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Telescoping prey selection in invasive Burmese pythons spells trouble for endangered rodents

The allometric scaling of predators and their prey is well established within snakes (i.e., gape-width limits maximum prey sizes). However, while some species exhibit ontogenetic shifts to larger prey as they grow, others exhibit telescoping prey selection and continue to consume small prey in addition to larger prey. The Burmese python ( Python bivittatus ) is a large dietary generalist constrictor native to Southeast Asia that is established in South Florida (USA). As part of survey efforts at the southern invasion front in the Florida Keys, we used camera traps to document predation on endangered Key Largo cotton mice ( Peromyscus gossypinus allapaticola ) by an adult female Burmese python. These images represent the first photo documentation of predation attempts upon a federally endangered species in the python's invasive range, but we note three additional instances of Key Largo cotton mice in the gut contents of euthanized pythons from Key Largo. These observations suggest Burmese pythons exhibit telescoping prey selection behavior where even small rodents (<30 g) are viable prey for adult snakes. However, based on the number of documented strikes with failed predation events and low frequency of occurrence in gut contents, we suspect mice may be less common prey items for adult (i.e., >185 cm SVL) pythons relative to cotton mouse abundance in the environment. However, we also documented endangered Key Largo woodrats ( Neotoma floridana smalli ) and Key Largo cotton mice collecting and consuming the shed skins of pythons, which suggests the two rodent species remain naïve to the threat of these invasive predators. Further understanding of the impact of Burmese pythons on native prey communities can help inform efforts to minimize biodiversity loss along their invasion fronts.

Food Webs↗

The Lake Ontario zooplankton community before (1987-1991) and after (2001-2005) invasion-induced ecosystem change

We assessed changes in Lake Ontario zooplankton biomass, production, and community composition before (1987–1991) and after (2001–2005) invasion-induced ecosystem changes. The ecosystem changes were associated with establishment of invasive dreissenid mussels and invasive predatory cladocerans ( Bythotrephes and Cercopagis ). Whole-lake total epilimnetic plus metalimnetic zooplankton production declined by approximately half from 42.45 (g dry wt∙m −2 ∙ year −1 ) during 1987–1991 to 21.91 (g dry wt∙m −2 ∙ year −1 ) in 2003 and averaged 21.01 (g dry wt∙m −2 ∙ year −1 ) during 2001–2005. Analysis of two independent data sets indicates that the mean biomass and biomass proportion of cyclopoid copepods declined while the same measures increased for the invasive predatory cladocerans. Changes in means and proportions of all other zooplankton groups were not consistent between the data sets. Cyclopoid copepod biomass and production declined by factors ranging from 3.6 to 5.7. Invasive predatory cladoceran biomass averaged from 5.0% to 8.0% of the total zooplankton biomass. The zooplankton community was otherwise resilient to the invasion-induced disruption as zooplankton species richness and diversity were unaffected. Zooplankton production was likely reduced by declines in primary productivity but may have declined further due to increased predation by alewives and invasive predatory cladocerans. Shifts in zooplankton community structure were consistent with increased predation pressure on cyclopoid copepods by alewives and invasive predatory cladocerans. Predicted declines in the proportion of small cladocerans were not evident. This study represents the first direct comparison of changes in Lake Ontario zooplankton production before and after the invasion-induced disruption and will be important to food web-scale investigations of invasion effects.

Journal of Great Lakes Research↗

A comparison of survey methods to evaluate macrophyte index of biotic integrity performance in Minnesota lakes

Aquatic macrophytes shape trophic web dynamics, provide food and refuge for macroinvertebrates and fish, and increase nutrient retention, sediment stabilization, and water clarity. Macrophytes are well-suited as indicators of ecological health because they are immobile, relatively easy to sample and identify, and respond to anthropogenic disturbance on an ecological time scale. Aquatic plant monitoring programs can provide valuable information to water resource managers, especially in conjunction with macrophyte-based indices of biotic integrity (IBI). However, there are several current sampling designs and the precision of IBI scores has not been evaluated across different surveys. We evaluated the performance of the Minnesota macrophyte-based IBI for two survey designs; a point intercept (PI) survey and a belt transect (BT) survey. PI surveys are time intensive, especially on large lakes, whereas BT are less time intensive and have been used historically in Minnesota. Our objectives were to compare the PI surveys with BT surveys on the same lakes, and to modify the BT survey (MT survey) to improve information obtained from BT surveys. BT surveys consistently overestimated IBI scores compared to the PI method ( t = 6.268, df = 60, p < 0.001). Overall IBI scores calculated from MT surveys differed significantly from PI scores, but on average, MT surveys predicted scores only 3% lower than PI scores. Implementation of the Minnesota macrophyte-based IBI through the adoption of the MT survey approach would improve sampling efficiency and enable widespread documentation of the effects of landscape change, shifts in hydrologic regimes, and other anthropogenic activities on the integrity of lacustrine systems.

