valuation from insect communities: a case study in the Azores (Terceira Island). Nature Conservation 18: 1-25. https://doi.org/10.3897/natureconservation.18.11523
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Insect pollinators provide vital ecosystem services through its maintenance of plant biological diversity and its role in food production. Indeed, adequate pollination services can increase the production and quality of fruit and vegetable crops. This service is currently challenged by land use intensification and expanding human population growth. Hence, this study aims: (1) to assess the pollination services in different land uses with different levels of disturbance through GIS mapping technique using insect pollinators abundance and richness as indicators, and (2) estimate the economic value of pollination by insects in agricultural crops. Our study takes place in a small oceanic island, Terceira (Azores, Portugal). Our results showed, remarkably, that not only the pristine vegetation areas, but also the orchards and agricultural areas have relatively high values of pollination services, even though both land uses have opposite disturbance levels. For the economic valuation, we analyzed 24 crops in the island and found that 18 depend on pollinators with one-third of these crops having 65% or 95% dependence on pollinators. The economic contribution of pollinators totals 36.2% of the total mean annual agricultural income of the dependent crops, highlighting the importance of insect pollinators in agricultural production and consequent economic gain productions.
Ecosystem service, GIS, pollination, insects, agriculture, economic value
Research at the interface of ecology and economics to characterize, value, and manage ecosystem services (henceforth ES) has supported a paradigm shift in how society thinks about biodiversity, ecosystems and human relationships to them (
The valuation and mapping of ES constitutes a continuous and very complex work for several national governments and organizations, and this process is only currently available for few countries (e.g. Portugal,
Pollination together with seed dispersal is considered as one of the key ES, classified by the Common International Classification of Ecosystem Services (CICES) coding system (
Besides these findings, there is also a general consensus that native pollinators abundance and richness are declining throughout the world (
The Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) from United Nations Environment Programme (UNEP;
These knowledge gaps unveil how the interactions between plants and insects are numerous and complex. So, the understanding of how plant-insect species’ interactions affect ecological functions and are affected by land management (
In this work, we assess the ES provision and values provided by insect pollinators in the Azores archipelagic region (Portugal) where few studies on ES assessment (e.g.
Terceira Island, with an area of approximately 402 km2 (length=29 km and width =17 km) is a small island of the central group of the Azores archipelago (Portugal), located in the North Atlantic Ocean (38°37'N, 38°48'N, 27°02'W, 27°23'W). Like the other islands of the archipelago, Terceira is of volcanic origin and the third oldest island after Santa Maria and São Miguel, with an age of about 3,52 million years (
Terceira climate is temperate oceanic, characterized by both high levels of relative atmospheric humidity and low temperature fluctuations throughout the year. Particularly, winter and autumn are marked by heavy and regular precipitations often associated with strong winds. The average annual precipitation exceed 3400 mm in “Serra de Santa Bárbara” summit, and reaches almost 1000 mm per year in all the island. The average annual temperature varies between 9°C in “Serra de Santa Bárbara”, to 17°C on the coast. Minimum temperature in the winter varies between 4°and 12°C while maximum temperature in the summer varies between 14°and 26°C (
The insects (Suppl. material
Digital Elevation Models (DEM) are a numerical representation of topography, made up of squared equal-sized grid cells (pixels) with an elevation value associated to each pixel. DEM constitute the most widely used data structure to store and analyze topographic information in GIS (
To complement this spatial analysis, we applied the formerly mentioned index of landscape disturbance metric based on the attributes of the landscape matrix (
For each analysis, we overlaid the respective pollination services’ interpolation maps delivered by the fieldwork data on bees and other insect pollinators from
Distribution of disturbance index (D) for bees’ and insect pollinators’ abundance (N) and richness (S) per classes.
