Geology topics

Christina M. Romagosa

Publications and source records attributed to Christina M. Romagosa.

24 records · Page 2Linked to original sources

USGS2018

Evaluating GPS biologging technology for studying spatial ecology of large constricting snakes

Background : GPS telemetry has revolutionized the study of animal spatial ecology in the last two decades. Until recently, it has mainly been deployed on large mammals and birds, but the technology is rapidly becoming miniaturized, and applications in diverse taxa are becoming possible. Large constricting snakes are top predators in their ecosystems, and accordingly they are often a management priority, whether their populations are threatened or invasive. Fine-scale GPS tracking datasets could greatly improve our ability to understand and manage these snakes, but the ability of this new technology to deliver high-quality data in this system is unproven. In order to evaluate GPS technology in large constrictors, we GPS-tagged 13 Burmese pythons ( Python bivittatu s) in Everglades National Park and deployed an additional 7 GPS tags on stationary platforms to evaluate habitat-driven biases in GPS locations. Both python and test platform GPS tags were programmed to attempt a GPS fix every 90 min. Results : While overall fix rates for the tagged pythons were low (18.1%), we were still able to obtain an average of 14.5 locations/animal/week, a large improvement over once-weekly VHF tracking. We found overall accuracy and precision to be very good (mean accuracy = 7.3 m, mean precision = 12.9 m), but a very few imprecise locations were still recorded (0.2% of locations with precision > 1.0 km). We found that dense vegetation did decrease fix rate, but we concluded that the low observed fix rate was also due to python microhabitat selection underground or underwater. Half of our recovered pythons were either missing their tag or the tag had malfunctioned, resulting in no data being recovered. Conclusions : GPS biologging technology is a promising tool for obtaining frequent, accurate, and precise locations of large constricting snakes. We recommend future studies couple GPS telemetry with frequent VHF locations in order to reduce bias and limit the impact of catastrophic failures on data collection, and we recommend improvements to GPS tag design to lessen the frequency of these failures.

Florida↗

USGS2017

Parasite spillover: Indirect effects of invasive Burmese pythons

Identification of the origin of parasites of nonindigenous species (NIS) can be complex. NIS may introduce parasites from their native range and acquire parasites from within their invaded range. Determination of whether parasites are non-native or native can be complicated when parasite genera occur within both the NIS’ native range and its introduced range. We explored potential for spillover and spillback of lung parasites infecting Burmese pythons ( Python bivittatus ) in their invasive range (Florida). We collected 498 indigenous snakes of 26 species and 805 Burmese pythons during 2004–2016 and examined them for lung parasites. We used morphology to identify three genera of pentastome parasites, Raillietiella , a cosmopolitan form, and Porocephalus and Kiricephalus , both New World forms. We sequenced these parasites at one mitochondrial and one nuclear locus and showed that each genus is represented by a single species, R. orientalis , P. crotali , and K. coarctatus . Pythons are host to R. orientalis and P. crotali , but not K. coarctatus ; native snakes are host to all three species. Sequence data show that pythons introduced R. orientalis to North America, where this parasite now infects native snakes. Additionally, our data suggest that pythons are competent hosts to P. crotali , a widespread parasite native to North and South America that was previously hypothesized to infect only viperid snakes. Our results indicate invasive Burmese pythons have affected parasite-host dynamics of native snakes in ways that are consistent with parasite spillover and demonstrate the potential for indirect effects during invasions. Additionally, we show that pythons have acquired a parasite native to their introduced range, which is the initial condition necessary for parasite spillback.

Florida↗

USGS2017

Optimal control of an invasive species using a reaction-diffusion model and linear programming

Managing an invasive species is particularly challenging as little is generally known about the species’ biological characteristics in its new habitat. In practice, removal of individuals often starts before the species is studied to provide the information that will later improve control. Therefore, the locations and the amount of control have to be determined in the face of great uncertainty about the species characteristics and with a limited amount of resources. We propose framing spatial control as a linear programming optimization problem. This formulation, paired with a discrete reaction-diffusion model, permits calculation of an optimal control strategy that minimizes the remaining number of invaders for a fixed cost or that minimizes the control cost for containment or protecting specific areas from invasion. We propose computing the optimal strategy for a range of possible model parameters, representing current uncertainty on the possible invasion scenarios. Then, a best strategy can be identified depending on the risk attitude of the decision-maker. We use this framework to study the spatial control of the Argentine black and white tegus ( Salvator merianae ) in South Florida. There is uncertainty about tegu demography and we considered several combinations of model parameters, exhibiting various dynamics of invasion. For a fixed one-year budget, we show that the risk-averse strategy, which optimizes the worst-case scenario of tegus’ dynamics, and the risk-neutral strategy, which optimizes the expected scenario, both concentrated control close to the point of introduction. A risk-seeking strategy, which optimizes the best-case scenario, focuses more on models where eradication of the species in a cell is possible and consists of spreading control as much as possible. For the establishment of a containment area, assuming an exponential growth we show that with current control methods it might not be possible to implement such a strategy for some of the models that we considered. Including different possible models allows an examination of how the strategy is expected to perform in different scenarios. Then, a strategy that accounts for the risk attitude of the decision-maker can be designed.