Ecological Indicators↗

Introduction to special section on impacts of land use change on water resources

Changes in land use have potentially large impacts on water resources, yet quantifying these impacts remains among the more challenging problems in hydrology. Water, food, energy, and climate are linked through complex webs of direct and indirect effects and feedbacks. Land use is undergoing major changes due not only to pressures for more efficient food, feed, and fiber production to support growing populations but also due to policy shifts that are creating markets for biofuel and agricultural carbon sequestration. Hydrologic systems embody flows of water, solutes, sediments, and energy that vary even in the absence of human activity. Understanding land use impacts thus necessitates integrated scientific approaches. Field measurements, remote sensing, and modeling studies are shedding new light on the modes and mechanisms by which land use changes impact water resources. Such studies can help deconflate the interconnected influences of human actions and natural variations on the quantity and quality of soil water, surface water, and groundwater, past, present, and future.

Water Resources Research↗

EMMMA: A web-based system for environmental mercury mapping, modeling, and analysis

Mercury in our environment - in our air, water, soil, and especially our food - poses significant hazards to human health, particularly for developing fetuses and young children. Because of the importance of this issue and the length of time it has been studied, large and complex data sets of mercury concentrations in various media and associated ancillary data have been generated by many Federal, State, Tribal, and local agencies. To facilitate efficient and effective use of these data in managing and mitigating human and wildlife exposure to mercury, the U.S. Geological Survey (USGS) and the National Institute of Environmental Health Sciences have developed a website for visualizing and studying the distribution of mercury in our environment. The Environmental Mercury Mapping, Modeling, and Analysis (EMMMA) website (http://emmma.usgs.gov) provides health and environmental researchers, managers, and other decision-makers the ability to: 1) Interactively view and access a nationwide collection of environmental mercury data (fish tissue, atmospheric emissions and deposition, stream sediments, soils, and coal) and mercuryrelated data (mine locations); 2) Interactively view and access predictions of the National Descriptive Model of Mercury in Fish (NDMMF) at 4,976 sites and 6,829 sampling events (events are unique combinations of site and sampling date) across the United States; and 3) Use interactive mapping and graphing capabilities to visualize spatial and temporal trends and study relationships between mercury and other variables.

Open-File Report↗

Enhancing the application of Earth observations for improved environmental decision-making using the Early Warning eXplorer (EWX)

The mitigation of losses due to extreme climate events and long-term climate adaptation requires climate informed decision-making. In the past few decades, several remote sensing and modeled-based Earth observations (EOs) have been developed to provide an unprecedented global overview and routine monitoring of climate and its impacts on vegetation and hydrologic conditions, with the goal of supporting informed decision-making. However, their usage in decision-making is particularly limited in climate-risk vulnerable and in situ data-scarce regions such as sub-Saharan Africa, due to lack of access to EOs. Here, we describe the Early Warning eXplorer (EWX), which was developed to address this crucial limitation and facilitate the application of EOs in decision-making, particularly in the food and water-insecure regions of the world. First, the EWX's core framework, which includes (i) the Viewer, (ii) GeoEngine, and (iii) Support Applications, is described. Then, a comprehensive overview of the Viewer, which is a web-based interface used to access EOs, is provided. This includes a description of (i) the maps and associated features to access gridded EO data and anomalies for different temporal averaging periods, (ii) time series graphs and associated features to access EOs aggregated over polygons such as administrative boundaries, and (iii) commonly used EOs served by the EWX that provide assessments of climate and vegetation conditions. Next, examples are provided to demonstrate how EWX can be used to monitor development, progression, spatial extent, and severity of climate-driven extreme events to support timely decisions related to mitigation of food insecurity and flooding impacts. Finally, the value of a regional implementation of EWX at the Regional Centre for Mapping of Resources for Development (RCMRD) in Nairobi, Kenya, is highlighted. Regional implementation of the EWX facilitates access to regionally focused EOs and their availability at polygon boundaries most relevant to the local decision-makers. Similar instances of EWX implemented in other regions, especially those susceptible to food and water security, will likely further enhance the application of EOs for informed decision-making.