Bees class | D | N | S | IP class | D | N | S |
---|---|---|---|---|---|---|---|
1 | D<20 | >10 | >2 | 1 | D<20 | >73 | >15 |
2 | D<20 | <10 | <2 | 2 | D<20 | 25<S<73 | 10<S<15 |
3 | 20<D<30 | >10 | >2 | 3 | D<20 | <25 | <10 |
4 | 20<D<30 | <10 | <2 | 4 | 20<D<30 | >73 | >15 |
5 | 30<D<40 | >10 | >2 | 5 | 20<D<30 | 25<S<73 | 10<S<15 |
6 | 30<D<40 | <10 | <2 | 6 | 20<D<30 | <25 | <10 |
7 | >40 | >10 | >2 | 7 | 30<D<40 | >73 | >15 |
8 | >40 | <10 | <2 | 8 | 30<D<40 | 25<S<73 | 10<S<15 |
9 | 30<D<40 | <25 | <10 | ||||
10 | >40 | >73 | >15 | ||||
11 | >40 | 25<S<73 | 10<S<15 | ||||
12 | >40 | <25 | <10 |
The disturbance level was organized in four classes, including a first one with very low disturbance level typical of high altitude native forests (D<20), two intermediate classes and finally a class with high levels of disturbance (D>40). The number of individuals of bees was divided in two classes in a logarithm scale (less than ten and more than ten individuals). The number of species of bees was divided in two classes with one species and two or more species. For insect pollinator abundance and richness three classes were prepared: for abundance, we created one for the rarest species, one for intermediate and one for the most abundant; for species richness we divided the classes arbitrarily in less than 10 species, 10 to 15 and more than 15 (see Table
Terceira Island’s main economic activity is agriculture, with the production of dairy products and raising livestock. Many small farmers practice subsistence agriculture or produce in small quantities to cooperatives. The island consumer is relatively similar to the southern Europe consumers, when comparing the GDP per capita of Azores region and Portugal to other countries of Europe (Suppl. material
FRUTER/Frutercoop is the “Association of Producers of Fruit, Vegetables and Flowers’ in Terceira Island”. Using their data from 2011 to 2015, we calculated the mean annual productions of 24 common fruits and vegetables in this island. Five-year means were used instead of the latest yearly production figures, in order to smooth out annual variations in crop output.
We estimated the value of pollination gain in agricultural crops and its respective vulnerability by using the crop production amount (
The IP dependency for each crop was categorized according to
By analyzing together both the land use map of Terceira Island (Fig.
Land use distribution map of Terceira Island with the selected sampling sites as black dots: NatFor (natural forests), SemiPast (semi-natural pastures), NatVeg (naturalized vegetation areas), ExoFor (exotic forests), IntPast (intensively managed pastures), urban areas and agriculture areas. Land use cartographic sources:
Pollination services’ interpolation maps: (upper left) bees abundance (N); (upper right) bees richness (S); (lower left) insect pollinators abundance (N); (lower right) insect pollinators richness (S).
In order to strengthen the previous analysis, we assessed the influence of the disturbance index (D), as calculated by
As a result of overlaying each previous pollination service output with the matching disturbance index D spatial data (see full description of classes in Table
Class | Total area (ha) | % of Terceira Island area |
1 | 225 | 0.56 |
2 | 1325 | 3.29 |
3 | 103 | 0.26 |
4 | 2367 | 5.89 |
5 | 1006 | 2.50 |
6 | 3342 | 8.31 |
7 | 14342 | 35.66 |
8 | 17376 | 43.20 |
TOTAL | 40086 | 99,67 |
Class | Total area (ha) | % of Terceira Island area |
---|---|---|
1 | 24 | 0.06 |
2 | 276 | 0.69 |
3 | 142 | 0.35 |
4 | 2071 | 5.15 |
5 | 1192 | 2.96 |
6 | 3674 | 9.13 |
7 | 13880 | 34.51 |
8 | 15787 | 39.25 |
TOTAL | 37046 | 92.11 |
Spatial assessment of insect pollinators’ abundance classes in Terceira Island area.
Class | Total area (ha) | % of Terceira Island area |
---|---|---|
1 | 154 | 0.38 |
2 | 753 | 1.87 |
3 | 255 | 0.63 |
4 | 100 | 0.25 |
5 | 1504 | 3.74 |
6 | 390 | 0.97 |
7 | 136 | 0.34 |
8 | 2510 | 6.24 |
9 | 977 | 2.43 |
10 | 1997 | 4.97 |
11 | 15776 | 39.22 |
12 | 12782 | 31.78 |
TOTAL | 37334 | 92.82 |
Spatial assessment of insect pollinators’ richness classes in Terceira Island.
