Geology topics

Ryan J. Monello

Publications and source records attributed to Ryan J. Monello.

8 recordsLinked to original sources

USGS2025

3D habitat complexity and coral morphology modulate reef fish functional structure in a marine national park

The ongoing degradation of coral reef habitats is widely acknowledged to have adverse effects on the abundance and diversity of reef fish populations, yet the direct effects on ecosystem functions remain uncertain. This study used a quantitative approach to determine the mechanistic links between fish assemblages and ecological function. We investigated the effects of 3D habitat structure and coral morphology on the ecological, behavioral, and morphological functional traits of reef fish within a protected marine national park. Fish traits such as Gregariousness, Water Column Position, and Body Shape were identified to be highly influential in shaping the multidimensional fish functional space, which was categorized into 10 Fish Functional Groups (FFG). Furthermore, habitat complexity and coral morphology significantly explained the abundances of eight out of 10 FFG. Notably, the habitat complexity metrics of Slope and Surface Complexity, along with coral morphologies of Branching and Mounding types, emerged as the most influential habitat features across FFG. Pairing Compressiform species and Schooling Short/Deep species, for example, significantly increased in abundance on substrate with higher Slopes and increased percentages of branching coral cover. Additionally, Cryptic and Nocturnal species exhibited statistically significant associations with all coral morphologies and substrates with high trait values of Slope and Curvature. Elucidating ecological drivers of specific functional groups of reef fish is critical for determining how changes in reef composition and structure will alter fish assemblages. Broad scale patterns were also detected, suggesting that although structural complexity is important, live coral morphologies have a greater positive impact on reef fish functional groups. These findings have direct implications for conservation and monitoring efforts, offering valuable insights for predicting the impacts of environmental change on community dynamics and ecosystem functioning.

Hawaii↗

USGS2024

Population and spatial dynamics of desert bighorn sheep in Grand Canyon during an outbreak of respiratory pneumonia

Introduction: Terrestrial species in riverine ecosystems face unique constraints leading to diverging patterns of population structure, connectivity, and disease dynamics. Desert bighorn sheep ( Ovis canadensis nelsoni ) in Grand Canyon National Park, a large native population in the southwestern USA, offer a unique opportunity to evaluate population patterns and processes in a remote riverine system with ongoing anthropogenic impacts. We integrated non-invasive, invasive, and citizen-science methods to address questions on abundance, distribution, disease status, genetic structure, and habitat fragmentation. Methods: We compiled bighorn sightings collected during river trips by park staff, commercial guides, and private citizens from 2000–2018 and captured bighorn in 2010–2016 to deploy GPS collars and test for disease. From 2011–2015, we non-invasively collected fecal samples and genotyped them at 9–16 microsatellite loci for individual identification and genetic structure. We used assignment tests to evaluate genetic structure and identify subpopulations, then estimated gene flow and recent migration to evaluate fragmentation. We used spatial capture-recapture to estimate annual population size, distribution, and trends after accounting for spatial variation in detection with a resource selection function model. Results and discussion: From 2010–2018, 3,176 sightings of bighorn were reported, with sightings of 56–145 bighorn annually on formal surveys. From 2012–2016, bighorn exhibiting signs of respiratory disease were observed along the river throughout the park. Of 25 captured individuals, 56% were infected by Mycoplasma ovipneumoniae , a key respiratory pathogen, and 81% were recently exposed. Pellet sampling for population estimation from 2011–2015 yielded 1,250 genotypes and 453 individuals. We detected 6 genetic clusters that exhibited mild to moderate genetic structure ( F ST 0.022–0.126). The river, distance, and likely topography restricted recent gene flow, but we detected cross-river movements in one section via genetic recaptures, no subpopulation appeared completely isolated, and genetic diversity was among the highest reported. Recolonization of one large stretch of currently empty habitat appears limited by the constrained topology of this system. Annual population estimates ranged 536–552 (95% CrI range 451–647), lamb:ewe ratios varied, and no significant population decline was detected. We provide a multi-method sampling framework useful for sampling other wildlife in remote riverine systems.