Frontiers in Climate↗

Patterns of primary production and ecological drought in Yellowstone

Introduction: Photosynthesis converts sunlight into stored energy in millions of leaves, flowers and seeds that maintain the web of life in Yellowstone. This transformation of energy fixes carbon, supplies organic matter to soils, and can become fuel for wildfire. As the first link of the food chain, new plant biomass is called primary production and provides energy to consumers, including wildlife. While Yellowstone is a mountain environment with deep winter snowpack, the park can get very dry in some years as evidenced by massive wildfires in 1988 and 2016. Droughts like these not only contribute to fire potential, but they affect primary production, the food chain and likely will play an increasingly important role in transforming vegetation structure and composition in the future. Meteorological, agricultural, and hydrological drought have been assessed quantitatively for many years, but key indicators of drought in wildland ecosystems have not been formally defined until recently (Crausbay et al., 2017). One promising new method to do this is by measuring how vegetation responds to negative effects of drought, and positive effects of favorable conditions that offset negative effects of drought. The balance of drought stress and growth has important implications for future vegetation condition as the climate of Yellowstone changes. Monitoring primary production, and predicting future vegetation changes are needed to provide a comprehensive view of park health and anticipate future ecosystem changes (Crabtree et al. 2009, Nemani et al. 2009). Although an important indicator of ecosystem condition, primary production can be time and resource-intensive to monitor in wildland settings using traditional ground-based methods such as clipping and weighing. Fortunately, ground-based methods can be complemented and enhanced by monitoring primary production with satellite imagery. Measurements of solar radiation reflectance in visible and near infra-red wavelengths can indicate primary production at frequent weekly intervals from the Moderate Resolution Imaging Spectrometer (MODIS) on satellites operated by NASA. The Greater Yellowstone Inventory and Monitoring Network (GRYN) uses this information to track changes in primary production across Yellowstone over time. They link these measurements to vegetation types, soils, and climate to understand where and when changes in production have occurred and may occur in the future.

Yellowstone National Park↗

Global irrigated area map (GIAM), derived from remote sensing, for the end of the last millennium

