The PHYGROW model forms one the foundation models for the IMPACT
assessment process as it concerns assessing dynamics of forage, animals and
management decision making on grazinglands. The primary use of the model is to
reflect complex landscapes characterized by modal plant communities comprise of
many species that are grazed by complex, dynamic herbivore populations. A
destock/restock rulebase establishes attitude toward risk by establishing
multiple decision points with varying levels of stocking adjustments and
increments reacting to dynamic weather events over multiple years. The PERL
scripting language is used to generate time-lagged animal responses (numbers,
weaning weights, milk yield, offspring crop) responsive to weather-induced
forage value indices which is linked to the FLIPSIM farm level simulation model
to better represent stocastic responses for assessment of farm survival relative
to baseline and technology induced responses. PHYGROW will also play a major
role in assessing potential forage-based yields for modal farms in regions where
current modal farms do not exist but environmental conditions can be identified.
This function is critical to the IMPACT regional analysis to support both
FLIPSIMS and ASM analyses. Currently, PHYGROW is being used in the following
projects:
- Assessment of potential water values resulting from brush control in the
Frio River basin for the City of Corpus Chisti using a combination of
PHYGROW, SWAT, ECON investment analysis, and WATERVAL models.
- Integrating biophysical and economic models for assessing regional
impacts of changes in grazingland ecosystems in the Edwards Plateau of
Texas due to changes in farm policy relative to production of sheep and
goats. PHYGROW and FLIPSIM are the principle models used in this program…see
attached brief.
- Assessing threshold levels of mesquite invasion in the coastal prairies
of Texas for optimal investment in land practices using a combination of
PHYGROW and a new probabilistic distribution analysis and investment
analyses.
- Assessing optimum brush management strategies for the Rolling Plains of
Texas of varying ages of invasion by mesquite and juniper. PHYGROW and
GAAT (grazinglands application analysis tool).
- Combinations of cattle, meat goats and white-tailed deer for optimum
biological and economic efficiency in response to stocastic weather and
market events in the sub-tropics of Texas. PHYGROW and FLIPSIM linked with
PERL scripting language are the primary tools used in this analysis.
- Development of an early warning system for pastorialists in East Africa.
PHYGROW and NUTBAL (nutritional balance analyzer)… see attached brief.
Model Description: PHYGROW is a multi-species plant growth/runoff modeling
system used to predict forage production and herbivore grazing. The model
simulates the growth of complex forage resources and grazing by multiple
species of animals. The model is sensitive to animal selectivity of plant
species, and translates these processes into animal production in terms of
stocking rates. The model is written in C++ using object-oriented
design/programming, and therefore, is well suited to link efficiently to the
other models, thus allowing grazingland ecosystem components to be accounted
for during impact analysis. An expanded explanation of the modeling
environment and a discussion of the key subcomponents of the model can be
found on the internet at http://cnrit.tamu.edu/rsg/phygrow.
Integrating Biophysical and Economic Models for Assessing
Regional Impacts of Changes on Grazingland Ecosystem
A methodology to integrate biophysical process and economic models at the
regional scale is developed and its usefulness in assessing impacts of
institutional, environmental and/or technological changes on range-based
ranching enterprises is demonstrated by applying the model to the Edwards
Plateau region of Texas.
A methodology for constructing representative ranch firms including
financial status, plant communities and livestock production practices was
developed to parameterize, for the Edwards Plateau region, the biophysical
model (PHYGROW) and economic model (FLIPSIM). Although the models were
parameterized for the Edwards Plateau region the methodology is general enough
to be applicable in other regions with the appropriate data.
Integration of the forage growth simulation model (PHYGROW) and the
firm-level economic performance simulation model (FLIPSIM) was accomplished as
follows. Local soil and plant community characteristics along with local
climatic conditions are used in PHYGROW to obtain daily and annual forage
production simulations. These results from PHYGROW, along with animal
performance variables (calf weaning weight and calving percentage, etc.) and
economic variables (cost of production, financial conditions of the ranch,
etc.) are used as input in FLIPSIM which, in turn, produces ranch performance
indicators such as cash flow, net present value, returns to equity, etc. as
output for each year in a specified planning horizon.
Productivity of land (and the agricultural firms that use it) is not the
same throughout a region due to the differences in financial, technological,
climatic or soil characteristics. To capture the heterogeneity of the region
the Edwards Plateau was divided into four ecological/economic zones based on
soil, climate and economic characteristics. One representative ranch from
Crockett, Sutton, San Saba and Kendall Counties each represented a unique
ecological/economic zone. The baseline financial and livestock production
practices for input in PHYGROW and FLIPSIM for the representative ranches was
developed using interview data from focus groups of local ranchers in each
zone. To obtain regional estimates, results from the representative ranches
are aggregated according to the proportion of the zone it represents and, in
turn, the zones are aggregated to represent the entire region.
The integrated model is used to assess the impacts of a cost-share program
to reduce brush canopy in the Edwards Plateau region. Scenarios are developed
for various levels of brush removal (50%, 75%, etc.) by adjusting the
plant communities in PHYGROW to reflect such changes for each representative
ranch. The rancher’s share of brush control cost is incorporated into the
model by way of increased production cost in FLIPSIM. The model is rerun using
these revised inputs and the result compared to the baseline result. This will
provide an estimate of net economic benefits to the ranchers of varying
degrees of brush control and can contribute to a more complete cost-benefit
analysis of brush removal in the Edwards Plateau.
Development of a Web-based Common Modeling Environment
A primary problem facing policy analysts in today’s decision environment
is the need to use a wide variety of economic, sociological, biophysical and
environmental models in some coordinated manner that allows a rational
sequence of analyses to represent the complexity facing the decision maker.
Models represent a long-term investment by their developers to properly
representing complex relationships in an evolutionary process of verification,
upgrading knowledge and validation cycling as new technologies allow
enhancements throughout the development profile. Model developers are
reluctant to change their finely tuned models to accommodate a broader set of
analysis, thereby creating problems of data sharing and transfer between model
input/output. To address this concern, a web-based common modeling environment
is being developed to allow a variety of models to be presented to uses in a
cohesive manner.
An alpha version of the common modeling environment is to be presented on
September 15, 1998 which allows selection of two models, PHYGROW and APEX in a
JAVA-based interface via the web and run a variety of complex scenarios. A
model server parser and model input/output SQL parser has been developed to
allow models to keep their models intact and linked to a import/export
specification table which allows data entry, data output graphing and data
exchange over the web. Once the alpha version of the system is tested, more
models will be added to the system and greater analytical capacity expanded in
the SQL parser logic for input and output data.
The ultimate goal is to package a series or suite of models such a ASM,
FLIPSIM, PHYGROW, SWAT, APEX and NUTBAL into a unified environment which
contains a matrix of mission-critical data files that could support policy
makers exploration of alternatives and emerging technology options. Supporting
databases would be populated in advance to minimize data acquisition,
organization and reconciliation, minimizing model set up time and maximizing
analytical output.
