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At least 1,693 records · Page 94Linked to original sources
USGS2010

Simultaneous modeling of habitat suitability, occupancy, and relative abundance: African elephants in Zimbabwe

The recent development of statistical models such as dynamic site occupancy models provides the opportunity to address fairly complex management and conservation problems with relatively simple models. However, surprisingly few empirical studies have simultaneously modeled habitat suitability and occupancy status of organisms over large landscapes for management purposes. Joint modeling of these components is particularly important in the context of management of wild populations, as it provides a more coherent framework to investigate the population dynamics of organisms in space and time for the application of management decision tools. We applied such an approach to the study of water hole use by African elephants in Hwange National Park, Zimbabwe. Here we show how such methodology may be implemented and derive estimates of annual transition probabilities among three dry-season states for water holes: (1) unsuitable state (dry water holes with no elephants); (2) suitable state (water hole with water) with low abundance of elephants; and (3) suitable state with high abundance of elephants. We found that annual rainfall and the number of neighboring water holes influenced the transition probabilities among these three states. Because of an increase in elephant densities in the park during the study period, we also found that transition probabilities from low abundance to high abundance states increased over time. The application of the joint habitat–occupancy models provides a coherent framework to examine how habitat suitability and factors that affect habitat suitability influence the distribution and abundance of organisms. We discuss how these simple models can further be used to apply structured decision-making tools in order to derive decisions that are optimal relative to specified management objectives. The modeling framework presented in this paper should be applicable to a wide range of existing data sets and should help to address important ecological, conservation, and management problems that deal with occupancy, relative abundance, and habitat suitability.

Hwange National Park↗
USGS2010

A consumer-resource approach to the density-dependent population dynamics of mutualism

Like predation and competition, mutualism is now recognized as a consumer resource (C-R) interaction, including, in particular, bi-directional (e.g., coral, plant- mycorrhizae) and uni-directional (e.g., ant-plant defense, plant-pollinator) C-R mutualisms. Here, we develop general theory for the density-dependent population dynamics of mutualism based on the C-R mechanism of interspecific interaction. To test the influence of C-R interactions on the dynamics and stability of bi- and uni-directional C-R mutualisms, we developed simple models that link consumer functional response of one mutualistic species with the resources supplied by another. Phase-plane analyses show that the ecological dynamics of C-R mutualisms are stable in general. Most transient behavior leads to an equilibrium of mutualistic coexistence, at which both species densities are greater than in the absence of interactions. However, due to the basic nature of C-R interactions, certain density-dependent conditions can lead to C-R dynamics characteristic of predator-prey interactions, in which one species overexploits and causes the other to go extinct. Consistent with empirical phenomena, these results suggest that the C-R interaction can provide a broad mechanism for understanding density-dependent population dynamics of mutualism. By unifying predation, competition, and mutualism under the common ecological framework of consumer-resource theory, we may also gain a better understanding of the universal features of interspecific interactions in general.