A Global Irrigated Area Map (GIAM) has been produced for the end of the last millennium using multiple satellite sensor, secondary, Google Earth and groundtruth data. The data included: (a) Advanced Very High Resolution Radiometer (AVHRR) 3-band and Normalized Difference Vegetation Index (NDVI) 10 km monthly time-series for 1997-1999, (b) Syste me pour l'Observation de la Terre Vegetation (SPOT VGT) NDVI 1 km monthly time series for 1999, (c) East Anglia University Climate Research Unit (CRU) rainfall 50km monthly time series for 1961-2000, (d) Global 30 Arc-Second Elevation Data Set (GTOPO30) 1 km digital elevation data of the World, (e) Japanese Earth Resources Satellite-1 Synthetic Aperture Radar (JERS-1 SAR) data for the rain forests during two seasons in 1996 and (f) University of Maryland Global Tree Cover 1 km data for 1992-1993. A single mega-file data-cube (MFDC) of the World with 159 layers, akin to hyperspectral data, was composed by re-sampling different data types into a common 1 km resolution. The MFDC was segmented based on elevation, temperature and precipitation zones. Classification was performed on the segments. Quantitative spectral matching techniques (SMTs) used in hyperspectral data analysis were adopted to group class spectra derived from unsupervised classification and match them with ideal or target spectra. A rigorous class identification and labelling process involved the use of: (a) space-time spiral curve (ST-SC) plots, (b) brightness-greenness-wetness (BGW) plots, (c) time series NDVI plots, (d) Google Earth very-high-resolution imagery (VHRI) 'zoom-in views' in over 11 000 locations, (e) groundtruth data broadly sourced from the degree confluence project (3 864 sample locations) and from the GIAM project (1 790 sample locations), (f) high-resolution Landsat-ETM+ Geocover 150m mosaic of the World and (g) secondary data (e.g. national and global land use and land cover data). Mixed classes were resolved based on decision tree algorithms and spatial modelling, and when that did not work, the problem class was used to mask and re-classify the MDFC, and the class identification and labelling protocol repeated. The sub-pixel area (SPA) calculations were performed by multiplying full-pixel areas (FPAs) with irrigated area fractions (IAFs) for every class. A 28 class GIAM was produced and the area statistics reported as: (a) annualized irrigated areas (AIAs), which consider intensity of irrigation (i.e. sum of irrigated areas from different seasons in a year plus continuous year-round irrigation or gross irrigated areas), and (b) total area available for irrigation (TAAI), which does not consider intensity of irrigation (i.e. irrigated areas at any given point of time plus the areas left fallow but 'equipped for irrigation' at the same point of time or net irrigated areas). The AIA of the World at the end of the last millennium was 467 million hectares (Mha), which is sum of the non-overlapping areas of: (a) 252 Mha from season one, (b) 174 Mha from season two and (c) 41 Mha from continuous year-round crops. The TAAI at the end of the last millennium was 399 Mha. The distribution of irrigated areas is highly skewed amongst continents and countries. Asia accounts for 79% (370 Mha) of all AIAs, followed by Europe (7%) and North America (7%). Three continents, South America (4%), Africa (2%) and Australia (1%), have a very low proportion of the global irrigation. The GIAM had an accuracy of 79-91%, with errors of omission not exceeding 21%, and the errors of commission not exceeding 23%. The GIAM statistics were also compared with: (a) the United Nations Food and Agricultural Organization (FAO) and University of Frankfurt (UF) derived irrigated areas and (b) national census data for India. The relationships and causes of differences are discussed in detail. The GIAM products are made available through a web portal (http://www.iwmigiam.org). ?? 2009 Taylor & Francis.

International Journal of Remote Sensing↗

Science and the storms: The USGS response to the hurricanes of 2005

This report is designed to give a view of the immediate response of the U.S. Geological Survey (USGS) to four major hurricanes of 2005: Dennis, Katrina, Rita, and Wilma. Some of this response took place days after the hurricanes; other responses included fieldwork and analysis through the spring. While hurricane science continues within the USGS, this overview of work following these hurricanes reveals how a Department of the Interior bureau quickly brought together a diverse array of its scientists and technologies to assess and analyze many hurricane effects. Topics vary from flooding and water quality to landscape and ecosystem impacts, from geotechnical reconnaissance to analyzing the collapse of bridges and estimating the volume of debris. Thus, the purpose of this report is to inform the American people of the USGS science that is available and ongoing in regard to hurricanes. It is the hope that such science will help inform the decisions of those citizens and officials tasked with coastal restoration and planning for future hurricanes. Chapter 1 is an essay establishing the need for science in building a resilient coast. The second chapter includes some hurricane facts that provide hurricane terminology, history, and maps of the four hurricanes’ paths. Chapters that follow give the scientific response of USGS to the storms. Both English and metric measurements are used in the articles in anticipation of both general and scientific audiences in the United States and elsewhere. Chapter 8 is a compilation of relevant ongoing and future hurricane work. The epilogue marks the 2-year anniversary of Hurricane Katrina. An index of authors follows the report to aid in finding articles that are cross-referenced within the report. In addition to performing the science needed to understand the effects of hurricanes, USGS employees helped in the rescue of citizens by boat and through technology by “geoaddressing” 911 calls after Katrina and Rita so that other rescuers could find persons trapped in attics and porches. They also delivered food and water to residents stranded along the lower Mississippi River for several days. That work is reported in chapter 3 of this volume. A great number of scientists contributed to this peer-reviewed report designed for a general audience. Because they work for USGS—an unbiased, multidisciplinary science organization that focuses on biology, geography, geology, geospatial information, and water—they are dedicated to the timely, relevant, and impartial study of the landscape and natural resources of the Nation, as well as natural hazards, like hurricanes, that threaten the Nation. To learn more about their work, visit the USGS Web site (www.usgs.gov).

