Understanding how patchy landscapes affect the distribution and abundance of species is a central issue in applied ecology. We examined the effects of landscape structure on the distribution of the Florida scrub lizard (Sceloporus woodi) in naturally fragmented habitat. Scrub lizards were absent from 89 of 132 patches, and their distribution was explained in multifactor models by two landscape variables: patch size and patch isolation. Mark-recapture studies of S. woodi and experimental displacement trials indicate that this species exhibits low vagility within a patch and that movement through dense habitat, which often characterizes the landscape matrix, is restricted. Poor dispersal ability relative to the degree of isolation of patches in this landscape may account for large gaps in its distribution. To examine the applicability of the scrub lizard model to other species, we applied the model to a sympatric lizard, the six-lined racerunner (Cnemidophorus sexlineatus), which is similar in body size, food habits, and habitat requirements. The racerunner was more widely distributed than the Florida scrub lizard within our scrub landscape, and the model failed to predict its distribution. This differing response to landscape structure by a similar species is likely due to the greater dispersal ability of C. sexlineatus. Our results, and similar studies of other scrub organisms, indicate that each species may have a unique response to habitat fragmentation. The design and management of effective preserves for Florida scrub will require a multiscaled, multispecies approach that reflects the differences in the dispersal abilities, area requirements, and habitat preferences of the species to be preserved.

This article is a U.S. government work, and is not subject to copyright in the United States. From the EditorLike many members of the American Ornithologists' Union, I developed a passion for birds early in life and have been trying to make a living from this passion ever since. As you get to know fellow AOU members, particularly over drinks, you hear stories about that moment in their lives when they discovered this incredible feeling about birds that could not be ignored. Some of us started at age six or seven, others in high school or college.Some of us, lacking the artistic skills of David Sibley or the humor of Pete Dunne, have had to fall back on doing research. Our field work allows us to earn a paycheck in pursuit of our passion. We get to see and catch and count birds in what are sometimes exciting, and hopefully always interesting, places. We are paid to write reports, scientific papers, and books that present our results from the field. In many cases, our work has direct or indirect implications for bird conservation.Unfortunately, we cannot simply write papers about anything that catches our fancy. Rather, we need to justify our work on the basis of prior studies and present our results using up-to-date methodologies. For many of us, this is where the ugly concepts of hypotheses, models, and statistics come into play and turn our lives of passion into actual work and sometimes drudgery. During my career, the profession has become more and more based on the testing of models, usually with associated quantitative measures. I took a single statistics course during eight years of college; my graduate students take at least three or four, and often more. One even has a Master's degree in statistics to go along with her MS in ecology. More and more, our field work is only as good as the model being tested, and the test only as good as the calculations provided.Of course, doing field work requires a lot of skill, though usually of the "natural history" category that involves details about birds, plants, and so forth. Doing modeling and developing statistical methods obviously requires a high comfort level with conceptual thinking and mathematics. Few ornithologists are experts in both areas; field people are always trying to figure out what is currently the best way to measure their area of specialty, while modelers are trying to provide methods for the analytical questions posed by the field people. The goal of both groups is to develop the best science possible, with the appropriate scientific models tested with the best quantitative techniques.All these areas within ornithological research change over time, so it is difficult for field people to stay current with the latest models and for modelers to ensure that field people are providing the best data possible and analyzing it properly. Ornithological Monograph No. 59 addresses this problem by serving as a bridge between field biologists and modelers. It provides a state-of-the-art review by a set of experts of the models they consider most relevant to...

Florida manatees (Trichechus manatus latirostris) overwintering in the Ten Thousand Islands and western Everglades have no access to power plants or major artesian springs that provide warm-water refugia in other parts of Florida. Instead, hundreds of manatees aggregate at artificial canals, basins, and natural deep water sites that act as passive thermal refugia (PTR). Monitoring at two canal sites revealed temperature inverted haloclines, which provided warm salty bottom layers that generally remained above temperatures considered adverse for manatees. At the largest PTR, the warmer bottom layer disappeared unless significant salt stratification was maintained by upstream freshwater inflow over a persistent tidal wedge. A detailed threedimensional hydrology model showed that salinity stratification inhibited vertical convection induced by atmospheric cooling. Management or creation of temperature inverted haloclines may be a feasible and desirable option for resource managers to provide passive thermal refugia for manatees and other temperature sensitive aquatic species.

Sea level rise (SLR) projections along the coast of Florida present an enormous challenge for management and conservation over the long term. Decision makers need to recognize and adopt strategies to adapt to the potentially detrimental effects of SLR. Structured decision making (SDM) provides a rigorous framework for the management of natural resources. The aim of SDM is to identify decisions that are optimal with respect to management objectives and knowledge of the system. Most applications of SDM have assumed that the managed systems are governed by stationary processes. However, in the context of SLR it may be necessary to acknowledge that the processes underlying managed systems may be non-stationary, such that systems will be continuously changing. Therefore, SLR brings some unique