Ecology↗
USGS2007

Mountain Lions of the Flagstaff Uplands: 2003-2006 Progress Report

Executive Summary Stakeholders in management of mountain lions in the Flagstaff Uplands of northern Arizona have expressed increasing concern about both potential impacts of humans on lions and potential risks posed by lions to humans. A series of human-mountain lion encounters during 2000-2001 on Mt. Elden, immediately adjacent to Flagstaff, and similar incidents during 2004 near Tucson brought increased attention to management of human safety in mountain lion range. These human-centered concerns, together with long-standing questions about how the human infrastructure centered on Flagstaff might be affecting lion movements led us to initiate a mountain lion study in 2003 which we plan to continue through 2009. Our study focuses on movements and other behaviors of mountain lions, with the goal of providing information that can be used to increase human safety, decrease human impacts, and, overall, provide insight into the ecology of lions in this region. To serve this goal, we have focused on collecting data that will be the basis of explanatory models that can provide spatially-explicit predictions of mountain lion activity, specify the effects of human facilities, such as highways and urban areas, and provide insight into when, where, and how often different kinds of lions kill different kinds of prey. During 2003-2006, we captured six female and five male mountain lions in the Flagstaff Uplands, 10 of which we fitted with collars that collected up to six high-precision GPS fixes per day, transmitted daily to our offices via Argos satellites. This timely delivery of data allowed us to visit kill sites and other foci of localized activity to collect detailed information on lion behavior. By June 2006 we had obtained 9357 GPS locations and visited 394 sites, at which we documented 218 kills, 165 of which were by five females and 53 by five males. These data were the basis for preliminary analyses presented in this report. All lions during all seasons exhibited a strong selection for rough terrain and forest or woodland cover. Females differed from males by selecting more strongly for intermediate, rather than extreme, levels of terrain roughness, by selecting more strongly for chaparral vegetation and related rocky areas during winter, and by not selecting as strongly for areas near water sources. Overall, lions collared during this study strongly avoided flat open areas in private ownership. Male but not female lions exhibited pronounced selection for National Park Service jurisdictions. Both males and females year-round avoided residential areas and a zone outward to about 1-3 km and, when within this zone, moved more slowly and with less change in direction compared to when farther away. Collared lions have so far rarely crossed paved highways of any description - orders of magnitude less often than expected by chance. We observed only 3 crossings of an interstate highway, all on I17 and none on I40. Elk comprised the majority (52%) of kills by lions in our study, followed by mule deer (46%), and small mammals (15%). Adults comprised most of the mule deer kills (68%) and mesocarnivores, primarily coyotes (n = 21), comprised 73% of smaller prey. Calf and short-yearling elk comprised the largest single category of kills (29%). In addition to kills, we documented seven instances of scavenging, involving four different lions. Females differed from males by killing more mule deer and virtually all of the mesocarnivores, and by killing fewer elk of all ages. Intervals between kills averaged between 144 hrs (young females) to 221 hours (adult females), whereas average time spent on a kill ranged from 19 hrs (adult males) to 40 hrs (young males). Carcass mass had a strong effect on likelihood that a lion would bury or relocate a kill, the percentage of edibles consumed, and overall time spent feeding. Time spent feeding and likelihoods of carcass burial and relocation all peaked at intermediate carcass masses, suggesting an optimal mass in the range of 50-150 kg, likely dictated as much by handling efficiencies and competition from other scavengers as by a lion's shear ability to kill prey. Adult male lions exhibited a life strategy distinctly different from all other sex-age classes that entailed moving more rapidly over larger areas, and spending less time on kills in which they invested less energy handling, but from which they consumed tissue at a higher sustained rate.

Open-File Report↗
USGS2022

Lessons learned from wetlands research at the Cottonwood Lake Study Area, Stutsman County, North Dakota, 1967–2021

Depressional wetlands in the Prairie Pothole Region of North America have a long history of investigation owing to their importance in maintaining migratory-bird populations, especially waterfowl. One area of particularly intensive study is the Cottonwood Lake study area in Stutsman County, North Dakota. Studies at the Cottonwood Lake study area began in 1967 and continue through the present (2022). During this period of scientific discovery, meteorological conditions at the Cottonwood Lake study area varied greatly and included one of the most severe droughts of the 20th century and one of the wettest periods in the past 500 years. Persistent wet conditions that began in 1993 have contributed to state changes in many of the study area’s larger wetlands to lake-like conditions, whereas the smaller wetlands returned to seasonally ponded conditions during relatively dry years interspersed within the longer-term wet period. Additionally, some nonwetland areas of the study area developed wetland plant, hydrology, and soil characteristics during the 1993-to-present (2022) wet period. The persistently high stages of water in the larger wetlands since 1993 contributed to a buildup of dissolved solids and increases in salinity with time following an initial decrease in salinity caused by the dilution of dissolved solids within a larger volume of water. During 2021, drought conditions similar to the 1988 to 1992 period may develop if conditions persist. However, meteorological changes during the past 30 years have persisted long enough to be considered a change in climate conditions at the study area and, if such wet conditions continue, would represent a change from conditions that occurred in the past two millennia. During the period of study covered in this report (1967–2021), biotic communities responded in a variety of ways to subtle and marked changes in ponded-water depths, permanence, and salinity among the different wetland types in the study area. This report provides background information on the Cottonwood Lake study area and its context within the Prairie Pothole Region, documents techniques used to quantify environmental conditions and biotic communities, describes major trends that have been observed, presents significant findings as “lessons learned,” discusses recent modeling advances, and highlights key messages to managers. The Wetland Continuum concept was used as a framework to place research findings within an ecological context and to highlight the dynamic nature of prairie-pothole wetland ecosystems.