Arizona↗

USGS2021

Population estimates and trends of three Maui Island-endemic Hawaiian Honeycreepers

Population monitoring is critical for informing the management and conservation of rare Hawaiian forest birds. In 2017, we used point-transect distance sampling methods to estimate population densities of birds on Haleakalā Volcano on east Maui island. We estimated the populations and ranges of three island-endemic Hawaiian honeycreepers, including the endangered ‘Ākohekohe ( Palmeria dolei ), the endangered Kiwikiu (Maui Parrotbill; Pseudonestor xanthophrys ), and the Maui ʻAlauahio ( Paroreomyza montana newtoni ). We examined population trends back to 1980, and our 2017 density estimates were the lowest ever recorded for each species. Most concerning was the status of Kiwikiu, with a 71% decline in population since 2001 to a current population of 157 (95% CI 44–312) birds. The population of ‘Ākohekohe similarly decreased by 78% to a current population of 1768 (1193–2411) birds. For both species, population declines were due to declines in density and contraction of ranges from lower elevations. Both species are now restricted to ranges of less than 3000 ha. We surveyed ~ 91% of the range of Maui ‘Alauahio and estimated a population of 99,060 (88,502–106,954) birds, a 41% decrease since the highest estimate in 1992. Contraction of ranges to higher elevations is consistent with evidence that the impacts of avian malaria are being exacerbated by global warming trends. Our results indicate that the landscape control of either avian malaria transmission or its vector ( Culex mosquitoes) will be a pre-requisite to preventing the extinction of endemic forest birds in Hawaii.

Hawaii↗

USGS2020

Genetic and environmental indicators of climate change vulnerability for desert bighorn sheep

Assessments of organisms’ vulnerability to potential climatic shifts are increasingly common. Such assessments are often conducted at the species level and focused primarily on the magnitude of anticipated climate change (i.e., climate exposure). However, wildlife management would benefit from population-level assessments that also incorporate measures of local or regional potential for organismal adaptation to change. Estimates of genetic diversity, gene flow, and landscape connectivity can address this need and complement climate exposure estimates to establish management priorities at broad to local scales. We provide an example of this holistic approach for desert bighorn sheep ( Ovis canadensis nelsoni ) within and surrounding lands administered by the U.S. National Park Service. We used genetic and environmental data from 62 populations across the southwestern U.S. to delineate genetic structure, evaluate relationships between genetic diversity and isolation, and estimate relative climate vulnerability for populations as a function of five variables associated with species’ responses to climate change: genetic diversity, genetic isolation, geographic isolation, forward climate velocity within a population’s habitat patch (a measure of geographic movement rate required for an organism to maintain constant climate conditions), and maximum elevation within the habitat patch (a measure of current climate stress, as lower maximum elevation is associated with higher temperature, lower precipitation, and lower population persistence). Genetic structure analyses revealed a high-level division between populations in southeastern Utah and populations in the remainder of the study area, which were further differentiated into four lower-level genetic clusters. Genetic diversity decreased with population isolation, whereas genetic differentiation increased, but these patterns were stronger for native populations than for translocated populations. Populations exhibited large variation in predicted vulnerability across the study area with respect to all variables, but native populations occupying relatively intact landscapes, such as Death Valley and Grand Canyon national parks, had the lowest overall vulnerability. These results provide local and regional context for conservation and management decisions regarding bighorn populations in a changing climate. Our study further demonstrates how assessments combining multiple factors could allow a more integrated response, such as increasing efforts to maintain connectivity and thus potential for adaptation in areas experiencing rapid climate change.