Class | Total area (ha) | % of Terceira Island area |
---|---|---|
1 | 117 | 0.29 |
2 | 202 | 0.50 |
3 | 24 | 0.06 |
4 | 181 | 0.45 |
5 | 1055 | 2.62 |
6 | 320 | 0.80 |
7 | 101 | 0.25 |
8 | 1864 | 4.63 |
9 | 1065 | 2.65 |
10 | 2612 | 6.49 |
11 | 7922 | 19.70 |
12 | 8705 | 21.64 |
TOTAL | 24168 | 60.09 |
Classification maps of pollination services according to the influence of disturbance index (D): (upper left) bees abundance (N); (upper right) bees richness (S); (lower left) insect pollinators abundance (N); (lower right) insect pollinators richness (S).
According to the same Fig.
Moreover, both bees-related maps (abundance - N and richness - S) in Fig.
In the case of IP-related maps (Fig.
According to the data provided by Frutercoop for the period between 2011 and 2015, the total value of production for the 24 referred crops in Table
In terms of welfare, an assessment of the social cost to Terceira Island consumers resulting from pollinator decline estimated that the consumer surplus (economic measure of consumers benefit) loss was from €156K to €231K, which reflects the impact on the price of the crop on the market, based upon average price elasticities of −1.2 to −0.8, respectively (Table
Among the 18 crops relatively dependent to IP, the greatest economic value generated by the IP was originated by the class “little” or DR = 0.05, with 46.9% (€119,833), as well as the one originated by the class “great” or DR = 0.065, with 29.5% (€75,465) (Tables
On average, in recent years (2011-2015), IP contributed to pollination service in crop production with about €91,957 (total economic value of IP, EVIP), representing 10.5% crops ratio of vulnerability (VR) (Table
Array of crops used directly for human food following FAOSTAT and listed by common names of crops.
Crop common name | Crop species | Crop category following FAO | Dependence upon animal pollination | Dependence ratio (we consider only crops for which pollinators increase production of plant parts that we consume) | Producer price per metric kg | Production | Total value of crop (TVC) | Economic value of insect pollinators (EVIP) | Consumer surplus loss (CSL) with elasticity = | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Min | Max | Mean (DR) | ||||||||||
sources: FAOstat (http://faostat.org) | sources: |
Sources = FRUTER/Serv. Desenvol. Agrário Terceira | Price * Production | TVC*D | –0.8 | –1.2 | ||||||
€ / metric kg | metric kg | € | € | € | € | |||||||
Apples | Malus domestica | Fruits | Great | 0.4 | 0.9 | 0.65 | 1.50 | 40,424.70 | 60,738.11 | 39,479.77 | 70,952.49 | 57,515.02 |
Bananas | Musasapientum, M.cavendishii, M.nana, M.paradisiaca | Fruits | Increase – breeding | – | – | – | 1.00 | 405,642.60 | 405,642.60 | – | – | – |
Beans, green | Vigna spp., V.unguiculata, V.subterranean (syn. Voandzeiasubterranea), Phaseolus spp. | Vegetables | Little | 0 | 0.1 | 0.05 | 3.50 | 2,027.14 | 7,094.99 | 354.75 | 365.80 | 362.07 |
Cabbages and other brassicas | Brassicachinensis, B.oleracea | Vegetables | Increase – seed production | – | – | – | 1.29 | 46,541.44 | 60,038.46 | – | – | – |
Carrots and turnips | Daucus carota | Vegetables | Increase – seed production | – | – | – | 0.52 | 2,659.00 | 1,382.68 | – | – | – |
Chestnuts | Castanea sativa | Treenuts | Modest | 0.1 | 0.4 | 0.25 | 1.00 | 6,104.60 | 6,104.60 | 1,526.15 | 1,807.69 | 1,706.62 |
Chillies and peppers, green | Capsciumannuum, C.frutescens | Vegetables | Little | 0 | 0.1 | 0.05 | 1.27 | 989.93 | 1,252.27 | 62.61 | 64.56 | 63.90 |