North Dakota↗
USGS1982

Water-quality assessment of White River between Lake Sequoyah and Beaver Reservoir, Washington County, Arkansas

The Arkansas Department of Pollution Control and Ecology and U.S. Geological Survey conducted a water quality assessment be made of the White River and, that a steady-state digital model be calibrated and used as a tool for simulating changes in nutrient loading. The city of Fayetteville 's wastewater-treatment plant is the only point-source discharger of waste effluent to the river. Data collected during synoptic surveys downstream from the wastewater-treatment plan indicate that temperature, dissolved oxygen, dissolved solids, un-ionized ammonia, total phosphorus, and floating solids and depositable materials did not meet Arkansas stream standards. Nutrient loadings below the treatment plant result in dissolved oxygen concentrations as low as 0.0 milligrams per liter. Biological surveys found low macroinvertebrate organism diversity and numerous dead fish. Computed dissolved oxygen deficits indicate that benthic demands are the most significant oxygen sinks in the river downstream from the wastewater-treatment plant. Benthic oxygen demands range from 2.8 to 11.0 grams per meter squared per day. Model projections indicate that for 7-day, 10-year low-flow conditions and water temperature of 29 degrees Celsius, daily average dissolved oxygen concentrations of 6.0 milligrams per liter can be maintained downstream from the wastewater-treatment plant if effluent concentrations of ultimate carbonaceous biochemical oxygen demand and ammonia nitrogen are 7.5 (5.0 5-day demand) and 2 milligrams per liter respectively. Model sensitivity analysis indicate that dissolved oxygen concentrations were most sensitive to changes in stream temperature. (USGS)

Water-Resources Investigations Report↗
USGS2020

Carrying capacity of a population diffusing in a heterogeneous environment

The carrying capacity of the environment for a population is one of the key concepts in ecology and it is incorporated in the growth term of reaction-diffusion equations describing populations in space. Analysis of reaction-diffusion models of populations in heterogeneous space have shown that, when the maximum growth rate and carrying capacity in a logistic growth function vary in space, conditions exist for which the total population size at equilibrium (i) exceeds the total population that which would occur in the absence of diffusion and (ii) exceeds that which would occur if the system were homogeneous and the total carrying capacity, computed as the integral over the local carrying capacities, was the same in the heterogeneous and homogeneous cases. We review here work over the past few years that has explained these apparently counter-intuitive results in terms of the way input of energy or another limiting resource (e.g., a nutrient) varies across the system. We report on both mathematical analysis and laboratory experiments confirming that total population size in a heterogeneous system with diffusion can exceed that in the system without diffusion. We further report, however, that when the resource of the population in question is explicitly modeled as a coupled variable, as in a reaction-diffusion chemostat model rather than a model with logistic growth, the total population in the heterogeneous system with diffusion cannot exceed the total population size in the corresponding homogeneous system in which the total carrying capacities are the same.

Mathematics and Computers in Modern Science - Acou↗
USGS2006

Proximate and landscape factors influence grassland bird distributions

Ecologists increasingly recognize that birds can respond to features well beyond their normal areas of activity, but little is known about the relative importance of landscapes and proximate factors or about the scales of landscapes that influence bird distributions. We examined the influences of tree cover at both proximate and landscape scales on grassland birds, a group of birds of high conservation concern, in the Sheyenne National Grassland in North Dakota, USA. The Grassland contains a diverse array of grassland and woodland habitats. We surveyed breeding birds on 2015 100 m long transect segments during 2002 and 2003. We modeled the occurrence of 19 species in relation to habitat features (percentages of grassland, woodland, shrubland, and wetland) within each 100-m segment and to tree cover within 200-1600 m of the segment. We used information-theoretic statistical methods to compare models and variables. At the proximate scales, tree cover was the most important variable, having negative influences on 13 species and positive influences on two species. In a comparison of multiple scales, models with only proximate variables were adequate for some species, but models combining proximate with landscape information were best for 17 of 19 species. Landscape-only models were rarely competitive. Combined models at the largest scales (800-1600 m) were best for 12 of 19 species. Seven species had best models including 1600-m landscapes plus proximate factors in at least one year. These were Wilson's Phalarope (Phalaropus tricolor), Sedge Wren (Cistothorus platensis), Field Sparrow (Spizella pusilla), Grasshopper Sparrow (Ammodramus savannarum), Bobolink (Dolychonix oryzivorus), Red-winged Blackbird (Agelaius phoeniceus), and Brown-headed Cowbird (Molothrus ater). These seven are small-bodied species; thus larger-bodied species do not necessarily respond most to the largest landscapes. Our findings suggest that birds respond to habitat features at a variety of scales. Models with only landscape-scale tree cover were rarely competitive, indicating that broad-scale modeling alone, such as that based solely on remotely sensed data, is likely to be inadequate in explaining species distributions. ?? 2006 by the Ecological Society of America.

