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Analyzing mixing systems using a new generation of Bayesian tracer mixing models
The ongoing evolution of tracer mixing models has resulted in a confusing array of software tools that differ in terms of data inputs, model assumptions, and associated analytic products. Here we introduce MixSIAR, an inclusive, rich, and flexible Bayesian tracer (e.g., stable isotope) mixing model framework implemented as an open-source R package. Using MixSIAR as a foundation, we provide guidance for the implementation of mixing model analyses. We begin by outlining the practical differences between mixture data error structure formulations and relate these error structures to common mixing model study designs in ecology. Because Bayesian mixing models afford the option to specify informative priors on source proportion contributions, we outline methods for establishing prior distributions and discuss the influence of prior specification on model outputs. We also discuss the options available for source data inputs (raw data versus summary statistics) and provide guidance for combining sources. We then describe a key advantage of MixSIAR over previous mixing model software—the ability to include fixed and random effects as covariates explaining variability in mixture proportions and calculate relative support for multiple models via information criteria. We present a case study of Alligator mississippiensis diet partitioning to demonstrate the power of this approach. Finally, we conclude with a discussion of limitations to mixing model applications. Through MixSIAR, we have consolidated the disparate array of mixing model tools into a single platform, diversified the set of available parameterizations, and provided developers a platform upon which to continue improving mixing model analyses in the future.
Journal Article
Spatial analysis of coastal environments
\"At the convergence of the land and sea, coastal environments are some of the most dynamic and populated places on Earth. This book explains how the many varied forms of spatial analysis, including mapping, monitoring and modelling, can be applied to a range of coastal environments such as estuaries, mangroves, seagrass beds and coral reefs. Presenting empirical geographical approaches to modelling, which draw on recent developments in remote sensing technology, geographical information science and spatial statistics, it provides the analytical tools to map, monitor and explain or predict coastal features. With detailed case studies and accompanying online practical exercises, it is an ideal resource for undergraduate courses in spatial science. Taking a broad view of spatial analysis and covering basic and advanced analytical areas such as spatial data and geostatistics, it is also a useful reference for ecologists, geomorphologists, geographers and modellers interested in understanding coastal environments\"-- Provided by publisher.
Book
Three-dimensional digital mapping of ecosystems: a new era in spatial ecology
Ecological processes occur over multiple spatial, temporal and thematic scales in three-dimensional (3D) ecosystems. Characterizing and monitoring change in 3D structure at multiple scales is challenging within the practical constraints of conventional ecological tools. Remote sensing from satellites and crewed aircraft has revolutionized broad-scale spatial ecology, but fine-scale patterns and processes operating at sub-metre resolution have remained understudied over continuous extents. We introduce two high-resolution remote sensing tools for rapid and accurate 3D mapping in ecology—terrestrial laser scanning and structure-from-motion photogrammetry. These technologies are likely to become standard sampling tools for mapping and monitoring 3D ecosystem structure across currently under-sampled scales. We present practical guidance in the use of the tools and address barriers to widespread adoption, including testing the accuracy of structure-from-motion models for ecologists. We aim to highlight a new era in spatial ecology that uses high-resolution remote sensing to interrogate 3D digital ecosystems.
Journal Article
The underworld : journeys to the depths of the ocean
\"From New York Times bestselling author Susan Casey, an awe-inspiring portrait of the mysterious world beneath the waves, and the men and women who seek to uncover its secrets For all of human history, the deep ocean has been a source of wonder and terror, an unknown realm that evoked a singular, compelling question: What's down there? Unable to answer this for centuries, people believed the deep was a sinister realm of fiendish creatures and deadly peril. But now, cutting-edge technologies allow scientists and explorers to dive miles beneath the surface, and we are beginning to understand this strange and exotic underworld: A place of soaring mountains, smoldering volcanoes, and valleys 7,000 feet deeper than Everest is high, where tectonic plates collide and separate, and extraordinary life forms operate under different rules. Far from a dark void, the deep is a vibrant realm that's home to pink gelatinous predators and shimmering creatures a hundred feet long and ancient animals with glass skeletons and sharks that live for half a millennium-among countless other marvels. Susan Casey is our premiere chronicler of the aquatic world. For The Underworld she traversed the globe, joining scientists and explorers on dives to the deepest places on the planet, interviewing the marine geologists, marine biologists, and oceanographers who are searching for knowledge in this vast unseen realm. She takes us on a fascinating journey through the history of deep-sea exploration, from the myths and legends of the ancient world to storied shipwrecks we can now reach on the bottom, to the first intrepid bathysphere pilots, to the scientists who are just beginning to understand the mind-blowing complexity and ecological importance of the quadrillions of creatures who live in realms long thought to be devoid of life. Throughout this journey, she learned how vital the deep is to the future of the planet, and how urgent it is that we understand it in a time of increasing threats from climate change, industrial fishing, pollution, and the mining companies that are also exploring its depths. The Underworld is Susan Casey's most beautiful and thrilling book yet, a gorgeous evocation of the natural world and a powerful call to arms\"-- Provided by publisher.