Circular↗

Disease, drought, and warming: A triple threat to a declining high-elevation amphibian

Managing species in an uncertain future is a reality for natural resource decision makers. Climate change is expected to exacerbate threats such as habitat loss and disease, and cause phenological mismatches, but there is uncertainty in the magnitude of these effects. Amphibians are among the most threatened taxa on earth, and most species in North America are uniquely tied to water availability for breeding, larval development, thermal refugia, and food availability. Changes in water availability and temperature may result in phenological mismatches with one or more of these processes. Thus, quantifying the dependency of amphibians to water on the landscape is critical to understanding how species may respond, as well as understanding the interplay with other threats, such as disease. We developed a dynamic co-occurrence occupancy model to explore the effects of climate change on the breeding occurrence of boreal toads ( Anaxyrus boreas ) and the amphibian chytrid fungus ( Batrachochytrium dendrobatidis , Bd) in the southern Rocky Mountains (SRM). We derived novel covariates to test hypotheses related to multi-generational impacts of climate on the dynamics of both boreal toad breeding and Bd. We report estimates of current (2001–2019) and future (2055–2069) occupancy under a range of plausible climate scenarios. The probability of boreal toad breeding occurrence at a site in the SRM declined > 40% from 2001 to 2019, and further declines are likely under future scenarios, particularly as active season length increases. To help integrate this information into management, we developed a web-based decision support tool to summarize predicted future hydrological and occupancy conditions.

Colorado, New Mexico, Wyoming↗

Prescribed fire and other fuel-reduction treatments alter ground spider assemblages in a Southern Appalachian hardwood forest

Prescribed burns and understory thinnings are forest management practices aimed at reducing fuel loads to lessen wildfire threat in the Southern Appalachians, USA. Spiders play a critical role in forest ecosystems by controlling insect populations and providing an important food source for vertebrates. We used pitfall and colored pan traps to investigate how abundance, species richness, and diversity of spiders differed among three fuel reduction treatments administered repeatedly over a 15-year period and untreated controls. Additionally, we examined how spiders responded to one round (before and after) of fuel reduction treatments. We established treatments within the 15-year period as follows: mechanical understory removal (twice; M), prescribed burning (four times; B), mechanical understory removal followed one year later by high-severity prescribed burns and three subsequent burns (MB), and untreated controls (C). Our study period (2014–2016) occurred after multiple prescribed burns and two rounds of mechanical understory removal had occurred. Salticidae and Lycosidae were the two most commonly collected spider families in Southern Appalachian hardwood forests. Generally, we found increased spider abundances within all fuel-reduction treatments compared to controls. Individual spider families and species showed variable responses to treatments, but abundance of several spider families was greater in one or more fuel-reduction treatments than in controls. Additionally, abundance of several spider families and hunting/web building guilds (webs built for hunting purposes or defense) exhibited yearly differences to the last round of fuel-reduction treatments. Overall, our results suggest that changes in the overstory and understory of a forest are important drivers of regional spider abundance and assemblages, and forest management practices that modify forest structure can dramatically alter spider abundance and richness, usually in a positive manner.

