Agriculture Reference
In-Depth Information
Researcher-proposed indicators were used in MCA to generate visual and
descriptive summaries of the trends in the indicator data. Two empirical measure-
ments were carried out on the same study sites and the same land-use units (LUUs)
within each study site, first in January-March 1999 and then in January-March
2000. The methods used for measuring the indicators are described in Chapter 6.
Data were managed using a relational database (Microsoft Access) and analyzed
using SAS (SAS Institute Inc., SAS Campus Drive, Cary, NC 27513).
Simple correspondence analysis (PROC CORRESP) was used to explore the
spatial trends in the indicator data. The analysis was based on a cross tabulation of
the study sites by each of the researcher-proposed LUU-level indicators. The analysis
and interpretation were based on the methods described by J. M. Greenacre (1993)
and M. Greenacre and Blasius (1994). Study site points that were close together were
considered as representing similarities along the respective dimensions, while those
that were further apart were considered as indicating differences along the plotted
dimensions.
For the temporal analysis, indicator measurements for the second round of mea-
surements were offered as supplementary points in MCA (Benzecri, 1992) of the
1999 data. The correlation between the coordinates of the main points and the supple-
mentary points was used to determine the presence of significant deviation of inertia
between the two measurements. Dimensions with the smaller Pearson's coefficients
were considered to have important temporal trends. The statistical significance of
these trends was assessed by testing the null hypothesis (1 −
r
) = 0, where
r
is the cor-
relation coefficient. Points that were further away from the main diagonal of a plot of
the main coordinates against the supplementary ones were considered to represent a
deviation in the inertia along that dimension over time. The further away the point, the
more significant the deviation. The significance of these deviations was assessed by
comparing the proportion of LUUs in the specific category during the first indicator
measurement to those in the same category in the second round of measurements.
7.2.2 e
v A l u A t i of in
of f
g
of A l s
, e
x p e C t A t i o n s
,
A n D
A
C h i e v e m e n t s
The objective was to explain, in a systemic way, the values, patterns, and trends in
indicators based on the perceived progress in community goals. Were the goals rea-
sonable given the available resources? Were the expected benefits reasonable given
the underlying social, economic, and biophysical processes? Given the changes
implemented, what would be the reasonable expectations over the short-, medium-,
and long-term time spans?
Progress toward community goals was evaluated using participatory methods.
Participants were asked to rank progress as negative, stagnant, slight, moderate, or a
lot. The ranking tools used were as described in Chapter 2. Evaluation of progress was
carried out in 1-day participatory workshops in January 1999 and in January 2000. The
changes in the system perceived to be driving this progression were also recorded.
Community expectations for each of these goals were assessed based on
pulse process models of their cognitive maps. The expected primary outputs were
those changes in system attributes that would be expected to be the direct result
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