Evaluating the Effect of Salinity on a Simulated American Crocodile ( Crocodylus acutus ) Population
Paul M. Richards
Florida State University, Tallahassee, FL
Wolf M. Mooij
Netherlands Institute of Ecology, Nieuwersluis, The Netherlands
Donald L. DeAngelis
U.S. Geological Survey, Center for Water and Restoration Studies, University of
Miami, Department of Biology, Coral Gables, FL USA
Everglades restoration will alter the hydrology of the endangered American crocodile’s (
Crocodylus acutus ) estuarine habitat of South Florida, affecting both water depth and salinity levels. Juvenile American crocodiles are thought to be sensitive to high salinity levels, suffering reduced mass, and potentially reduced survivorship and recruitment, thereby negatively impacting the population recovery. To answer the question of how the crocodile population will respond to alterations in hydrology we developed a spatially explicit individual based model designed to relate water levels, salinities, and dominant vegetation to crocodile distribution, abundance, population growth, individual growth, survival, nesting effort, and nesting success. The nature of the relationship between salinity and growth was based on physiological measures in the lab that include only individuals smaller than 450 grams. The core of this model assumes that this relationship applies to the field, and to some extent, to individuals of all sizes
(fig.1). Four different combinations of base parameterizations and initial population size were examined with sensitivity analyses and a factorial manipulation of model salinities, to evaluate the effects of each on population size, nest number, and survivorship of young of the year (YOY) crocodiles.
Two types of sensitivity analysis were used, individual parameter perturbation
(IPP) and uncertainty analysis. IPP examines the effect of small changes in individual parameter values on model output while holding all other parameters constant and uncertainty analysis examines the effect of random combinations of parameter values on model output. For IPP analysis we individually altered each nominal parameter by +/- 1% for continuous values and +/- 1 unit for integer values while holding all other parameters constant. For uncertainly analysis we employed the modified Latin hypercube parameter sampling method with 100
Monte Carlo simulations. Each continuous parameter was cut into 100 equidistant values within its range and each integer parameter was cut into 100 integer pieces

within its range. From these sets we randomly selected parameters without replacement to construct the 100 parameter sets.
The rank ordering from the IPP analysis failed to give consistent rankings between populations. Because of this lack of consistency, for any output variable it is difficult to use these results to select a set of parameters that the model may be particularly sensitive to, independent of the population initial conditions or parameterization. In contrast, the uncertainty analysis consistently ranked parameters between populations, and therefore, it can inform us about parameters to concentrate on for further research and management.
Based on this result we conclude that to better understand C. acutus population dynamics, we suggest that research focus on survivorship and growth rate parameters, because these were ranked high by uncertainty analysis. The parameter with the largest effect on model output was survival of large individuals, which is not unusual for long-lived organisms. It may be difficult to measure survivorship for large individuals, but since it is consistently highly ranked as a parameter to which population size is sensitive, greater effort should be made to collect this sort of data.
To examine the model under possible management alternatives, we varied the application of salinity to the model in a fully crossed 3 way ANOVA. The model can alter timing of peak salinity, duration of salinity levels, and the spatial distribution of salinity ranges. Each of these factors were manipulated at 3 levels.
Timing of the salinity peak was altered by one month (30 days), earlier and later than the base model value of day 144 (May 24). Salinity duration was compared at 3 levels, short, medium (base), and long. Regional salinity range values were also compared, raising these 5 ppt, and 10 ppt above base model runs.
Increasing regional salinity significantly reduced population size, nest number, and YOY survivorship in all base parameterizations. This effect was probably because at highest regional salinity treatment, even the lowest salinity habitats were at salinities for part of the year where small crocodiles would lose mass regardless of other conditions. Delaying the peak salinity level by one month, which placed it at the beginning of hatching season, significantly reduced the number of nests for only one parameterization. No other parameterizations were significantly affected by alterations in timing of peak salinity. Duration of salinity spread had no significant effect.
This model shows that research should focus on estimates of annual survivorship for large individuals. Similarly, conservation priority should be placed on

reducing anthropogenic sources of mortality on large individuals, such as road mortality. Everglades restoration, through it’s effects on water flow to estuaries may benefit crocodile populations if increased freshwater flow reduces the chances that regional salinity levels exceed levels where small individuals lose mass.
Figure 1: Daily percent change in mass (MaxMass∆) as a function of salinity for model C. acutus from 50g to 500kg.
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Paul M. Richards, School of Computational Science and Information Technology,
400 Dirac Science Library, Florida State University, Tallahassee, Fl 32306-4052
Phone: 850-644-0178 paul@csit.fsu.edu