North Carolina↗

Wildlife specimen collection, preservation, and shipment

Specimens are used to provide supporting information leading to the determination of the cause of disease or death in wildlife and for disease monitoring or surveillance. Commonly used specimens for wildlife disease investigations include intact carcasses, tissues from carcasses, euthanized or moribund animals, parasites, ingested food, feces, or environmental samples. Samples from live animals or the environment (e.g., contaminated feed) in the same vicinity as a mortality event also may be helpful. The type of specimen collected is determined by availability of samples and biological objectives. Multiple fresh, intact carcasses from affected species are the most useful in establishing a cause for a mortality event. Submission of entire carcasses allows observation of gross lesions and abnormalities, as well as disease testing of multiple tissues. Samples from live animals may be more appropriate when sick animals cannot be euthanized (e.g., threatened or endangered species) or for research and monitoring projects examining disease or agents circulating in apparently healthy animals or those not exhibiting clinical signs. Samples from live animals may include collections of blood, hair, feathers, feces, or ectoparasites, or samples obtained by swabbing lesions or orifices. Photographs and videos are useful additions for recording field and clinical signs and conveying conditions at the site. Collection of environmental samples (e.g., feces, water, feed, or soil) may be appropriate when animals cannot be captured for sampling or the disease agent may persist in the environment. If lethal collection is considered necessary, biologists should refer to the policies, procedures, and permit requirements of their institution/facility and the agency responsible for species management (U.S. Fish and Wildlife Service or State natural resource agency) prior to use in the field. If threatened or endangered species are found dead, or there is evidence of illegal take, field personal should contact local wildlife law enforcement authorities immediately and prior to handling the carcass. Prior to collecting samples, it is important to determine the capabilities and submission criteria of the laboratory receiving the samples. Some laboratories may specialize in a limited number of tests, be equipped to accept only certain types of tissues (instead of entire carcasses), or specialize in particular species or group of animals (e.g., reptiles, birds, mammals). Diagnostic laboratories have specific requirements regarding preparation, labeling, and shipping of samples. Adherence to these requirements helps ensure the usefulness of any submitted specimens. Although laboratories may vary in the cost and turnaround times for diagnostic tests, some laboratories may be able to prioritize samples and accommodate accelerated time frames if communicated at the time of submission. Keeping a prepacked kit with basic carcass-collection supplies, including a paper copy of the specimen history form (available for download from the Web sites of most diagnostic laboratories), in the office or vehicle will decrease the chances of forgetting an essential item and decrease response time for arriving at an event.

Techniques and Methods↗

Submersed Aquatic Vegetation Modeling Output Online

Introduction The ability to predict the distribution of submersed aquatic vegetation in the Upper Mississippi River on the basis of physical or chemical variables is useful to resource managers. Wildlife managers have a keen interest in advanced estimates of food quantity such as American wildcelery (Vallisneria americana) population status to give out more informed advisories to hunters before the fall hunting season. Predictions for distribution of submerged aquatic vegetation beds can potentially increase hunter observance of voluntary avoidance zones where foraging birds are left alone to feed undisturbed. In years when submersed aquatic vegetation is predicted to be scarce in important wildlife habitats, managers can get the message out to hunters well before the hunting season (Jim Nissen, Upper Mississippi River National Wildlife and Fish Refuge, La Crosse District Manager, La Crosse, Wisconsin, personal communication). We developed a statistical model to predict the probability of occurrence of submersed aquatic vegetation in Pool 8 of the Upper Mississippi River on the basis of a few hydrological, physical, and geomorphic variables. Our model takes into consideration flow velocity, wind fetch, bathymetry, growing-season daily water level, and light extinction coefficient in the river (fig. 1) and calculates the probability of submersed aquatic vegetation existence in Pool 8 in individual 5- x 5-m grid cells. The model was calibrated using the data collected in 1998 (516 sites), 1999 (595 sites), and 2000 (649 sites) using a stratified random sampling protocol (Yin and others, 2000b). To validate the model, we chose the data from the Long Term Resource Monitoring Program (LTRMP) transect sampling in backwater areas (Rogers and Owens 1995; Yin and others, 2000a) and ran the model for each 5- x 5-m grid cell in every growing season from 1991 to 2001. We tallied all the cells and came up with an annual average percent frequency of submersed aquatic vegetation occurrence and compared the results with actual LTRMP survey data (fig. 2). Both a paired Student's test (P = 0.4620) and a Wilcoxon's two-sample test (P = 0.4738) did not contradict our null hypothesis that the model prediction and the sampling data are statistically the same. We have not found an effective statistical test to compare model-predicted spatial pattern with aerial photography geographic information, but we are satisfied with the model's outcome on the basis of visual inspection (fig. 3). A unique feature about this model is that a prediction can be made by the end of June each year; therefore, providing wildlife managers an assessment of current year vegetation growth condition 3 to 4 months ahead of the arrival of migrating waterfowl that feed on submersed aquatic vegetation. We are working with the LTRMP partnership to create a mechanism so that model predictions (fig. 4) can be updated annually and the results posted on the LTRMP Web site. Our model underestimated the prevalence of vegetation from 2001 to 2004. We speculate that the summer water level reduction conducted in 2001 and 2002 triggered vegetation responses that are outside the model's domain. Future enhancement of the model will incorporate the summer water level drawdown effects as well as the effects of growth conditions in previous years.

Open-File Report↗