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T-Space at The University of Toronto Libraries >
P. E. Hallett (2011) Farmed Solitary Bees & Wasps, Data Set (generations 1997-2008) >
01.0 Introduction >

01.01 Motivation

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As a young father in the 1960s I could not help being aware of scientific predictions that civilization might begin to collapse as soon as the 1990s because of increasing starvation due to the world’s growing population. The “Green Revolution” averted this disaster at the cost of converting much of the world’s unexploited “wastelands” to agricultural and forest monocultures, expending huge amounts of energy and fuel on mechanical farming and fertiliser synthesis in the process.

Later, as a new grandfather, spurred by a survey of human domination of the planet (Vitousek et al., 1997), and alert to how few insects have been successfully exploited (e.g., Buchman & Nabhan, 1996), I resolved to use my entomological background and retirement to develop methods for mixed culturing of local solitary bees and wasps. These beneficial insects amount to many species, which are adapted to most environments, some occurring in the inner cities, and represent an enormous untapped renewable resource for farming and environmental restoration. From 1997-2001 I developed and tested a farming method, expanded the amount of fielded equipment and kept records of annual productivity (Hallett, 2001a-d) ---only to realise that successful commercial exploitation would require more vigorous promoters than myself, and the foreseeable consequences would very likely be much what I was anxious to avoid (overharvesting, transportation of non-local species, monocultures, and propagation of parasites and pathogens).

Accordingly in 2001 I embarked on more elaborate data collection with a view to encouraging research on the farming of local solitary bees and wasps by entomologists and ecologists ---by providing data, equipment, and livestock. After 2003 the increase in the farmed populations was overwhelming, and the time required for detailed recording burdensome. By 2007-8 I was obliged to reduce the effort.

This rather personal history helps explain the nature of the present database. All records and totals are censuses, not samples, so there are no measurement error bars; any one who worries that the Data Set is just a single instance of the many possible ways in which such populations can grow in such equipment at such localities can resort to computational resampling methods. Records for the development phase of 1997-2001 were simple totals of annual production and harvests. In order to record 4000 nest cavities per year a special coding system was developed during 2001-3. This was at first a nest-by-nest census of the later immature stages and emergence, i.e., count vectors of nest development stages over space. For annual generations 2004-8, field records were expanded to cover all stages of nest development and the likely causes of loss at each stage. For 2005-8, dates for nesting events were added.

The number of fielded nest cavities was reduced in 2007 and to zero by 2009. The 25,000 field records are coded as character strings rather than English text but are easily read given the documentation and worked examples (see 04.0 Data coding). In 2009 I wrote Python code to expand the field codes for each nest cavity (row) in a given generation, location and nest box platform (spreadsheet) into many columns of simple counts or descriptions suitable for direct analysis, e.g., by spreadsheet count and countif formulae, PostgreSQL data basing or the R statistical language. The Data Set's SOURCE spreadsheets are to be found in subdirectories within the major directory 11.0 RECORD SOURCES and SUMMARY analyses. A summary of just one aspect of the SOURCE spreadsheets is provided in the file SUMMARY OF NEST COUNTS BY FATE. Probably almost all errors in the SOURCE sheets have been caught by direct visual inspection, during Python program development and testing or by spreadsheet analyses for a variety of talks to the Entomological Society of Ontario (ESO). Errors that arose in the field when writing the dense codes have nearly all been corrected without estimation because of the redundancy in the field code. Missing counts are coded by Q in field record column W of the SOURCE sheets and interpolated or extrapolated prior to multicolumn expansion in column X. Other types of data are in the main directories 05.0 Ancilliary data, 07.0 Manuscripts&analyses, 08.0 Communications ,and 06B Documentary photos.

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