Book
Hairiness: the missing link between pollinators and pollination
Functional traits are the primary biotic component driving organism influence on ecosystem functions; in consequence, traits are widely used in ecological research. However, most animal trait-based studies use easy-to-measure characteristics of species that are at best only weakly associated with functions. Animal-mediated pollination is a key ecosystem function and is likely to be influenced by pollinator traits, but to date no one has identified functional traits that are simple to measure and have good predictive power.
Here, we show that a simple, easy to measure trait (hairiness) can predict pollinator effectiveness with high accuracy. We used a novel image analysis method to calculate entropy values for insect body surfaces as a measure of hairiness. We evaluated the power of our method for predicting pollinator effectiveness by regressing pollinator hairiness (entropy) against single visit pollen deposition (SVD) and pollen loads on insects. We used linear models and AIC
model selection to determine which body regions were the best predictors of SVD and pollen load.
We found that hairiness can be used as a robust proxy of SVD. The best models for predicting SVD for the flower species
and
were hairiness on the face and thorax as predictors (
= 0.98 and 0.91 respectively). The best model for predicting pollen load for
.
was hairiness on the face (
= 0.81).
We suggest that the match between pollinator body region hairiness and plant reproductive structure morphology is a powerful predictor of pollinator effectiveness. We show that pollinator hairiness is strongly linked to pollination-an important ecosystem function, and provide a rigorous and time-efficient method for measuring hairiness. Identifying and accurately measuring key traits that drive ecosystem processes is critical as global change increasingly alters ecological communities, and subsequently, ecosystem functions worldwide.
Journal Article
MaxEnt’s parameter configuration and small samples: are we paying attention to recommendations? A systematic review
Environmental niche modeling (ENM) is commonly used to develop probabilistic maps of species distribution. Among available ENM techniques, MaxEnt has become one of the most popular tools for modeling species distribution, with hundreds of peer-reviewed articles published each year. MaxEnt’s popularity is mainly due to the use of a graphical interface and automatic parameter configuration capabilities. However, recent studies have shown that using the default automatic configuration may not be always appropriate because it can produce non-optimal models; particularly when dealing with a small number of species presence points. Thus, the recommendation is to evaluate the best potential combination of parameters (feature classes and regularization multiplier) to select the most appropriate model. In this work we reviewed 244 articles published between 2013 and 2015 to assess whether researchers are following recommendations to avoid using the default parameter configuration when dealing with small sample sizes, or if they are using MaxEnt as a “black box tool.” Our results show that in only 16% of analyzed articles authors evaluated best feature classes, in 6.9% evaluated best regularization multipliers, and in a meager 3.7% evaluated simultaneously both parameters before producing the definitive distribution model. We analyzed 20 articles to quantify the potential differences in resulting outputs when using software default parameters instead of the alternative best model. Results from our analysis reveal important differences between the use of default parameters and the best model approach, especially in the total area identified as suitable for the assessed species and the specific areas that are identified as suitable by both modelling approaches. These results are worrying, because publications are potentially reporting over-complex or over-simplistic models that can undermine the applicability of their results. Of particular importance are studies used to inform policy making. Therefore, researchers, practitioners, reviewers and editors need to be very judicious when dealing with MaxEnt, particularly when the modelling process is based on small sample sizes.
Journal Article
Phylogenetic and functional characteristics of household yard floras and their changes along an urbanization gradient
Urban areas are among the most heavily managed landscapes in the world, yet they harbor a remarkable richness of species. Private yards are common habitats in urban areas and are places where cultivated species manage to escape cultivation and become part of the spontaneous species pool. Yards are novel ecosystems where community assembly is driven by both natural and anthropogenic processes. Phylogenetic diversity and functional traits are increasingly recognized as critical to understanding processes of community assembly. Recent evidence indicates that urban areas may select more closely related plant species from the pool of regionally occurring species than do nonurban areas, and that exotic species are phylogenetically clustered within communities. We tested whether phylogenetic diversity and functional trait composition in privately managed yards change along a gradient of housing density in the Minneapolis–Saint Paul metropolis, Minnesota, USA, in accordance with these predictions. We also identified characteristics of the spontaneous yard flora by comparing its phylogenetic diversity and functional composition with the “natural‐areas” species pool represented by the flora of nearby Cedar Creek Ecosystem Science Reserve. Along the urbanization gradient, yards had more species per hectare in densely built regions than in lower‐density regions, but phylogenetic diversity and functional composition did not change with housing density. In contrast, in comparison to species in natural areas, yard species were more closely related to each other and functionally distinct: They were more often short‐lived, self‐compatible, and had higher specific leaf area than species of Cedar Creek. The high number of exotic yard species increased the yard flora's phylogenetic relatedness in comparison to species of Cedar Creek, causing a degree of phylogenetic homogenization within yards. The urban environment and homeowners' preferences select for trait attributes and phylogenetic lineages that can colonize and persist in yards. As yard species disperse beyond household boundaries, their functional attributes will affect ecosystem processes in urban environments and beyond, such as accelerating decomposition rates. Limited phylogenetic diversity may reduce the potential of ecosystems to respond to environmental changes. As cities continue to expand globally, understanding the impacts of yard management for biodiversity and ecosystem services becomes increasingly important.