Arizona, California, Nevada, Utah↗

USGS2018

Applying a Bayesian weighted surveillance approach to detect chronic wasting disease in white‐tailed deer

Surveillance is critical for early detection of emerging and re‐emerging infectious diseases. Weighted surveillance leverages heterogeneity in infection risk to increase sampling efficiency. Here, we apply a Bayesian approach to estimate weights for 16 surveillance classes of white‐tailed deer in Wisconsin, USA, relative to hunter‐harvested yearling males. We used these weights to conduct a surveillance programme for detecting chronic wasting disease (CWD) in white‐tailed deer at Shenandoah National Park (SHEN) in Virginia, USA. Generally, for surveillance, risk of infection increased with age and was greater in males. Clinical suspect deer had the highest risk, with weight estimates of 33.33 and 9.09 for community‐reported and hunter‐reported suspect deer, respectively. Fawns had the lowest risk with an estimated weight of 0.001. We used surveillance weights for Wisconsin deer to determine sampling effort required to detect a CWD‐positive case in SHEN if prevalence in yearling males ≥0.025. The sampling required to detect CWD was 37–91 adult deer, depending on the adult male:female ratio in the surveillance stream. We collected rectal biopsies from 49 female and 21 male adult deer, and 10 additional samples from vehicle‐killed deer. CWD was not detected and we concluded with 95% probability that prevalence in the reference population (yearling males) was between 0.0% and 3.6%. Synthesis and applications . Our approach allows managers to estimate relative surveillance weights for different host classes and quantify limits of disease detection in real time when only a sample of animals from a population can be tested, resulting in considerable cost savings for agencies performing wildlife disease detection surveillance. Additionally, it provides a rigorous means of estimating prevalence limits when a disease/pathogen is not detected in a sample set. It is therefore applicable to other wildlife, domestic animal and human disease systems, which can be characterized by surveillance classes with heterogeneous probability of infection. This methodology is also extendable to other disciplines such as invasive species, environmental toxicology, and generally, any ecological question seeking to efficiently use scarce financial and human resources to maximize the detection probability of a rare event.

Journal of Applied Ecology↗

USGS2018

Estimating abundance of an open population with an N-mixture model using auxiliary data on animal movements

Accurate assessment of abundance forms a central challenge in population ecology and wildlife management. Many statistical techniques have been developed to estimate population sizes because populations change over time and space and to correct for the bias resulting from animals that are present in a study area but not observed. The mobility of individuals makes it difficult to design sampling procedures that account for movement into and out of areas with fixed jurisdictional boundaries. Aerial surveys are the gold standard used to obtain data of large mobile species in geographic regions with harsh terrain, but these surveys can be prohibitively expensive and dangerous. Estimating abundance with ground‐based census methods have practical advantages, but it can be difficult to simultaneously account for temporary emigration and observer error to avoid biased results. Contemporary research in population ecology increasingly relies on telemetry observations of the states and locations of individuals to gain insight on vital rates, animal movements, and population abundance. Analytical models that use observations of movements to improve estimates of abundance have not been developed. Here we build upon existing multi‐state mark–recapture methods using a hierarchical N ‐mixture model with multiple sources of data, including telemetry data on locations of individuals, to improve estimates of population sizes. We used a state‐space approach to model animal movements to approximate the number of marked animals present within the study area at any observation period, thereby accounting for a frequently changing number of marked individuals. We illustrate the approach using data on a population of elk ( Cervus elaphus nelsoni ) in Northern Colorado, USA. We demonstrate substantial improvement compared to existing abundance estimation methods and corroborate our results from the ground based surveys with estimates from aerial surveys during the same seasons. We develop a hierarchical Bayesian N‐mixture model using multiple sources of data on abundance, movement and survival to estimate the population size of a mobile species that uses remote conservation areas. The model improves accuracy of inference relative to previous methods for estimating abundance of open populations.

