Investigating the impact of invasive Asian carp on river otter diet and the native fish communities of Indiana

Invasive Asian carp (i.e., bighead and silver carp, Hypophthalmic molitric and hypophalmichthy nobilis), threaten native fish populations in Midwestern United States freshwater ecosystems. These species are primarily planktivorous, experience rapid growth rates, and have enhanced predator avoidance traits resulting in a competitive advantage over native fish species. The success of Asian carp may also threaten higher-level predators by altering prey availability, potentially causing a change in predator behavior and diet. Since the coinciding river otter (Lontra canadensis) reintroduction and Asian carp invasion in Indiana’s waterways in 1995, no studies have investigated the impact of Asian carp on higher- level predators. Our objective is to determine the role of Asian carp in the diet of a top predator in Indiana’s waterways, the North American river otter. To determine the impact of Asian carp in otter diet, we will be conducting diet analyses through two methods: gross fecal analysis and stable isotope analysis. We will compare otter diet in a carp-invaded watershed to the otter diet in a carp-free watershed. We are collecting scat at 2 different locations along the carp-invaded Tippecanoe River: Prophetstown State Park, YMCA Camp Tecumseh and 2 different locations in non-carp invaded waterways: Chain’O Lakes State Park and Pigeon River Fish and Wildlife Area. We hypothesize that river otters will select against invasive Asian carp in preference for native species, with which they have coevolved. This result would indicate an increase in predation pressure upon already reduced native fish populations, as well as a reduction in fitness of the predator from limited prey availability. If otters do prefer Asian carp, they may serve as an effective bio control for Asian carp while also creating a positive public perception of otters

Assessing the influence of socials calls on bat mist-netting success in North America

Since the introduction of the fungal disease White-Nose Syndrome in 2006, millions of North American bats have perished. For many species, the disease has caused over a 90 percent decline in abundance. With populations fluctuating as the pathogen spreads, biologists require improved methods of estimating bat demographics and abundance. Previous research indicates that mist netting success may be improved with the use of acoustic lures at mist-netting locations. Our research investigates which type of social calls improve the capture rates of North American bats, including the big brown bat (Eptesicus fuscus). Social call types used include antagonistic buzzes, distress calls, advertising calls, mother-to-offspring calls, and cohesion calls. We deployed acoustic lures at each netting site from 15 May 2017 to 15 August 2017. We created 5-hour long playlists using 10-minute blocks of each of the 5 call types, including a block of silence as control. We recorded the time of each bat capture to indicate the call block each individual entered the net. We utilized maximum likelihood analysis in program R to identify if call type had an influence on bat captures. Analysis indicated that European distress calls negatively impacted big brown bat captures. Overall, this suggests that researchers should utilize North American bat calls to improve capture rates of big brown bats

SEARCH: Spatially Explicit Animal Response to Composition of Habitat.

Complex decisions dramatically affect animal dispersal and space use. Dispersing individuals respond to a combination of fine-scale environmental stimuli and internal attributes. Individual-based modeling offers a valuable approach for the investigation of such interactions because it combines the heterogeneity of animal behaviors with spatial detail. Most individual-based models (IBMs), however, vastly oversimplify animal behavior and such behavioral minimalism diminishes the value of these models. We present program SEARCH (Spatially Explicit Animal Response to Composition of Habitat), a spatially explicit, individual-based, population model of animal dispersal through realistic landscapes. SEARCH uses values in Geographic Information System (GIS) maps to apply rules that animals follow during dispersal, thus allowing virtual animals to respond to fine-scale features of the landscape and maintain a detailed memory of areas sensed during movement. SEARCH also incorporates temporally dynamic landscapes so that the environment to which virtual animals respond can change during the course of a simulation. Animals in SEARCH are behaviorally dynamic and able to respond to stimuli based upon their individual experiences. Therefore, SEARCH is able to model behavioral traits of dispersing animals at fine scales and with many dynamic aspects. Such added complexity allows investigation of unique ecological questions. To illustrate SEARCH\u27s capabilities, we simulated case studies using three mammals. We examined the impact of seasonally variable food resources on the weight distribution of dispersing raccoons (Procyon lotor), the effect of temporally dynamic mortality pressure in combination with various levels of behavioral responsiveness in eastern chipmunks (Tamias striatus), and the impact of behavioral plasticity and home range selection on disperser mortality and weight change in virtual American martens (Martes americana). These simulations highlight the relevance of SEARCH for a variety of applications and illustrate benefits it can provide for conservation planning

An integrated assessment of the potential impacts of climate change on Indiana forests