Journal Article
Understanding trends in Zostera research, stressors, and response variables: a global systematic review of the seagrass genus
Seagrass meadows are ecologically significant habitats that are globally threatened. Thus, there is increased interest in conservation of seagrasses as they face widespread decline. Biotic and abiotic factors that influence seagrass can be classified as stressors, such as rising temperature and eutrophication. Our study met an imminent need to consolidate data from previous studies to discern knowledge gaps and identify trends in studies, stressors, species, and geographic origination of research for the genus
. For our systematic review, the objectives were to (A) qualitatively assess and summarize the current state of literature focused on seagrass species within the
genus and their stressors; (B) utilize data extracted from full-text articles to identify trends and knowledge gaps for the study of stressors, response variable measurements, species, geography, and study designs; and (C) map the distribution, type, and number of these studies globally.
We included articles that focused on stressors associated with
seagrass species, and excluded studies of other seagrasses and non-stressor related articles. We conducted a Web of Science search of all databases, concluding in January of 2021, followed by a standardized review and data extraction protocol using Colandr (colandrapp.com) as our article screening tool. All 15 review participants were trained on the same set of practice articles and decision trees to minimize variation between individuals. After full text extraction, we analyzed our data by frequency and association between species, stressors, and geographic locations studied.
We screened 7,331 titles and abstracts and extracted data from 1,098 full-text articles. We found nutrients, temperature, and light were the most studied stressors. The United States of America produced the most articles in our review, followed by Australia.
was most frequently studied, and our review found no stressor studies for five species in the genus. Studies most frequently measured response variables across multiple levels of ecological organization, including the individual plant, biotic community, and environmental conditions. As a part of our review, we made all extracted data publicly available as an interactive map.
Undertaking a review of global studies allowed us to assess more seagrass articles for a single genus than any prior systematic review, summarizing a breadth of stressor studies related to the
genus. A team effort and standardized training minimized bias during screening and data extraction. Evidence limitations may exist due to the single database used in our search protocol, as well as species, geographic, and stressor biases in included studies. Our review creates a centralized knowledge base that serves as a foundational information source for
research, while highlighting existing knowledge gaps in the literature.
Journal Article
The spatial and temporal evolution of habitat quality and driving factors in nature reserves: a case study of 33 forest ecosystem reserves in Guizhou Province
Biodiversity plays a crucial role for humanity, serving as a foundation for human survival and development. Habitat quality serves as a critical indicator for assessing biodiversity and holds significant importance in both theoretical and practical domains. The unique natural geographical environment of Guizhou Province has fostered rich biodiversity and facilitated the establishment of numerous nature reserves, predominantly centered on forest ecosystems. Analyzing the habitat quality of nature reserves and its influencing factors is of great significance for maintaining the regional ecosystem stability, promoting sustainable development, and improving the ecological environment.
Therefore, taking the 33 nature reserves of forest ecosystem in Guizhou Province as the study area, we first quantified habitat quality using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to analyze changes in the nature reserve from 2000 to 2020. Then, we explored the effects of natural and social factors on the spatiotemporal evolution of habitat quality using the optimal parameters-based geographical detector (OPGD).
Forests were identified as the primary land-use type in the study area. However, the nature reserves saw an increase area in cropland, and impervious land by 5,001.39 ha and 102.15 ha; a significant decrease in forests and grasslands; and a slight decrease in watersheds. Rapid urbanization, therefore, negatively affected the overall habitat quality of the reserve. Although there is a declining trend in the habitat quality of the nature reserve, the magnitude of change from 2010 to 2020 (-0.04) is smaller than that from 2000 to 2010 (-0.17), indicating that the management of the reserve has been somewhat effective. In national-level nature reserves, interactions between natural geographic factors and socio-economic factors were greater than interactions between natural geographic factors. Similarly, in local-level nature reserves, interactions between natural geographic factors and socio-economic factors outweighed interactions among social factors.
The spatiotemporal variability of habitat quality in the study area was shaped by the combined effects of natural and social factors. The habitat quality of local-level protected areas is, furthermore, more significantly affected by human activities, which are the primary cause of their degradation.
Journal Article