USGS - science for a changing world

South Florida Information Access (SOFIA)



projects > across trophic level system simulation (atlss) > cape sable seaside sparrows > abstract


Individual Based Spatially Explicit Model of the Cape Sable Seaside Sparrow Population in the Florida Everglades

M. Philip Nott


The Cape Sable seaside sparrow (Ammodramus maritima mirabilis) is an ecologically isolated subspecies of the seaside sparrow. Recent surveys estimate its population at fewer than 6,000 individuals, and its range to be restricted to the extreme southern part of the Florida Peninsula, almost entirely within the boundaries of the Everglades National Park and Big Cypress National Preserve. The sparrow breeds in marl prairies typified by dense stands of graminoid species usually below 1 meter in height and naturally inundated by freshwater part of the year. As water levels recede during the dry season in late winter and spring, the sparrows establish territories and start nesting in the grass. Pairs may produce up to three broods if their nesting sites remain dry. If water levels do not recede early enough in spring, nesting may be delayed and if reflooding occurs during the nesting season, eggs or nestlings may be lost.

Declines have occurred in the sparrow population across its entire range, probably due to higher water levels in recent years. Because the current range of the sparrow is limited to a few hundred square kilometers and because it is subject to flooding and fires, the population is highly vulnerable. Changes to the hydrology of the southern Everglades, planned as part of an Everglades restoration project, could increase the water levels in parts of the sparrow’s range and inadvertently increase the risk to the reproductive success of the sparrow in certain areas. Figure 1 shows some of these risks in the "western" habitat area of the Cape Sable seaside sparrow. It is critical to predict how serious these risks are.

Topographic map of the Cape Sable seaside sparrow habitat and a bulleted list describing some risks in the habitat.
Figure 1. Topography of the western Cape Sable seaside sparrow habitat. Description of the effects of flooding and fire on sparrow habitat. Click for larger image.

A model for the Cape Sable sparrow subpopulation in the nesting area northwest of Shark Slough has been developed and has the following features:

  1. The landscape of the sparrow's range is modeled explicitly as a set of spatial cells of fine enough resolution to represent areas of similar vegetation, topography, and hydrology.
  2. Each individual sparrow in the population is modeled during a breeding period. In particular, the model tracks the sex, age, breeding status, of each model individual from egg to the end of its life. For mature males, the model tracks his search for an available territory, his finding a mate, the start of nesting, and the status of eggs and nestlings on a daily basis.
  3. The relation of sparrow breeding activity to water depth is modeled. Water depth in spatial cells is kept track of daily through a hydrologic model. A spatial cell is not available for nesting until water depth in that cell falls below about 5 cm. Any increase in water depth above 10 cm in a particular spatial cell during the nesting season is assumed to cause nest abandonment to the sparrows that have nests in that cell. The "variability" incorporated in this model is that of the specific spatial locations of sparrows' nests in different spatial cells, and thus the elevation of an individual sparrow nests. This elevation relative to the water stage determines the length of the effective reproductive season for the pair of sparrows and the vulnerability of the nest to flooding.
  4. The sparrows are not modeled in detail during the nonbreeding season. Age-specific mortalities are assigned probabilistically to individuals during that period, based on empirical data. The following spring, when the next breeding season begins, older males search for nesting territories as close as possible to the site they used last year (if it was successful), whereas new adult males begin their search close to their natal site.

The above conceptual model has been implemented as a Monte Carlo simulation model called SIMSPAR (M.P. Nott, Ph.D. dissertation, 1998). The model has been applied to a main subpopulation of the Cape Sable seaside sparrows on the western side of Shark Slough in the Everglades. The size of this subpopulation has reached as high as 3,000 sparrows, and the model is capable of keeping track of the locations and breeding status of all these birds during the breeding season. The model increases the age of an individual each day and updates its status according to movement and behavior rules. The core of the model is a simple flow of decisions and actions that affect individuals in relation to abiotic factors and other individuals. At each step the model updates the breeding status and tracks associations between individuals. Figure 2 shows some of the management questions to which this model is being applied.

Map image alongside a list of three (textual) management questions.
Figure 2. Management questions related to the effects of hydrology on Cape Sable seaside sparrow habitat. Click for larger image.