Forests provide myriad ecosystem services, many of which are vital to local and regional economies. Consequently, there is a need to better understand how predicted changes in climate will impact forests dynamics and the implications of such changes for society as a whole. Here we focus on the impacts of climate change on Indiana forests, which are representative of many secondary growth broadleaved forests in the greater Midwest region in terms of their land use history and current composition. We find that predicted changes in climate for the state – warmer and wetter winters/springs and hotter and potentially drier summers – will dramatically shape forest communities, resulting in new assemblages of trees and wildlife that differ from forest communities of the past or present. Overall, suitable habitat is expected to decline for 17-29 percent of tree species and increase for 43-52 percent of tree species in the state, depending on the region and climate scenario. Such changes have important consequences for wildlife that depend on certain tree species or have ranges with strong sensitivities to climate. Additionally, these changes will have potential economic impacts on Indiana industries that depend on forest resources and products (both timber and non-timber). Finally, we offer some practical suggestions on how management may minimize the extent of climate-induced ecological impacts, and highlight a case study from a tree planting initiative currently underway in the Patoka River National Wildlife Refuge and Management Area

Spatial risk modeling of cattle depredation by black vultures in the midwestern United States

ock operations through depredation of stock are a cause of human‐wildlife conflict. Management of such conflict requires identifying environmental and non‐environmental factors specific to a wildlife species\u27 biology and ecology that influence the potential for livestock depredation to occur. Identification of such factors can improve understanding of the conditions placing livestock at risk. Black vultures (Coragyps atratus) have expanded their historical range northward into the midwestern United States. Concomitantly, an increase in concern among agricultural producers regarding potential black vulture attacks on livestock has occurred. We estimated area with greater or lesser potential for depredation of domestic cattle by black vultures across a 6‐state region in the midwestern United States using an ensemble of small models (ESM). Specifically, we identified landscape‐scale spatial factors, at a zip code resolution, associated with reported black vulture depredation on cattle in midwestern landscapes to predict future potential livestock depredation. We hypothesized that livestock depredation would be greatest in areas with intensive beef cattle production close to preferred black vulture habitat (e.g., areas with fewer old fields and early successional vegetation paired with more direct edge between older forest and agricultural lands). We predicted that the density of cattle within the county, habitat structure, and proximity to anthropogenic landscape features would be the strongest predictors of black vulture livestock‐depredation risk. Our ESM estimated the relative risk of black vulture‐cattle depredation to be between 0.154–0.631 across our entire study area. Consistent with our hypothesis, areas of greatest predicted risk of depredation correspond with locations that are favorable to vulture life‐history requirements and increased potential to encounter livestock. Our results allow wildlife managers the ability to predict where black vulture depredation of cattle is more likely to occur in the future. It is in these areas where extension and outreach efforts aimed at mitigating this conflict should be focused. Researchers and wildlife managers interested in developing or employing tools aimed at mitigating livestock‐vulture conflicts can also leverage our results to select areas where depredation is most likely to occur

Indiana\u27s Future Forests: A Report from the Indiana Climate Change Impacts Assessment

Over the next century, rising temperatures and changing precipitation patterns across the Midwest will likely have profound consequences for Indiana’s forests. Such changes include shifts in the distributions and abundances of trees, understory plants and wildlife, as well as changes to the environmental, economic and cultural benefits these forests provide. This report from the Indiana Climate Change Impacts Assessment (IN CCIA) examines the direct and indirect impacts that climate change is expected to have on Indiana’s forests. The report specifically addresses forest regeneration, forest composition, tree growth and harvest, wildlife habitat and forest products

The effects of spatial legacies following shifting management practices and fire on boreal forest age structure

Forest age structure and its spatial arrangement are important elements of sustainable forestry because of their effects on biodiversity and timber availability. Forest management objectives that include specific forest age structure may not be easily attained due to constraints imposed by the legacies of historical management and natural disturbance. We used a spatially explicit stochastic model to explore the synergetic effects of forest management and fire on boreal forest age structure. Specifically, we examined (1) the duration of spatial legacies of different management practices in the boreal forest, (2) how multiple shifts in management practices affect legacy duration and the spatial trajectories of forest age structure, and (3) how fire influences legacy duration and pattern development in combination with harvesting. Results based on 30 replicates of 500 years for each scenario indicate that (1) spatial legacies persist over 200 years and the rate at which legacies are overcome depends on whether new management targets are in synchrony with existing spatial pattern; (2) age specific goals were met faster after multiple management shifts due to the similar spatial scale of the preceding management types; (3) because large fires can erase the spatial pattern created by smaller disturbances, scenarios with fire had shorter lags than scenarios without fire. These results suggest that forest management goals can be accelerated by applying management at a similar spatial scale as existing spatial patterns. Also, management planning should include careful consideration of historical management as well as current and likely future disturbances

Genetic Overlap Between Alzheimer’s Disease and Bipolar Disorder Implicates the MARK2 and VAC14 Genes