Ecological Applications↗
USGS2017

Marine infectious disease ecology

To put marine disease impacts in context requires a broad perspective on the roles infectious agents have in the ocean. Parasites infect most marine vertebrate and invertebrate species, and parasites and predators can have comparable biomass density, suggesting they play comparable parts as consumers in marine food webs. Although some parasites might increase with disturbance, most probably decline as food webs unravel. There are several ways to adapt epidemiological theory to the marine environment. In particular, because the ocean represents a three-dimensional moving habitat for hosts and parasites, models should open up the spatial scales at which infective stages and host larvae travel. In addition to open recruitment and dimensionality, marine parasites are subject to fishing, filter feeders, dosedependent infection, environmental forcing, and death-based transmission. Adding such considerations to marine disease models will make it easier to predict which infectious diseases will increase or decrease in a changing ocean.

Annual Review of Ecology, Evolution, and Systemati↗
USGS2018

Monitoring dynamic spatio-temporal ecological processes optimally

Population dynamics vary in space and time. Survey designs that ignore these dynamics may be inefficient and fail to capture essential spatio‐temporal variability of a process. Alternatively, dynamic survey designs explicitly incorporate knowledge of ecological processes, the associated uncertainty in those processes, and can be optimized with respect to monitoring objectives. We describe a cohesive framework for monitoring a spreading population that explicitly links animal movement models with survey design and monitoring objectives. We apply the framework to develop an optimal survey design for sea otters in Glacier Bay. Sea otters were first detected in Glacier Bay in 1988 and have since increased in both abundance and distribution; abundance estimates increased from 5 otters to >5,000 otters, and they have spread faster than 2.7 km/yr. By explicitly linking animal movement models and survey design, we are able to reduce uncertainty associated with forecasting occupancy, abundance, and distribution compared to other potential random designs. The framework we describe is general, and we outline steps to applying it to novel systems and taxa.

Ecology↗
USGS2019

Using the beta distribution to analyze plant cover data

Most plant species are spatially aggregated. Local demographic and ecological processes (e.g. vegetative growth and limited seed dispersal) result in a clustered spatial pattern within an environmentally homogenous area. Spatial aggregation should be considered when modelling plant abundance data. Commonly, plant abundance is quantified by measuring cover within multiple areal plots or along multiple lines randomly placed within a study area. A common practice for analyzing plant cover is to use statistical methods that rely on the normal distribution for quantifying uncertainty. This is problematic because plant cover data tend to be left‐skewed (J‐shaped), right skewed (L‐shaped) or U‐shaped and, therefore, commonly violate classic statistical assumptions, such as normality. We outline statistical analyses that explicitly account for spatial aggregation by assuming that plant cover is beta‐distributed. The beta distribution is a flexible choice because within the open unit interval it can take on a wide range of shapes (L, J, U, or a bell‐shaped). We discuss and introduce extensions to the beta distribution that address common analysis issues encountered in plant cover datasets, such as i) the treatment of zero and one cover values, ii) hierarchical data structures, and iii) observations errors. For heuristic purposes, we focus on single species analyses, but we demonstrate how the outlined methods can be generalized to more species. The assumption that plant cover is beta‐distributed allows us to estimate the degree of spatial aggregation, and the ecological significance of this new knowledge is discussed. We provide a summary of available software for analyses (emphasizing standard R packages) and include worked examples and a simulation study comparing analysis options as supplemental information. Synthesis . Previously, the state of the statistical software made it practically difficult for empirical plant ecologists to analyze their cover data correctly, but new theory and R‐packages have been developed, and this difficulty no longer exists. We recommend that empirical plant ecologists embrace the new statistical possibilities for exploring the exciting ecological features in spatial variation of plant cover.

