Ecological invasions and colonizations occur dynamically through space and time. Estimating the distribution and abundance of colonizing species is critical for efficient management or conservation. We describe a statistical framework for simultaneously estimating spatiotemporal occupancy and abundance dynamics of a colonizing species. Our method accounts for several issues that are common when modeling spatiotemporal ecological data including multiple levels of detection probability, multiple data sources, and computational limitations that occur when making fine-scale inference over a large spatiotemporal domain. We apply the model to estimate the colonization dynamics of sea otters (Enhydra lutris) in Glacier Bay, in southeastern Alaska.
The genetic impacts of hybridization between native and introduced species are of considerable conservation concern, while the possibility of reticulate evolution affects our basic understanding of how species arise and shapes how we use genetic data to understand evolutionary diversification. By using mitochondrial NADH dehydrogenase subunit 2 (ND2) sequences and 467 amplified fragment-length polymorphism nuclear DNA markers, we show that the introduced white sucker (Catostomus commersoni) has hybridized with two species native to the Colorado River Basin-the flannelmouth sucker (Catostomus latipinnis) and the bluehead sucker (Catostomus discobolus). Hybrids between the flannelmouth sucker and white sucker have facilitated introgression between the two native species, previously isolated by reproductive barriers, such that individuals exist with contributions from all three genomes. Most hybrids had the mitochondrial haplotype of the introduced white sucker, emphasizing its pivotal role in this three-way hybridization. Our findings highlight how introduced species can threaten the genetic integrity of not only one species but also multiple previously reproductively isolated species. Furthermore, this complex three-way reticulate (as opposed to strictly bifurcating) evolution suggests that seeking examples in other vertebrate systems might be productive. Although the present study involved an introduced species, similar patterns of hybridization could result from natural processes, including stream capture or geological formations (e.g., the Bering land bridge).conservation ͉ hybridization ͉ native fish ͉ reticulate evolution
Partial differential equations (PDEs) are a useful tool for modeling spatiotemporal dynamics of ecological processes. However, as an ecological process evolves, we need statistical models that can adapt to changing dynamics as new data are collected. We developed a model that combines an ecological diffusion equation and logistic growth to characterize colonization processes of a population that establishes long‐term equilibrium over a heterogeneous environment. We also developed a homogenization strategy to statistically upscale the PDE for faster computation and adopted a hierarchical framework to accommodate multiple data sources collected at different spatial scales. We highlighted the advantages of using a logistic reaction component instead of a Malthusian component when population growth demonstrates asymptotic behavior. As a case study, we demonstrated that our model improves spatiotemporal abundance forecasts of sea otters in Glacier Bay, Alaska. Furthermore, we predicted spatially varying local equilibrium abundances as a result of environmentally driven diffusion and density‐regulated growth. Integrating equilibrium abundances over the study area in our application enabled us to infer the overall carrying capacity of sea otters in Glacier Bay, Alaska.
Aim: Sea otters (Enhydra lutris) are an apex predator of the nearshore marine community and nearly went extinct at the turn of the 20th century. Reintroductions and legal protection allowed sea otters to re-colonize much of their former range. Our objective was to chronicle the colonization of this apex predator in Glacier Bay, Alaska, to help understand the mechanisms that governed their successful colonization.Location: Glacier Bay is a tidewater glacier fjord in southeastern Alaska that was entirely covered by glaciers in the mid-18th century. Since then, it has endured the fastest tidewater glacier retreat in recorded history. Methods:We collected and analysed several data sets, spanning 20 years, to document the spatio-temporal dynamics of an apex predator expanding into an area where they were formerly absent. We used novel quantitative tools to model the occupancy, abundance and colonization dynamics of sea otters, while accounting for uncertainty in the data collection process, the ecological process and model parameters.Results: Twenty years after sea otters were first observed colonizing Glacier Bay, they became one of the most abundant and widely distributed marine mammal. The population grew exponentially at a rate of 20% per year. They colonized Glacier Bay at a maximum rate of 6 km per year, with faster colonization rates occurring early in the colonization process. During colonization, sea otters selected shallow areas, close to shore, with a steep bottom slope, and a relatively simple shoreline complexity index. Main conclusions:The growth and expansion of sea otters in Glacier Bay demonstrate how legal protection and translocation of apex predators can facilitate their successful establishment into a community in which they were formerly absent. The success of sea otters was, in part, a consequence of habitat that was left largely unperturbed by humans for the past 250 years. Further, sea otters and other marine predators, whose distribution is limited by ice, have the potential to expand in
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.
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