Ecological Applications↗

USGS2016

Seeded amplification of chronic wasting disease prions in nasal brushings and recto-anal mucosal associated lymphoid tissues from elk by real time quaking-induced conversion

Chronic wasting disease (CWD), a transmissible spongiform encephalopathy of cervids, was first documented nearly 50 years ago in Colorado and Wyoming and has since been detected across North America and the Republic of Korea. The expansion of this disease makes the development of sensitive diagnostic assays and antemortem sampling techniques crucial for the mitigation of its spread; this is especially true in cases of relocation/reintroduction or prevalence studies of large or protected herds, where depopulation may be contraindicated. This study evaluated the sensitivity of the real-time quaking-induced conversion (RT-QuIC) assay of recto-anal mucosa-associated lymphoid tissue (RAMALT) biopsy specimens and nasal brushings collected antemortem. These findings were compared to results of immunohistochemistry (IHC) analysis of ante- and postmortem samples. RAMALT samples were collected from populations of farmed and free-ranging Rocky Mountain elk ( Cervus elaphus nelsoni ; n = 323), and nasal brush samples were collected from a subpopulation of these animals ( n = 205). We hypothesized that the sensitivity of RT-QuIC would be comparable to that of IHC analysis of RAMALT and would correspond to that of IHC analysis of postmortem tissues. We found RAMALT sensitivity (77.3%) to be highly correlative between RT-QuIC and IHC analysis. Sensitivity was lower when testing nasal brushings (34%), though both RAMALT and nasal brush test sensitivities were dependent on both the PRNP genotype and disease progression determined by the obex score. These data suggest that RT-QuIC, like IHC analysis, is a relatively sensitive assay for detection of CWD prions in RAMALT biopsy specimens and, with further investigation, has potential for large-scale and rapid automated testing of antemortem samples for CWD.

Journal of Clinical Microbiology↗

USGS2013

Fifty years after Welles and Welles: Distribution and genetic structure of Desert Bighorn Sheep in Death Valley National Park

The status of desert bighorn sheep (Ovis canadensis nelsoni) populations in the mountains around Death Valley was first evaluated in 1938, shortly after designation of Death Valley National Monument. However, the most comprehensive evaluation of bighorn sheep in the region was conducted by Ralph and Florence Welles during 1955-1961. They documented patterns of use at water sources and other focal areas around Death Valley and roughly estimated numbers of bighorn sheep from observational data. Data collection on bighorn sheep in the area since that time has lacked a regional approach needed to address metapopulation questions.From 2011-2013, we evaluated bighorn activity at important water sources and other likely locations around Death Valley using remote cameras and observations of tracks, beds, sign, and bighorn sheep, and non-invasively collected genetic samples (fecal pellets and bones). Where possible, we revisited many of the water sources and other locations originally investigated by Welles and Welles (1961) and earlier researchers. We extracted DNA from fecal pellets, carcass tissue samples, and blood samples archived from earlier captures and genotyped them using highly variable genetic markers (15 microsatellite loci) with sufficient power to distinguish individuals and characterize gene flow and genetic structure. We also analyzed DNA samples collected from other bighorn sheep populations extending north to the White Mountains, west to the Inyo Mountains, south to the Avawatz Mountains, and southeast to the Clark Mountain Range, Kingston Range, and Spring Mountains of Nevada. We estimated genetic structure and recent gene flow among nearly all known populations of bighorn sheep in and around Death Valley National Park (DEVA), and used assignment tests to evaluate individual and population-level genetic structure to infer connectivity across the region. We found that bighorn sheep are still widely distributed in mountain ranges throughout DEVA, including many of the areas described by Welles and Welles (1961), although some use patterns appear to have changed and other areas still require resurvey. Gene flow was relatively high through some sections of fairly continuous habitat, such as the Grapevine and Funeral Mountains along the eastern side of Death Valley, but other populations were more isolated. Genetic diversity was relatively high throughout the park. Although southern Death Valley populations were genetically distinct from populations to the southeast, population assignment tests and recent gene flow estimates suggested that individuals occasionally migrate between those regions, indicating the potential for the recent outbreak of respiratory disease in the southern Mojave Desert to spread into the Death Valley system. We recommend careful monitoring of bighorn sheep using remote cameras to check for signs of respiratory disease in southeastern DEVA and ground surveys in the still-understudied southwestern part of DEVA.

Conference Paper↗