Florida↗

USGS2016

Spatially explicit control of invasive species using a reaction-diffusion model

Invasive species, which can be responsible for severe economic and environmental damages, must often be managed over a wide area with limited resources, and the optimal allocation of effort in space and time can be challenging. If the spatial range of the invasive species is large, control actions might be applied only on some parcels of land, for example because of property type, accessibility, or limited human resources. Selecting the locations for control is critical and can significantly impact management efficiency. To help make decisions concerning the spatial allocation of control actions, we propose a simulation based approach, where the spatial distribution of the invader is approximated by a reaction–diffusion model. We extend the classic Fisher equation to incorporate the effect of control both in the diffusion and local growth of the invader. The modified reaction–diffusion model that we propose accounts for the effect of control, not only on the controlled locations, but on neighboring locations, which are based on the theoretical speed of the invasion front. Based on simulated examples, we show the superiority of our model compared to the state-of-the-art approach. We illustrate the use of this model for the management of Burmese pythons in the Everglades (Florida, USA). Thanks to the generality of the modified reaction–diffusion model, this framework is potentially suitable for a wide class of management problems and provides a tool for managers to predict the effects of different management strategies.

Ecological Modelling↗

USGS2015

Predicting invasiveness of species in trade: Climate match, trophic guild and fecundity influence establishment and impact of non-native freshwater fishes

Aim Impacts of non-native species have motivated development of risk assessment tools for identifying introduced species likely to become invasive. Here, we develop trait-based models for the establishment and impact stages of freshwater fish invasion, and use them to screen non-native species common in international trade. We also determine which species in the aquarium, biological supply, live bait, live food and water garden trades are likely to become invasive. Results are compared to historical patterns of non-native fish establishment to assess the relative importance over time of pathways in causing invasions. Location Laurentian Great Lakes region. Methods Trait-based classification trees for the establishment and impact stages of invasion were developed from data on freshwater fish species that established or failed to establish in the Great Lakes. Fishes in trade were determined from import data from Canadian and United States regulatory agencies, assigned to specific trades and screened through the developed models. Results Climate match between a species’ native range and the Great Lakes region predicted establishment success with 75–81% accuracy. Trophic guild and fecundity predicted potential harmful impacts of established non-native fishes with 75–83% accuracy. Screening outcomes suggest the water garden trade poses the greatest risk of introducing new invasive species, followed by the live food and aquarium trades. Analysis of historical patterns of introduction pathways demonstrates the increasing importance of these trades relative to other pathways. Comparisons among trades reveal that model predictions parallel historical patterns; all fishes previously introduced from the water garden trade have established. The live bait, biological supply, aquarium and live food trades have also contributed established non-native fishes. Main conclusions Our models predict invasion risk of potential fish invaders to the Great Lakes region and could help managers prioritize efforts among species and pathways to minimize such risk. Similar approaches could be applied to other taxonomic groups and geographic regions.

Diversity and Distributions↗

USGS2012

Severe mammal declines coincide with proliferation of invasive Burmese pythons in Everglades National Park

Invasive species represent a significant threat to global biodiversity and a substantial economic burden. Burmese pythons, giant constricting snakes native to Asia, now are found throughout much of southern Florida, including all of Everglades National Park (ENP). Pythons have increased dramatically in both abundance and geographic range since 2000 and consume a wide variety of mammals and birds. Here we report severe apparent declines in mammal populations that coincide temporally and spatially with the proliferation of pythons in ENP. Before 2000, mammals were encountered frequently during nocturnal road surveys within ENP. In contrast, road surveys totaling 56,971 km from 2003–2011 documented a 99.3% decrease in the frequency of raccoon observations, decreases of 98.9% and 87.5% for opossum and bobcat observations, respectively, and failed to detect rabbits. Road surveys also revealed that these species are more common in areas where pythons have been discovered only recently and are most abundant outside the python's current introduced range. These findings suggest that predation by pythons has resulted in dramatic declines in mammals within ENP and that introduced apex predators, such as giant constrictors, can exert significant top-down pressure on prey populations. Severe declines in easily observed and/or common mammals, such as raccoons and bobcats, bode poorly for species of conservation concern, which often are more difficult to sample and occur at lower densities.

Florida↗