Geology topics

Caitlin E. Hackett

Publications and source records attributed to Caitlin E. Hackett.

5 recordsLinked to original sources

USGS2023

The Everglades vulnerability analysis: Linking ecological models to support ecosystem restoration

Understanding of the Everglades’ ecological vulnerabilities and restoration needs has advanced over the past decade but has not been applied in an integrated manner. To address this need, we developed the Everglades Vulnerability Analysis (EVA), a decision support tool that uses modular Bayesian networks to predict the ecological outcomes of a subset of the ecosystem’s health indicators. This tool takes advantage of the extensive modeling work already done in the Everglades and synthesizes information across indicators of ecosystem health to forecast long-term, landscape-scale changes. In addition, the tool can predict indicator vulnerability through comparison to user-defined ideal system states that can vary in the level of certainty of outcomes. An integrated understanding of the Everglades system is essential for evaluation of trade-offs at local, regional, and system-wide scales. Through EVA, Everglades restoration decision makers can provide effective guidance during restoration planning and implementation processes to mitigate unintended consequences that could result in further damage to the Everglades system.

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USGS2022

Managing multiple species with conflicting needs in the Greater Everglades

Given limited funding, natural resources decision making is riddled with tradeoffs, including which species or landscapes to prioritize for management action. Florida’s Everglades wetland is home to numerous indicator species, some of which are endangered. But with a multitude of species comes differing hydrologic requirements to yield appropriate foraging and breeding conditions for each. The Everglades ecosystem is highly managed, with water being moved across the landscape to meet the habitat and reproductive needs of species of concern. Predictive modeling can help water managers understand potential consequences to targeted water conditions. EverForecast is a novel spatially explicit, hydrologic, and ecological operational forecast developed to inform conservation management decisions. Not only does EverForecast provide probable near-term water conditions, but also predicted species responses to those hydrologic conditions. Using examples from two focal regions of the Everglades, we show the magnitude of impacts to a suite of species and an almost 70% decline in suitable conditions for one species when prioritizing water management to meet the needs of another species. Although EverForecast is a relatively new decision support tool, its hydrologic outputs are already commonly used to make water management recommendations because it provides near-term hydrologic forecasts that scientists and managers need for water operations decision making. Because species management decisions have historically been made to target a single species at a time, it may take longer for full utility of EverForecast’s ability to quantify tradeoffs among species to become integrated into decision making.

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USGS2022

Hematology and biochemistry reference intervals for American alligator (Alligator mississippiensis) in South Florida, USA

We calculated reference intervals for 48 blood parameters from 120 wild American alligators ( Alligator mississippiensis ) in South Florida, US. Although previously reported by others, this study includes additional parameters not yet reported in wild populations. Most previously reported blood parameter values were similar to ours and fell within our reference intervals.

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USGS2021

The Everglades vulnerability analysis—Integrating ecological models and addressing uncertainty

The Everglades vulnerability analysis (EVA) is a project led by the U.S. Geological Survey in cooperation with the National Park Service and U.S. Army Corps of Engineers to accomplish one of the science goals of Restoration Coordination & Verification (RECOVER), a multiagency group responsible for providing scientific and technical evaluations and assessments for improving the ability of the Comprehensive Everglades Restoration Plan to restore, preserve, and protect the south Florida ecosystem while providing for the region’s other water-related needs. In 2016, RECOVER acknowledged the need for a tool that could synthesize the decades of Everglades ecosystem science and identify areas vulnerable to changing conditions on the landscape. The EVA tool answers this need through a landscape-scale modeling framework that provides annual responses and relative vulnerability for a suite of indicators of Everglades ecosystem health.

Florida↗

USGS2021

Hierarchical models improve the use of alligator abundance as an indicator

Indicator species are species which can be monitored as an index to measure the overall health of an ecosystem. Crocodylians have been shown to be good indicators of wetland condition as they respond to changes in hydrology, can be efficiently monitored, and are a key part of ecosystem trophic relationships. Eye shine surveys at night are a standard method used to sample alligators, but because some individuals that are present in a study area may go undetected and the proportion of individuals counted is not constant over time, appropriate modeling is required to convert counts to estimates of abundance. We analyzed 13 years of American alligator ( Alligator mississippiensis ) survey count data from South Florida using an N -mixture model. Alligator abundance estimates were assigned to quartiles that were then represented as color coded categories of red, yellow, or green to provide a straightforward rating of Everglades restoration based on familiar stoplight coloring. These results were then compared to a previously used method in which unadjusted counts of these same data were assigned to color coded quartile categories. Water depth played a major role in the detection probability of alligators and the stoplight colors between the two methods matched 76% of the time. This suggests that the original stoplight score method provided a good overall snapshot of the trends in alligator abundance in the Everglades; however, the hierarchical models estimate abundance and trends of alligator abundance by incorporating detection probability thus providing unbiased estimates of abundance.

Florida↗