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1. The effect of colonization dynamics in competition for space in metacommunities

   https://doi.org/10.1007/s12080-021-00515-9  

   Arroyo-Esquivel, Jorge; Marculis, Nathan G.; Hastings, Alan (December 2021, Theoretical Ecology)

   Abstract One of the main factors that determines habitat suitability for sessile and territorial organisms is the presence or absence of another competing individual in that habitat. This type of competition arises in populations occupying patches in a metacommunity. Previous studies have looked at this process using a continuous-time modeling framework, where colonizations and extinctions occur simultaneously. However, different colonization processes may be performed by different species, which may affect the metacommunity dynamics. We address this issue by developing a discrete-time framework that describes these kinds of metacommunity interactions, and we consider different colonization dynamics. To understand potential dynamics, we consider specific functional forms that characterize the colonization and extinction processes of metapopulations competing for space as their limiting factor. We then provide a mathematical analysis of the models generated by this framework, and we compare these results to what is seen in nature and in previous models. 

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2. Persistence of a reef fish metapopulation via network connectivity: theory and data

   https://doi.org/10.1111/ele.13721  

   Dedrick, Allison G.; Catalano, Katrina A.; Stuart, Michelle R.; White, J. Wilson; Montes, Jr., Humberto R.; Pinsky, Malin L.; Marshall, ed., Dustin (March 2021, Ecology Letters)

   Abstract Determining metapopulation persistence requires understanding both demographic rates and patch connectivity. Persistence is well understood in theory but has proved challenging to test empirically for marine and other species with high connectivity that precludes classic colonisation–extinction dynamics. Here, we assessed persistence for a yellowtail anemonefish (Amphiprion clarkii) metapopulation using 7 years of annual sampling data along 30 km of coastline. We carefully accounted for uncertainty in demographic rates. Despite stable population abundances through time and sufficient production of surviving offspring for replacement, the pattern of connectivity made the metapopulation unlikely to persist in isolation and reliant on immigrants from outside habitat. To persist in isolation, the metapopulation would need higher fecundity or to retain essentially all recruits produced. This assessment of persistence in a marine metapopulation shows that stable abundance alone does not indicate persistence, emphasising the necessity of assessing both demographic and connectivity processes to understand metapopulation dynamics. 

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3. Small mammal community composition varies among Ozark glades

   https://doi.org/10.1093/jmammal/gyz102  

   Beasley, Emily M; Maher, Sean P (December 2019, Journal of Mammalogy)

   Powell, Roger (Ed.)

   Abstract Island biogeography theory (IBT) explains and estimates large-scale ecological patterns among islands and isolated habitat patches. Specifically, IBT predicts that the number of species per habitat patch differs as a function of area and isolation as a result of local colonization and extinction. Accurate estimates of species richness are essential for testing predictions of IBT, but differences in detectability of species can lead to bias in empirical data. Hierarchical community models correct for imperfect detection by leveraging information from across the community to estimate species-specific occupancy and detection probabilities. Using the fragmented Ozark glades as our model system, we constructed a hierarchical community model to 1) estimate site-level and regional species richness of small mammals while correcting for detection error, and 2) determine environmental covariates driving occupancy. We sampled 16 glades in southwestern Missouri in summer 2016–2017 and quantified mammal community structure within the glade network. The detected species pool included eight species, and the model yielded a regional species estimate of 8.6 species, with a mean of 3.47 species per glade. Species richness increased with patch area but not isolation, and effects of patch shape varied between species in the community. 