Journal of Ecology↗
USGS2013

The LANDFIRE Refresh strategy: updating the national dataset

The LANDFIRE Program provides comprehensive vegetation and fuel datasets for the entire United States. As with many large-scale ecological datasets, vegetation and landscape conditions must be updated periodically to account for disturbances, growth, and natural succession. The LANDFIRE Refresh effort was the first attempt to consistently update these products nationwide. It incorporated a combination of specific systematic improvements to the original LANDFIRE National data, remote sensing based disturbance detection methods, field collected disturbance information, vegetation growth and succession modeling, and vegetation transition processes. This resulted in the creation of two complete datasets for all 50 states: LANDFIRE Refresh 2001, which includes the systematic improvements, and LANDFIRE Refresh 2008, which includes the disturbance and succession updates to the vegetation and fuel data. The new datasets are comparable for studying landscape changes in vegetation type and structure over a decadal period, and provide the most recent characterization of fuel conditions across the country. The applicability of the new layers is discussed and the effects of using the new fuel datasets are demonstrated through a fire behavior modeling exercise using the 2011 Wallow Fire in eastern Arizona as an example.

Fire Ecology↗
USGS2018

Quantifying uncertainty and tradeoffs in resilience assessments

Several frameworks have been developed to assess the resilience of social-ecological systems, but most require substantial data inputs, time, and technical expertise. Stakeholders and practitioners often lack the resources for such intensive efforts. Furthermore, most end with problem framing and fail to explicitly address trade-offs and uncertainty. To remedy this gap, we developed a rapid survey assessment that compares the relative resilience of social-ecological systems with respect to a number of resilience properties. This approach generates large amounts of information relative to stakeholder inputs. We targeted four stakeholder categories: government (policy, regulation, management), end users (farmers, ranchers, landowners, industry), agency/public science (research, university, extension), and NGOs (environmental, citizen, social justice) in four North American watersheds, to assess social-ecological resilience through surveys. Conceptually, social-ecological systems are comprised of components ranging from strictly human to strictly ecological, but that relate directly or indirectly to one another. They have soft boundaries and several important dimensions or axes that together describe the nature of social-ecological interactions, e.g., variability, diversity, modularity, slow variables, feedbacks, capital, innovation, redundancy, and ecosystem services. There is no absolute measure of resilience, so our design takes advantage of cross-watershed comparisons and therefore focuses on relative resilience. Our approach quantifies and compares the relative resilience across watershed systems and potential trade-offs among different aspects of the social-ecological system, e.g., between social, economic, and ecological contributions. This approach permits explicit assessment of several types of uncertainty (e.g., self-assigned uncertainty for stakeholders; uncertainty across respondents, watersheds, and subsystems), and subjectivity in perceptions of resilience among key actors and decision makers and provides an efficient way to develop the mental models that inform our stakeholders and stakeholder categories.

Ecology and Society↗
USGS2019

Natural resource management decision-making under climate uncertainty: Building social-ecological resilience in southwestern Colorado

The goal of this project was to facilitate climate change adaptation that contributes to social-ecological resilience, ecosystem and species conservation, and sustainable human communities in southwestern Colorado. The team developed and piloted integrated adaptation planning tools and principles that merge the strengths of the iterative scenario process, the Adaptation for Conservation Targets (ACT) planning framework, institutional analysis, and climate modeling. These tools and principles generated practical strategies and scientific knowledge to advance climate change adaptation in both the Gunnison River Basin and San Juan River Basin and, potentially, other landscapes. A key objective of this project was to work with decision-makers to develop social-ecological adaptation strategies and coordinate actions to reduce the impacts of a changing climate on nature and people. To accomplish this, the project blended science (biophysical and social) and participatory approaches to integrate expert knowledge, land management decision making, and local needs. These adaptation strategies and their creation process were documented by the project team to assist communities and scientists elsewhere who are grappling with the challenges posed by climate change.

