Production Index (API) Model
Empirical basis and model assumptions:
The ATLSS American Alligator Production Index (API) Model was developed as a coarse indicator of the yearly production potential (probability of producing nests and offspring successfully) for the American Alligator in South Florida, based upon local habitat and hydrologic conditions. The API model addresses only the effects of relative local habitat quality and hydrological dynamics on production. Consequently, this model should not be interpreted as providing estimates of population dynamics or viability.
Spatial Constraints. - The spatial resolution for the model is 500x500 meters. Historical observations suggest that this roughly corresponds to the home-range of nesting female alligators, so it is a useful scale of resolution. All data (water depth, vegetation type, ground elevation, breeding indices) represent values for a 500x500 meter area.
Temporal Constraints. - The temporal resolution for the model is one day for all water data (height and depth) and is static for the vegetation habitat types. The model produces a single yearly value for each spatial cell that takes account of the daily water data affecting the nesting and offspring production during that year.
Breeding. - Water levels encountered during the period ranging from May 16 of the current nesting year to April 15 of the previous year are used as an indicator of the probability of breeding occurrence in an area. The probability that nesting will occur correlates positively with the amount of time spent in flooded conditions during this period. This model component is defined to be the proportion of this period for which there was water depth greater than 0.5 feet. Biologists at ARM Loxahatchee NWR have suggested that a static value of 1.0 for this model component is appropriate for WCA 1.
Nest Construction. - The mean water depth during the peak of the mating season from April 16 through May 15 is used as an indicator of the probability that mating and nest construction will occur in a given area. Two linear functions are applied to define the value of this model component such that the highest probability of nest construction occurs at a mean level of 1.3 feet. Mean water depth values higher or lower than this reduce the probability of nest construction.
Nest Flooding. - The probability of a nest being flooding is calculated from a combination of the mean water level during nest construction and the maximum water level during egg incubation. Field observations indicate that the mean water level between June 15 and June 30 will determine the elevation at which a nest will be constructed. A linear function is applied to the difference between the maximum water level during the egg incubation period (July 1 through September 1) and the mean water level during nest construction to give the probability of nest flooding. Biologists at ARM Loxahatchee NWR have suggested that a static value of 1.0 for this model component is appropriate for WCA 1.
Relative Habitat Quality - Available evidence suggests that the type of vegetative cover and elevation within an area greatly influence the probability of nesting. This model uses a static ranking of the dominant vegetation type within a 500-meter spatial cell as a measure of habitat quality.
Fleming, D. M. 1991. Wildlife Ecology Studies, Annual Report, South Florida Research Center, Everglades National Park, Homestead, Fl, V-10-1-52.
Kushlan, J. A. and T. Jacobsen. 1990. Environmental Variability and Reproductive Success of Everglades Alligators. J Herpetol. 24(2):176-184.
Mazzotti, F. J. and L. Brandt, 1994. Ecology of the American Alligator in a Seasonally Fluctuating Environment. Pgs:485-505 in S. M. Davis and J. Ogden (eds.) Everglades: The Ecosystem and Its Restoration. St. Lucie Press, Delray Beach, Fl.
The flow chart shows the steps in computing an index value for a cell.
Calculation of effects of water levels during periods of year
Four periods of the year are used:
(1) period from April 15 of previous year to May 16 of current year;
The model iterates over this time period and sums up all of the days in which the water depth is less than 0.5 feet. Then the proportion of non-nesting days during that period with water depth less than 0.5 feet (proportion_dry_days) is computed;
proportion_dry_days = [1.0 - (non_nesting_days - dry_days)/non_nesting_days]
This is used to compute the probability of females breeding in a cell located at x,y, as
females_nesting(x,y) = 1.53 - 4.88*proportion_dry_days(x,y)
This is set to 1.0 if females_nesting(x,y) > 1.0 and to 0.0 if females_nesting(x,y) < 0.0
This value of females_nesting(x,y) is rescaled for each cell by using the maximum and minimum values of this quantity on the entire modeled grid. The rescaled value is
females_nesting = 1/(MAX(females_nesting) - MIN(females_nesting))*(females_nesting -
(2) peak mating season, April 16 through May 15 of current year;
The current water levels are kept track of and the mean water depth (mean_mating_depth) during mating is calculated by averaging over the values of (mating_water_depth) during that period. This is used to determine if a nest will be built. If the mean water depth is less than 1.3 feet, then the probability of a nest being built is
prob_nest_built(x,y) = 0.212 + 0.457*mean_mating_depth
If the mean water depth is greater than 1.3 feet, then the probability of a nest being built is
prob_nest_built(x,y) = 3.15 - 1.67*mean_mating_depth
This value is set to 1.0 if prob_nest_built(x,y) > 1.0 and to 0.0 if prob_nest_built(x,y) < 0.0
The variables females_nesting(x,y) and prob_nest_built(x,y) are combined into a single variable
nesting(x,y) = (females_nesting(x,y) + probability_nest_built(x,y))/2.0
(3) peak early nest construction season, June 15 through June 30;
The probability of a nest being flooding is calculated from a combination of the mean water level during nest construction and the maximum water level during egg incubation. The current water levels (nest_water_depth) during this period are kept track of and the mean value during this time (mean_nest-water) is calculated. This will provide an estimate of the elevation at which the nest is built.
(4) incubation period, July 1 through September 30
A linear function is applied to the difference between the maximum water level during the egg incubation period (July 1 through September 1) and the mean water level during nest construction to give the probability of nest flooding. An indication of flooding potential is given by the difference between the maximum water depth during the incubation period (max_gest_water) and the mean water depth during the nest-building period (mean_nest_water)
flooding(x,y) = (max_gest_water - mean_nest_water)*2
In addition to factors derived from these hydrologic conditions, a habitat weighting factor, representing the quality of different FGAP habitat types, is defined:
Relative Habitat Quality - Available evidence suggests that the type of vegetative cover and elevation within an area greatly influence the probability of nesting. This model uses a static ranking of the dominant vegetation type within a 500-meter spatial cell as a measure of habitat quality. Habitat quality is given by the parameter habitat_weight. If this is zero for a cell, then there is no reproduction.
The values of habitat_weight are:
Veg. Class Weight Veg. Class Weight
0 0 22 0
1 1.0 23 1.0
2 1.0 24 0.6
3 Exclude 25 0.5
4 0 26 Exclude
5 0 27 0
6 0 29 1.0
7 1.0 30 0.7
8 0.1 31 0.5
9 Exclude 32 0.4
10 0 33 0.5
12 0 34 0.8
13 0 35 0
14 0 36 0
15 1.0 37 0
17 Exclude 38 0.7
18 0 39 0.5
20 1.0 40 0
21 0 41 0
The potential for alligator nesting success is then calculated as a combination of the terms representing nesting, habitat quality, and the potential for flooding.
gator_potential(x,y) = ((nesting(x,y) * NESTING_WEIGHT) + habitat_weight(x,y)
+ (1.0 - flooding(x,y))*FLOODING_WEIGHT)/FACTOR
where: NESTING_WEIGHT = 2.0
FLOODING_WEIGHT = 3.0
FACTOR = 6.0
For more information, see the original model description