Background: Alzheimer's disease (AD) and bipolar disorder (BIP) are complex traits influenced by numerous common genetic variants, most of which remain to be detected. Clinical and epidemiological evidence suggest that AD and BIP are related. However, it is not established if this relation is of genetic origin. Here, we applied statistical methods based on the conditional false discovery rate (FDR) framework to detect genetic overlap between AD and BIP and utilized this overlap to increase the power to identify common genetic variants associated with either or both traits. Methods: We obtained genome wide association studies data from the International Genomics of Alzheimer's Project part 1 (17,008 AD cases and 37,154 controls) and the Psychiatric Genetic Consortium Bipolar Disorder Working Group (20,352 BIP cases and 31,358 controls). We used conditional QQ-plots to assess overlap in common genetic variants between AD and BIP. We exploited the genetic overlap to re-rank test-statistics for AD and BIP and improve detection of genetic variants using the conditional FDR framework. Results: Conditional QQ-plots demonstrated a polygenic overlap between AD and BIP. Using conditional FDR, we identified one novel genomic locus associated with AD, and nine novel loci associated with BIP. Further, we identified two novel loci jointly associated with AD and BIP implicating the MARK2 gene (lead SNP rs10792421, conjunctional FDR=0.030, same direction of effect) and the VAC14 gene (lead SNP rs11649476, conjunctional FDR=0.022, opposite direction of effect). Conclusions: We found polygenic overlap between AD and BIP and identified novel loci for each trait and two jointly associated loci. Further studies should examine if the shared loci implicating the MARK2 and VAC14 genes could explain parts of the shared and distinct features of AD and BIP

Bipolar multiplex families have an increased burden of common risk variants for psychiatric disorders.

Multiplex families with a high prevalence of a psychiatric disorder are often examined to identify rare genetic variants with large effect sizes. In the present study, we analysed whether the risk for bipolar disorder (BD) in BD multiplex families is influenced by common genetic variants. Furthermore, we investigated whether this risk is conferred mainly by BD-specific risk variants or by variants also associated with the susceptibility to schizophrenia or major depression. In total, 395 individuals from 33 Andalusian BD multiplex families (166 BD, 78 major depressive disorder, 151 unaffected) as well as 438 subjects from an independent, BD case/control cohort (161 unrelated BD, 277 unrelated controls) were analysed. Polygenic risk scores (PRS) for BD, schizophrenia (SCZ), and major depression were calculated and compared between the cohorts. Both the familial BD cases and unaffected family members had higher PRS for all three psychiatric disorders than the independent controls, with BD and SCZ being significant after correction for multiple testing, suggesting a high baseline risk for several psychiatric disorders in the families. Moreover, familial BD cases showed significantly higher BD PRS than unaffected family members and unrelated BD cases. A plausible hypothesis is that, in multiplex families with a general increase in risk for psychiatric disease, BD development is attributable to a high burden of common variants that confer a specific risk for BD. The present analyses demonstrated that common genetic risk variants for psychiatric disorders are likely to contribute to the high incidence of affective psychiatric disorders in the multiplex families. However, the PRS explained only part of the observed phenotypic variance, and rare variants might have also contributed to disease development

The genetics of the mood disorder spectrum:genome-wide association analyses of over 185,000 cases and 439,000 controls

Background Mood disorders (including major depressive disorder and bipolar disorder) affect 10-20% of the population. They range from brief, mild episodes to severe, incapacitating conditions that markedly impact lives. Despite their diagnostic distinction, multiple approaches have shown considerable sharing of risk factors across the mood disorders. Methods To clarify their shared molecular genetic basis, and to highlight disorder-specific associations, we meta-analysed data from the latest Psychiatric Genomics Consortium (PGC) genome-wide association studies of major depression (including data from 23andMe) and bipolar disorder, and an additional major depressive disorder cohort from UK Biobank (total: 185,285 cases, 439,741 controls; non-overlapping N = 609,424). Results Seventy-three loci reached genome-wide significance in the meta-analysis, including 15 that are novel for mood disorders. More genome-wide significant loci from the PGC analysis of major depression than bipolar disorder reached genome-wide significance. Genetic correlations revealed that type 2 bipolar disorder correlates strongly with recurrent and single episode major depressive disorder. Systems biology analyses highlight both similarities and differences between the mood disorders, particularly in the mouse brain cell-types implicated by the expression patterns of associated genes. The mood disorders also differ in their genetic correlation with educational attainment – positive in bipolar disorder but negative in major depressive disorder. Conclusions The mood disorders share several genetic associations, and can be combined effectively to increase variant discovery. However, we demonstrate several differences between these disorders. Analysing subtypes of major depressive disorder and bipolar disorder provides evidence for a genetic mood disorders spectrum