Colorado↗
USGS2009

Methods for assessing movement path recursion with application to African buffalo in South Africa

Recent developments of automated methods for monitoring animal movement, e.g., global positioning systems (GPS) technology, yield high-resolution spatiotemporal data. To gain insights into the processes creating movement patterns, we present two new techniques for extracting information from these data on repeated visits to a particular site or patch ("recursions"). Identification of such patches and quantification of recursion pathways, when combined with patch-related ecological data, should contribute to our understanding of the habitat requirements of large herbivores, of factors governing their space-use patterns, and their interactions with the ecosystem. We begin by presenting output from a simple spatial model that simulates movements of large-herbivore groups based on minimal parameters: resource availability and rates of resource recovery after a local depletion. We then present the details of our new techniques of analyses (recursion analysis and circle analysis) and apply them to data generated by our model, as well as two sets of empirical data on movements of African buffalo (Syncerus coffer): the first collected in Klaserie Private Nature Reserve and the second in Kruger National Park, South Africa. Our recursion analyses of model outputs provide us with a basis for inferring aspects of the processes governing the production of buffalo recursion patterns, particularly the potential influence of resource recovery rate. Although the focus of our simulations was a comparison of movement patterns produced by different resource recovery rates, we conclude our paper with a comprehensive discussion of how recursion analyses can be used when appropriate ecological data are available to elucidate various factors influencing movement. Inter alia, these include the various limiting and preferred resources, parasites, and topographical and landscape factors. ?? 2009 by the Ecological Society of America.

Ecology↗
USGS2011

Feeding ecology and energetics

Successful management of walleye and sauger populations often requires a detailed knowledge of prey resources. As with many fishes, diets of juvenile Sander spp. are often different than those of adult fish and can have important implications for growth and survival. Similarly, spatial and temporal variation in diet composition can contribute to variation in growth and production of Sander populations. Thus, management efforts (e.g., stocking) aimed at enhancing walleye and sauger populations benefit from the knowledge and tools to effectively quantify feeding patterns. Today, fisheries managers face a myriad of challenges posed by nonnative species, eutrophication, climate change, and water availability, to name just a few. As a result, knowledge about prey use, energetics, and effects of Sander populations on food web structure has increased dramatically in the last 30 years. Experimental work with larval and juvenile walleyes has provided new insights into factors affecting growth and survival during early life stages (see Chapter 7) that has benefitted management and propagation efforts. Similarly, contemporary analytical approaches, such as bioenergetics modeling and stable isotope analysis, have improved our understanding of walleye foraging behavior and provided new tools for exploring trophic interactions. In this chapter, we review the general feeding ecology of walleye and sauger and highlight contemporary approaches for quantifying energy acquisition and trophic interactions.

Book chapter↗
USGS2020

Report on the workshop ‘Next Steps in Developing Nature Futures’

The workshop ‘New Narratives for Nature: operationalizing the IPBES Nature Futures Scenarios’ was organised by the IPBES task force on scenarios and models and hosted by the Institute for Global Environmental Strategies (IGES), with support from the research team on “Predicting and Assessing Natural Capital and Ecosystem Services through an Integrated Social-Ecological Systems Approach (PANCES)” based at the University of Tokyo, the Research Institute for Humanity and Nature (RIHN), and the United Nations University, with generous financial support from the Ministry of the Environment of Japan. Due to the COVID-19 virus outbreak, most task force members participated through virtual means, with a subset of task force members meeting in person in Japan. The aim of the workshop was to build on the Nature Futures Framework (NFF) and on the ‘nature futures’ participatory scenario-development work initiated by the IPBES expert group on scenarios and models in the first IPBES work programme. This workshop aims to further elaborate the pre-workshop scenario narratives and to enrich discussions on the NFF. The workshop also served to start working on a more detailed task force work plan. These aims were achieved through: • Task force sessions on the further formulation of the Nature Futures narratives. • Task force sessions on the cross-comparison of draft narratives and the further elaboration of the historical-present narrative. • Organisational sessions to begin the drafting of sub-deliverable-specific work plans. • In parallel to the task force workshop, collaborative sessions between the task force and Japanese researchers took place to discuss the application of the Nature Futures Framework at the national scale, using existing national level scenarios from Japan. • A public seminar, in Japan, for a wider audience introducing the scenarios and models task force’s work, the concept of the Nature Futures Framework, and fostered discussions on the concept of transformative change. Summary of outputs of the workshop in Japan • 6 NEW scenario narratives drafts – an evolution of the pre-workshop work using the narrative templates, into a more coherent set of narratives fitting their locations in the Nature Futures Framework, including some illustrative visualisations. • A cross-comparison table – to identify the core similarities and differences across the 6 new narratives (including single narrative-between-narrative comparisons). • A discussion on how to continue further development, requiring identifying pathways to complete the 6 new narratives. • 1 historical-to-present narrative draft – also an evolution of work done prior to the workshop. The task force has yet to synthesize and shorten this draft, ensuring linkages with topics detailed in the 6 new narratives into a more digestible level. • Elaboration of a follow-up plan for further development of the narratives, post-workshop, through a “buddy” system of in-depth online discussions per and between narratives. • 1 Japan case study – on fitting national level scenarios into the Nature Futures Framework. A summary will be shared by the team who worked closely on this with the PANCES partners, which we expect will give interesting insights to the cross-scale application of the Nature Futures Framework. • Detailed work plan implementation drafts (ongoing post workshop in sub-groups).

