Cyclicity in Northern Bobwhites: A Time-Analytic Review of the Evidence

Cyclical behavior in wildlife populations, including northern bobwhite (Colinus virginianus), has long fascinated human observers. However, studies examining cyclicity of bobwhite abundance have yielded contradictory results. We reviewed evidence for periodic fluctuation in bobwhite abundance by studying 73 long-term time series. Our aim was to discern with time-series techniques whether cyclicity occurred in bobwhite abundance. We elucidated the frequency of occurrence, geographical distribution, and potential mechanisms responsible for cyclicity. Approximately one-half (n = 37) of the populations examined demonstrated cyclical behavior, with a period varying between 4 and 17 yrs. True cycles, consistent, significant fluctuations in abundance, were rare, occurring in only 3 time series. The predominant form of periodicity was of the phase-forgetting quasi-cycle type (n = 34). This phase-forgetting may have contributed to previous contradictory findings of cyclicity in this species. We reason cyclicity in bobwhite populations is caused by aperiodic environmental perturbations interacting with density-dependence. Cyclic bobwhite populations occupied the northern and western portion of the species’ range, where stochastic weather events regularly negatively influence bobwhite population dynamics. Bobwhite populations were non-cyclic in the relatively consistent climate of the southeastern United States, however, habitat fragmentation rather than climate may have contributed to the absence of cyclicity in this region

Survey of Diseases in Wild Turkeys in Arkansas

Nineteen dead wild turkeys were necropsied and 573 live wild turkeys were physically examined for pathological agents in Arkansas between 1992 and 1997 to determine the proximate role disease may play in declining wild populations in Arkansas. Necropsy of the dead wild turkeys identified avian pox and histomoniasis as the most common diseases (16% and 11% of necropsies, respectively). Avian pox was recorded from three major physiographic regions in the state (Ozark Highlands, Ouachita Mountains, Gulf Coastal Plain). One hen died of non-accidental crop impaction, the fifth occurrence observed in the southeastern United States. Another hen died after developing severe, focal necrotic dermatitis caused by a Penicillium sp. fungus, the first occurrence observed in wild turkeys. All live wild turkeys appeared free of gross signs of disease. We found diseases in wild turkeys in Arkansas are not uncommon and are more diverse than previously reported. Continued monitoring of disease in wild turkeys is therefore encouraged

Winter Habitat Associations of Blackbirds and Starlings Wintering in the South-Central United States

Birds can cause extensive crop damage in the United States. In some regions, depredating species comprise a substantial portion of the total avian population, emphasizing their importance both economically and ecologically. We used the National Audubon Society Christmas Bird Count data from the south-central United States and mixed-effects models to identify habitat factors associated with population trend and abundance for 5 species: red-winged blackbird (Agelaius phoeniceus), common grackle (Quiscalus quiscula), rusty blackbird (Euphagus carolinus), Brewer’s blackbird (Euphagus cyanocephalus), and European starling (Sturnus vulgaris). Overall, we found positive associations between bird abundance and agricultural land-cover for all species. Relationships between abundance and other land-cover types were species-specific, often with contrasting relationships among species. Likewise, we found no consistent patterns among abundance and climate. Of the 5 species, only red-winged blackbirds had a significant population trend in our study area, increasing annually by 2.4%. There was marginal evidence to suggest population increases for rusty blackbirds, whereas all other species showed no trend in population size within our study area. Our study provides managers who are interested in limiting crop damage in the south-central United States with novel information on habitat associations in the region that could be used to improve management and control action

Current And Future Land Use Around A Nationwide Protected Area Network

Land-use change around protected areas can reduce their effective size and limit their ability to conserve biodiversity because land-use change alters ecological processes and the ability of organisms to move freely among protected areas. The goal of our analysis was to inform conservation planning efforts for a nationwide network of protected lands by predicting future land use change. We evaluated the relative effect of three economic policy scenarios on land use surrounding the U.S. Fish and Wildlife Service\u27s National Wildlife Refuges. We predicted changes for three land-use classes (forest/range, crop/pasture, and urban) by 2051. Our results showed an increase in forest/range lands (by 1.9% to 4.7% depending on the scenario), a decrease in crop/pasture between 15.2% and 23.1%, and a substantial increase in urban land use between 28.5% and 57.0%. The magnitude of land-use change differed strongly among different USFWS administrative regions, with the most change in the Upper Midwestern US (approximately 30%), and the Southeastern and Northeastern US (25%), and the rest of the U.S. between 15 and 20%. Among our scenarios, changes in land use were similar, with the exception of our restricted-urban-growth\u27\u27 scenario, which resulted in noticeably different rates of change. This demonstrates that it will likely be difficult to influence land-use change patterns with national policies and that understanding regional land-use dynamics is critical for effective management and planning of protected lands throughout the U.S

Quasi-extinction risk and population targets for the Eastern, migratory population of monarch butterflies (Danaus plexippus)