Citrus fruit, nes | Citrusbergamia, C.medica (var.cedrata), C.myrtifolia, Fortunellajaponica | Fruits | Little | 0 | 0.1 | 0.05 | 1.99 | 12,790.40 | 25,452.90 | 1,272.64 | 1,312.28 | 1,298.89 |
Cucumbers and gherkins | Cucumis sativus | Vegetables | Great | 0.4 | 0.9 | 0.65 | 0.79 | 6,695.04 | 5,289.08 | 3,437.90 | 6,178.55 | 5,008.41 |
Figs | Ficus carica | Fruits | Modest | 0.1 | 0.4 | 0.25 | 10.00 | 1,098.22 | 10,982.20 | 2,745.55 | 3,252.04 | 3,070.21 |
Lemons and limes | Citrusaurantifolia, C.limetta, C.limon | Fruits | Little | 0 | 0.1 | 0.05 | 2.79 | 5,669.94 | 15,819.13 | 790.96 | 815.59 | 807.27 |
Lettuce and chicory | Lactucasativa, Cichoriumintybus, C.endivia | Vegetables | Increase – seed production | – | – | – | 4.06 | 36,104.51 | 146,584.31 | – | – | – |
Onions (inc. shallots), green | Alliumcepa, A.ascalonicum, A.fistulosum | Vegetables | Increase – seed production | – | – | – | 0.88 | 4,732.20 | 4,140.68 | – | – | – |
Oranges | Citrusaurantium, C.sinensis | Fruits | Little | 0 | 0.1 | 0.05 | 1.19 | 3,750.00 | 4,443.75 | 222.19 | 229.11 | 226.77 |
Other melons (inc.cantaloupes) | Cucumis melo | Vegetables | Essential | 0.9 | 1 | 0.95 | 2.99 | 6,327.10 | 18,918.03 | 17,972.13 | 77,617.29 | 42,633.64 |
Peaches and nestarines | Prunuspersica, Persicalaevis | Fruits | Great | 0.4 | 0.9 | 0.65 | 1.99 | 90.22 | 179.54 | 116.70 | 209.73 | 170.01 |
Pears | Pyrus communis | Fruits | Great | 0.4 | 0.9 | 0.65 | 1.50 | 463.10 | 694.65 | 451.52 | 811.47 | 657.79 |
Plums and sloes | Prunusdomestica, P.spinosa | Fruits | Great | 0.4 | 0.9 | 0.65 | 1.99 | 4,303.30 | 8,563.57 | 5,566.32 | 10,003.71 | 8,109.14 |
Pumpkins, squash and gourds | Cucurbitamaxima, C.mixta, C.moschata, C.pepo | Vegetables | Essential | 0.9 | 1 | 0.95 | 3.80 | 1,329.14 | 5,050.73 | 4,798.20 | 20,722.25 | 11,382.32 |
Strawberries | Fragaria spp. | Fruits | Modest | 0.1 | 0.4 | 0.25 | 3.89 | 3,064.24 | 11,919.89 | 2,979.97 | 3,529.71 | 3,332.35 |
Sweet potatoes | Ipomoea batatas | Roots and Tubers | Increase – breeding | – | – | – | 1.49 | 1,079.90 | 1,609.05 | – | – | – |
Tomatoes | Lycopersicon esculentum | Vegetables | Little | 0 | 0.1 | 0.05 | 2.64 | 24,889.46 | 65,770.40 | 3,288.52 | 3,390.94 | 3,356.34 |
Watermelons | Citrullus lanatus | Vegetables | Essential | 0.9 | 1 | 0.95 | 0.69 | 10,512.90 | 7,253.90 | 6,891.21 | 29,761.46 | 16,347.38 |
TOTAL OR MEAN | 0.28 | 0.52 | 0.40 | 2.29 | 27,273.44 | 874,925.51 | 91,957.09 | 231,024.67 | 156,048.13 |
Economic impact of insect pollination of the agricultural production used directly for human food and listed by the main categories.
Crop category following FAOSTAT | Average value per metric kg | Total value of crop (TVC) | Economic value of insect pollinators (EVIP) | Ratio of vulnerability (RV) | Consumer surplus loss (CSL) with elasticity equal to | |
---|---|---|---|---|---|---|
Price * Production | TVC*DR | EVIP/TVC | -0.8 | -1.2 | ||
€ / metric kg | € | € | € | € | ||
Fruits | 1.14 | 544,436.34 | 53,625.63 | 9.8% | 91,116.13 | 75,187.45 |
Roots and Tubers | 1.49 | 1,609.05 | 0.00 | 0.0% | 0.00 | 0.00 |
Treenuts | 1.00 | 6,104.60 | 1,526.15 | 25.0% | 1,807.69 | 1,706.62 |
Vegetables | 2.26 | 322,775.52 | 36,805.31 | 11.4% | 138,100.85 | 79,154.07 |
TOTAL | 874,925.51 | 91,957.09 | 10.5% | 231,024.67 | 156,048.13 |
Mean annual production values of crops with different pollinator dependency categories, for the period from 2011 to 2015.