Report↗
USGS2016

Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099

The frequency of deep ventilation events in Crater Lake, a caldera lake in the Oregon Cascade Mountains, was simulated in six future climate scenarios, using a 1-dimensional deep ventilation model (1DDV) that was developed to simulate the ventilation of deep water initiated by reverse stratification and subsequent thermobaric instability. The model was calibrated and validated with lake temperature data collected from 1994 to 2011. Wind and air temperature data from three general circulation models and two representative concentration pathways were used to simulate the change in lake temperature and the frequency of deep ventilation events in possible future climates. The lumped model air2water was used to project lake surface temperature, a required boundary condition for the lake model, based on air temperature in the future climates. The 1DDV model was used to simulate daily water temperature profiles through 2099. All future climate scenarios projected increased water temperature throughout the water column and a substantive reduction in the frequency of deep ventilation events. The least extreme scenario projected the frequency of deep ventilation events to decrease from about 1 in 2 years in current conditions to about 1 in 3 years by 2100. The most extreme scenario considered projected the frequency of deep ventilation events to be about 1 in 7.7 years by 2100. All scenarios predicted that the temperature of the entire water column will be greater than 4 °C for increasing lengths of time in the future and that the conditions required for thermobaric instability induced mixing will become rare or non-existent. The disruption of deep ventilation by itself does not provide a complete picture of the potential ecological and water quality consequences of warming climate to Crater Lake. Estimating the effect of warming climate on deep water oxygen depletion and water clarity will require careful modeling studies to combine the physical mixing processes affected by the atmosphere with the multitude of factors affecting the growth of algae and corresponding water clarity.

Oregon↗
USGS2022

Modeling and estimating co-occurrence between the invasive Shiny Cowbird and its Puerto Rican hosts

Invasive species threaten island biodiversity globally. For example, the Shiny Cowbird ( Molothrus bonariensis ) parasitizes many of Puerto Rico’s endemic species, particularly in the open forests in the island’s southwest. Less is known, however, about cowbird parasitism in the agro-ecological highlands, which contain a patchwork of forests, shaded-coffee plantations, and coffee farms without shade. In this paper, we estimated co-occurrence rates, a potential indicator of parasitism rates, between the cowbird and four host species across these three land uses, hypothesizing that cowbirds would most likely co-occur with their hosts in shaded-coffee farms. We also hypothesized that the presence of host species would increase the probability of cowbird occurrence. To investigate these hypotheses, we developed three Bayesian hierarchical occupancy models: one where the hosts and parasite occurred independently, one that used the latent host species richness as a predictor of cowbird occurrence, and one that used each latent host occurrence state as predictors. These methods addressed observation errors and appropriately propagated error to our predictions of co-occurrence rates. We selected the best performing model using WAIC, then used it to predict co-occurrence rates. While there was some evidence that host species richness increased the probability of cowbirds, the parsimonious model assumed no interaction. With this model, we found that cowbirds were more likely to overlap with certain hosts in shaded-coffee plantations. This may suggest increased parasitism at these plantations, potentially presenting challenges for managers who advocate for shade restoration to gain ecological services such as biodiversity conservation.

Biological Invasions↗