POLLINATORS POLLINATION AND FOOD PRODUCTION

THE ASSESSMENT REPORT ON POLLINATORS, POLLINATION AND FOOD PRODUCTION
232
4. ECONOMIC VALUATION OF POLLINATOR GAINS
AND LOSSES
3.2.2.4 Availability of long-term data sets
Good estimates of pollination value to consumer and
producer welfare depend on the availability of several
biological and economic data (see Section 2.4.). These
databases are seldom consistent for long periods. There
is also a strong interaction between temporal and spatial
scales at this case, with better temporal resolution (i.e.,
data collected at shorter time intervals) at medium scales
(national). Geographic bias is strong, with great variation
in the availability of long-term national and sub-national
data between countries (Lautenbach et al., 2012). At the
global and national scales, most estimates used crop
production, cultivated area, prices and beehive number,
among others, provided by the Food and Agriculture
Organization (FAO) of the United Nations over the last five
decades (e.g., FAOSTAT, 2007; http://www.fao.org). For
some variables, data is not available for all consecutive
years for all countries, demanding statistical procedures
to estimate values for specific periods (Leonhardt et al.,
2013) or assuming that introduced biases are consistent
in time and space (Lautenbach et al., 2012). At the subnational
level (i.e., within-country variations), the level of
detail on data collection and availability in FAO databases
differs substantially among countries. For example, the USA
provides spatially structured data on yield whereas Germany
reports yield data in highly aggregated formats (Lautenbach
et al., 2012). In addition, FAO data on production prices are
subdivided in two datasets, from 1966 to 1990 and from
1991-2009, which are not directly comparable (Leonhardt et
al., 2013).
Long-term biological data is also difficult to obtain, since it
involves many different species of pollinators and variables
that are prone to temporal and spatial variations. Usually,
variables such as the amount of pollen deposited by each
pollinator species and the fraction of flowers each of them
fully pollinate are quantified without temporal replicates. In
a recent review, Melathopoulos et al. (2015) indicated the
high level of uncertainty about the pollination dependency
coefficients for the 10 crops with the highest aggregate
benefits of pollination services. Such biological data are not
available in public databases aggregating multiple countries
or regions but are usually scattered on published documents
regarding each specific crop at local scale (see Bommarco
et al., 2012). In a recent review, Vanbergen et al. (2012)
presented a list of major gaps in knowledge and research
priorities to demonstrate how pollination functions differ
across species and crops. Many of their recommendations
include obtaining temporally replicated biological data that
are important for valuation, with systematic monitoring
of pollinator diversity, abundance and efficiency. This is
especially necessary for those crop types with very limited
knowledge and high economic importance. A summary of
the most important data limitations and needs for valuing
pollination services at different scales is given in Table 4.6
(see also: Sections 2 and 5.3).
3.2.3 Tools
3.2.3.1 Time series analysis
TABLE 4.6
Main data needs for more precise economic valuation of pollination services across scales
Excludable
The term “time series” is generally used to refer to a
non-random temporal sequence of values of a variable,
ordered at successive and regular time intervals (Tsay, 2002;
Montgomery et al., 2008). Time series analysis implies that
Non excludable
Local/national Non-market or non-monetary food consumption - Production for own consumption or direct trade for goods
and services;
- Harvesting of wild fruits and honey
Local/national Production and consumption in the secondary market - Quantity and sale prices on the secondary markets
Local/national Price responses to changes in supply of particular crops - Information on consumer preferences;
- Crop substitution elasticities.
Local/national Management of pollinators - Number of beekeepers and beehives for own production
and rental;
- Type and extension of crops that use managed pollinators
Local/national Seasonal variations in production and prices - Intra-annual data on production and prices
National/global
Standardized databases (National- among regions/
states/provinces; Global – among countries)
- Standard procedures for data collection (i.e., minimum
crop area considered for inclusion, area/volume units,
cultivars)
National/global Distortion in market prices due to taxes or subsidies - Official information on subsidies and taxes
Local/national/global
Local/national/global
Precise estimation of pollinator dependency is not
available for several crops
Decrease in agricultural value in the case of
pollination failure
- Pollination biology for different crops and cultivars
replicated through time and space
- Frequency of different types of decisions of farmers and
consumers responding to changes in supply
Local/national/global Pollination impacts on fruit quality - Quantification pollination effects on fruit visual
appearance, palatability or nutritional composition