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4. A novel method for estimating pathogen presence, prevalence, load, and dynamics at multiple scales

   https://doi.org/10.1038/s41598-025-93865-x  

   Grider, John F; Udell, Bradley J; Reichert, Brian E; Foster, Jeffrey T; Kendall, William L; Cheng, Tina L; Frick, Winifred F (December 2025, Scientific Reports)

   Abstract The use of quantitative real-time PCR (qPCR) to monitor pathogens is common; however, quantitative frameworks that consider the observation process, dynamics in pathogen presence, and pathogen load are lacking. This can be problematic in the early stages of disease progression, where low level detections may be treated as ‘inconclusive’ and excluded from analyses. Alternatively, a framework that accounts for imperfect detection would provide more robust inferences. To better estimate pathogen dynamics, we developed a hierarchical multi-scale dynamic occupancy hurdle model (MS-DOHM). The model used data gathered during sampling forPseudogymnoascus destructans (Pd), the causative agent of white-nose syndrome, a fungal disease that has cause severe declines in several species of hibernating bats in North America. The model allowed us to estimate initial occupancy, colonization, persistence and prevalence ofPdat bat hibernacula. Additionally, utilizing the relationship between cycle threshold and pathogen load, we estimated pathogen detectability and modeled expected colony and bat pathogen loads. To assess the ability of MS-DOHM to estimate pathogen dynamics, we compared MS-DOHM’s results to those of a dynamic occupancy model and naïve detection/non-detection. MS-DOHM’s estimates of site-level pathogen presence were up to 11.9% higher than estimates from the dynamic occupancy model and 35.7% higher than naïve occupancy. Including prevalence and load in our modeling framework resulted in estimates of pathogen arrival that were two to three years earlier compared to the dynamic occupancy and naïve detection/non-detection, respectively. Compared to naïve values, MS-DOHM predicted greater pathogen loads on colonies; however, we found no difference between model estimates and naïve values of prevalence. While the model predicted no declines in site-level prevalence, there were instances where pathogen load decreased in colonies that had beenPdpositive for longer periods of time. Our findings demonstrate that accounting for pathogen load and prevalence at multiple scales changes our understanding ofPddynamics, potentially allowing earlier conservation intervention. Additionally, we found that accounting for pathogen load and prevalence within hibernacula and among individuals resulted in a better fitting model with greater predictive ability. 

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5. Tail associations in ecological variables and their impact on extinction risk

   https://doi.org/10.1002/ecs2.3132  

   Ghosh, Shyamolina; Sheppard, Lawrence W.; Reuman, Daniel C. (May 2020, Ecosphere)

   Abstract Extreme climatic events (ECEs) are becoming more frequent and more intense due to climate change. Furthermore, there is reason to believe ECEs may modify tail associations between distinct population vital rates, or between values of an environmental variable measured in different locations. Tail associations between two variables are associations that occur between values in the left or right tails of the distributions of the variables. Two positively associated variables can be principally left‐tail associated (i.e., more correlated when they take low values than when they take high values) or right‐tail associated (more correlated when they take high than low values), even with the same overall correlation coefficient in both cases. We tested, in the context of non‐spatial stage‐structured matrix models, whether tail associations between stage‐specific vital rates may influence extinction risk. We also tested whether the nature of spatial tail associations of environmental variables can influence metapopulation extinction risk. For instance, if low values of an environmental variable reduce the growth rates of local populations, one may expect that left‐tail associations increase metapopulation extinction risks because then environmental catastrophes are spatially synchronized, presumably reducing the potential for rescue effects. For the non‐spatial, stage‐structured models we considered, left‐tail associations between vital rates did accentuate extinction risk compared to right‐tail associations, but the effect was small. In contrast, we showed that density dependence interacts with tail associations to influence metapopulation extinction risk substantially: For population models showing undercompensatory density dependence, left‐tail associations in environmental variables often strongly accentuated and right‐tail associations mitigated extinction risk, whereas the reverse was usually true for models showing overcompensatory density dependence. Tail associations and their asymmetries are taken into account in assessing risks in finance and other fields, but to our knowledge, our study is one of the first to consider how tail associations influence population extinction risk. Our modeling results provide an initial demonstration of a new mechanism influencing extinction risks and, in our view, should help motivate more comprehensive study of the mechanism and its importance for real populations in future work. 

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