The Eastern, migratory population of monarch butterflies (Danaus plexippus), an iconic North American insect, has declined by ~80% over the last decade. The monarch’s multi-generational migration between overwintering grounds in central Mexico and the summer breeding grounds in the northern U.S. and southern Canada is celebrated in all three countries and creates shared management responsibilities across North America. Here we present a novel Bayesian multivariate auto-regressive state-space model to assess quasi-extinction risk and aid in the establishment of a target population size for monarch conservation planning. We find that, given a range of plausible quasi-extinction thresholds, the population has a substantial probability of quasi-extinction, from 11–57% over 20 years, although uncertainty in these estimates is large. Exceptionally high population stochasticity, declining numbers, and a small current population size act in concert to drive this risk. An approximately 5-fold increase of the monarch population size (relative to the winter of 2014–15) is necessary to halve the current risk of quasi-extinction across all thresholds considered. Conserving the monarch migration thus requires active management to reverse population declines, and the establishment of an ambitious target population size goal to buffer against future environmentally driven variability

A General Modeling Framework for Describing Spatially Structured Population Dynamics

Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network‐based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life‐history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network‐based population is modeled with discrete time steps. Using both theoretical and real‐world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network‐based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance that comparative analyses are colored by model details rather than general principles

Developing population models with data from marked individuals

Population viability analysis (PVA) is a powerful tool for biodiversity assessments, but its use has been limited because of the requirements for fully specified population models such as demographic structure, densitydependence, environmental stochasticity, and specification of uncertainties. Developing a fully specified population model from commonly available data sources -notably, mark-recapture studies -remains complicated due to lack of practical methods for estimating fecundity, true survival (as opposed to apparent survival), natural temporal variability in both survival and fecundity, density-dependence in the demographic parameters, and uncertainty in model parameters. We present a general method that estimates all the key parameters required to specify a stochastic, matrix-based population model, constructed using a long-term mark-recapture dataset. Unlike standard mark-recapture analyses, our approach provides estimates of true survival rates and fecundities, their respective natural temporal variabilities, and density-dependence functions, making it possible to construct a population model for long-term projection of population dynamics. Furthermore, our method includes a formal quantification of parameter uncertainty for global (multivariate) sensitivity analysis. We apply this approach to 9 bird species and demonstrate the feasibility of using data from the Monitoring Avian Productivity and Survivorship (MAPS) program. Bias-correction factors for raw estimates of survival and fecundity derived from markrecapture data (apparent survival and juvenile:adult ratio, respectively) were non-negligible, and corrected parameters were generally more biologically reasonable than their uncorrected counterparts. Our method allows the development of fully specified stochastic population models using a single, widely available data source, substantially reducing the barriers that have until now limited the widespread application of PVA. This method is expected to greatly enhance our understanding of the processes underlying population dynamics and our ability to analyze viability and project trends for species of conservation concern

Current and Future Land Use around a Nationwide Protected Area Network

Land-use change around protected areas can reduce their effective size and limit their ability to conserve biodiversity because land-use change alters ecological processes and the ability of organisms to move freely among protected areas. The goal of our analysis was to inform conservation planning efforts for a nationwide network of protected lands by predicting future land use change. We evaluated the relative effect of three economic policy scenarios on land use surrounding the U.S. Fish and Wildlife Service’s National Wildlife Refuges. We predicted changes for three land-use classes (forest/range, crop/pasture, and urban) by 2051. Our results showed an increase in forest/range lands (by 1.9% to 4.7% depending on the scenario), a decrease in crop/pasture between 15.2% and 23.1%, and a substantial increase in urban land use between 28.5% and 57.0%. The magnitude of land-use change differed strongly among different USFWS administrative regions, with the most change in the Upper Midwestern US (approximately 30%), and the Southeastern and Northeastern US (25%), and the rest of the U.S. between 15 and 20%. Among our scenarios, changes in land use were similar, with the exception of our ‘‘restricted-urban-growth’’ scenario, which resulted in noticeably different rates of change. This demonstrates that it will likely be difficult to influence land-use change patterns with national policies and that understanding regional land-use dynamics is critical for effective management and planning of protected lands throughout the U.S

The Integrated Monarch Monitoring Program: From Design to Implementation

Steep declines in North American monarch butterfly (Danaus plexippus) populations have prompted continent-wide conservation efforts. While monarch monitoring efforts have existed for years, we lack a comprehensive approach to monitoring population vital rates integrated with habitat quality to inform adaptive management and effective conservation strategies. Building a geographically and ecologically representative dataset of monarchs and their habitat will improve these efforts. These data will help track long-term changes in the distribution and abundance of monarchs and their habitats, refine population and habitat models, and illuminate how conservation activities affect monarchs and their habitats. The Monarch Conservation Science Partnership developed the Integrated Monarch Monitoring Program (IMMP) to profile breeding habitats and their use by monarchs in North America. A spatially balanced random sampling framework guides site selection, while also allowing opportunistic inclusion of sites chosen by participants, such as conservation areas. The IMMP weaves new protocols together with those from existing monitoring programs to improve data compatibility for assessing milkweed (Asclepias spp.) density, nectar resources, monarch reproduction and survival, and adult monarch habitat use. Participants may select a protocol subset according to interests or local monitoring objectives, thereby maximizing contributions. Conservation partners, including public and private land managers, academic researchers, and citizen scientists contribute data to a national dataset available for analyses at multiple scales. We describe the program and its development, implementation elements that make the program robust and feasible, participation to date, and how IMMP data can advance research and conservation for monarchs, pollinators, and their habitats