Crop | Pollinator dependency class | Pollinators DR | Mean annual production (kg) |
---|---|---|---|
Beans, green; chillies and peppers, green; citrus fruit; lemons and limes; oranges; tomatoes | Little | 0.05 | 50,116.87 |
Chestnuts, figs; strawberries | Modest | 0.25 | 10,267.06 |
Apples; pears; peaches and nectarines; plums and sloes; cucumbers and gherkins | Great | 0.65 | 51,976.36 |
Pumpkins; squash and gourds; watermelons and other melons | Essential | 0.95 | 18,169.14 |
Bananas; cabbages and other brassicas; carrots and turnips; lettuce and chicory; onions (inc. shallots); sweet potatoes | Unknown | – | 496,759.65 |
Total | 627,289.08 |
Under the same thematic as “Deliverable 3a” from IPBES (
Based on the results obtained for low altitude agricultural areas, the disturbance index D variable, in contrast to other studies (e.g.
This study also highlights the fact that about one-third of Terceira Island crops have an essential or great dependence on pollinators, therefore complementing the above information on high values of insect pollinator abundance and richness in low altitude agro-ecosystems. The economic contribution of pollinators totalizes 36.2% (€170K) of the mean total annual agricultural income of the dependent crops (€469K). This EVIP percentage represents also the VR of agricultural production. Moreover, the consumer surplus loss was estimated between €156K and €231K based upon average price elasticities of −1.2 to −0.8 respectively. This interval of prices on the consumer surplus loss represents the difference between what island consumer are willing or able to pay for the ES relatively to its market price, in case of pollination services loss. These values referred to Frutercoop production only represents 54% of the island’s total crop productions (Tables
Our study also indicates the high socioeconomic relevance of pollination-related ES in a small oceanic islands’ context. Nevertheless, bio-economics based valuation studies have been inherently and generally unable to provide thorough and consistent results, due to frequent changes in currency values, labor costs and food prices. This type of approach has also failed to consider and propose realistic and cost-effective mitigation efforts that might reduce the impact of a pollination crisis. In general, the costs are still being strongly dependent on the local agro-ecological setting, namely the crops phenology, the local insect populations, and the existing ecological relationships between farmland and surrounding natural or semi-natural areas.
Some crops, despite their modest or little dependence, showed very high values of mean annual production and, therefore, even in these cases, the contribution of pollinators is significant (
As a result, these pollinator-dependent crops are crucial for maintaining the agricultural food balance of the increasing population-growth of Terceira Island’s consumers. Meanwhile, at the world scale, IP are becoming increasingly more vulnerable to (i) land-use intensification (
With the expected need for an increased production of vegetables and fruit in Terceira Island in the coming years, integrated mitigation measures (e.g. biological pest control, wild flowering plants production areas, promotion of organic farming), as well as (cost-) effective, innovative and attractive (for farmers) agri-environmental schemes are required in order to adequately promote pollination services and to compensate for some eventual crops’ failing production (e.g.
Agri-environmental schemes aiming to foster and to pay/compensate farmers for a more sustainable management of low-intensity pasture systems and to implement integrated farm management and organic agriculture practices should be especially encouraged in the north-western, eastern and south-eastern agro-ecosystem areas of Terceira Island.
Finally, this broad, straightforward and cost-effective methodological approach may be able to be applied in further small oceanic islands with the aim of improving the capacity of effectively assessing and monitoring pollination-related ecosystem services, in order to improve the existing decision support systems for land use planning/management policies, especially those related to agriculture and nature conservation.
We would like to thank the reviewers Nicolai Gallai and Natacha Chacoff for their useful comments on the manuscript. AP was supported by a Ph.D. grant from Direção Regional da Ciência e Tecnologia dos Açores (M3.1.2/F/031/2011). FR was supported by the Post-Doc Grant FCT – PTDC/BIA-BIC/119255/2010 and AG was supported by the Post-Doc Grant FCT – SFRH/BPD/100017/2014, funded by the National Budget of the Ministry of Education and Science of Portugal and by the European Social Fund. PB and AG were partly financed by the Project CSA-SEP-210140185-ESMERALDA. We would like also to acknowledge FRUTER/Frutercoop and Serviço de Desenvolvimento Agrário da Ilha Terceira for giving information related to crop production.
Supporting information
Data type: methods
Explanation note: Description of the landscape disturbance index methodological approach according to