Subsequently, to address the question of uncertainty in model parameters affecting results, a sensitivity analysis was performed on SIMSPAR. The sensitivity analysis was done in the following way.

Step 1.- Each of the parameters was varied individually relative to the field estimate and 20 Monte Carlo simulations over 21 years was performed for each using the same hydrologic sequence experienced during the period 1976-96. For each simulation the highest population number and endpoint population number was detected. Overall, for a set of simulations the mean and coefficient of variation associated with each of these numbers was determined.

Step 2.- The 5 to 10 parameters to which population size is most sensitive were sampled from distributions about their means. Model runs were made with all of the parameters of this subset able to vary simultaneously. At least 200 simulations were performed. Again, means and 95 percent confidence intervals were plotted for the 31-year runs.

The sensitivity analyses have been extended to determine the relative contributions of each parameter to the overall response using generalized linear modeling. It is also possible that the model will be used to explore the evolutionary consequences of inherited dispersal behaviors.

Another objective of this work will be to design and edit web-based documentation of the model and the assumptions behind the mechanics. Such a design would mimic the experience of an individual bird as it proceeds through the model and the outcome would depend upon the course of action and status at any stage. This objective has also been extended to provide web-based documentation understandable at various levels of technical ability.

The most sensitive parameters and the biological or biophysical realities they correspond to are as follows:

Mortality.- Adult and juvenile (post fledging) mortality may vary as a result of food availability over the non-breeding season and predation pressure by hawks or snakes throughout the year. Egg and nestling mortality includes components of drowning risk during high-water events and extreme weather conditions causing desiccation or heat stress. Flooding may also affect the availability of food during this critical stage of the life cycle by drowning less vagile invertebrate species (for example, Orthopteran and Lepidopteran instars).

Number of clutches.- Although up to three clutches (with associated probabilities) have been attempted by breeding pairs during a potentially long breeding season (90-100 dry days) it is possible that fewer could be attempted. Reducing the maximum number might simulate a behavioral response to a lack of nestling food or a uniform decrease in the "window of opportunity" for breeding that might result from late drydown or early summer flooding periods.

Dispersal.- Sexual dimorphism is apparent in the dispersal strategies of individual sparrows. Males own territories for life so, once a territory has been established, the owner returns year after year. Females, on the other hand, choose a different mate year after year and therefore must search within a given range.

Habitat quality.- Degradation of sparrow habitat resulted in a greater than proportional decrease in overall breeding population size and an increased coefficient of variation in population size. When degradation of habitat and male dispersal were altered in a factorial set of runs, habitat degradation decreased population numbers whereas increased dispersal range increased population numbers. However, with increased dispersal, the coefficient of variation increased to asymptote at a dispersal distance of 1,000 meters.

Habitat changes.- Spatial pattern of degradation relevant to habitat type also affected overall numbers. If high elevation breeding habitat was degraded systematically, the population number declined to a greater extent than if low elevation breeding habitat was degraded by marsh expansion, or if all breeding habitat was degraded by spatially random processes.

These parameters all have a significant effect on population trajectories. However, it appears that dispersal behavior is a very crucial factor in population persistence, especially when linked to habitat degradation. Finding new, recently available, or restored habitat is crucial if small populations are to recover. An important question is: What is the impact of imposing an observed dispersal-distance distribution on a deterministic or simpler population model when the actual dispersal-distance distribution resulting may change as the result of an evolutionary stable strategy? We need much more information concerning age and sex-specific dispersal behaviors in this species and how these might change dependent upon the hydrologic conditions experienced over a number of years. Only by utilizing an individual based approach can we explore the limits of these relations and guide field studies.


(This abstract was taken from the Greater Everglades Ecosystem Restoration (GEER) Open File Report (PDF, 8.7 MB))

Note: PDF files require the Adobe Acrobat Reader to be read. Download the FREE Adobe Acrobat Reader ®.

Back to Project Homepage


U.S. Department of the Interior, U.S. Geological Survey, Center for Coastal Geology
This page is: http://sofia.usgs.gov /projects/atlss/sparrows/ibsemabgeer00.html
Comments and suggestions? Contact: Heather Henkel - Webmaster
Last updated: 04 September, 2013 @ 02:08 PM (KP)