This dataset is about books and is filtered where the book series is Environmental and ecological statistics, featuring 9 columns including author, BNB id, book, book publisher, and book series. The preview is ordered by publication date (descending).

Ecological flow (EFlow) statistics have been designated to characterize the magnitude, frequency, and duration of extreme high- and low-flows, the timing of seasonal flows, and the consistency of the historic regime. This Child Item contains a table of 178 EFlows for the time periods 1940-1969, 1970-1999, and 2000-2018, with absolute and percent change between periods, where applicable. Statistics were computed by Water Year (WY) for all 178 metrics and absolute and percent change were calculated by comparing metrics between combinations of two of the three time periods (1940-1969 and 1970-1999; 1940-1969 and 2000-2018; 1970-1999 and 2000-2018). Streamgages from the original dataset (n = 409) were excluded from one or more time periods of analysis because of extensive data gaps that would yield incomplete EFlows; therefore, stations were indexed into the earliest possible time period relative to their installation date (for example, a streamgage with an operating start year of 1958 would be included in the analysis for the time periods 1970-1999 and 2000-2018), which resulted in different sample sizes for each period: 1940-1969 (n = 90), 1970-1999 (n = 167), and 2000-2018 (n = 243). Similarly, multiple stations were wholly excluded because of frequent discontinuities in the daily mean streamflow through all three time periods. Finally, a streamgage must have fallen within at least two time periods to have a change value. As such, not all stations are represented in the change analysis (change between 1940-1969 and 1970-1999 [n = 90]; change between 1940-1969 and 2000-2018 [n = 90]; change between 1970-1999 and 2000-2018 [n = 167]).

Biology students’ understanding of statistics is incomplete due to poor integration of these two disciplines. In some cases, students fail to learn statistics at the undergraduate level due to poor student interest and cursory teaching of concepts, highlighting a need for new and unique approaches to the teaching of statistics in the undergraduate biology curriculum. The most effective method of teaching statistics is to provide opportunities for students to apply concepts, not just learn facts. Opportunities to learn statistics also need to be prevalent throughout a student’s education to reinforce learning. The purpose of developing and implementing curriculum that integrates a topic in biology with an emphasis on statistical analysis was to improve students’ quantitative thinking skills. Our lesson focuses on the change in the richness of native species for a specified area with the aid of iNaturalist and the capacity for analysis afforded by Google Sheets. We emphasized the skills of data entry, storage, organization, curation and analysis. Students then had to report their findings, as well as discuss biases and other confounding factors. Pre- and post-lesson assessment revealed students’ quantitative thinking skills, as measured by a paired-samples t test, improved. At the end of the lesson, students had an increased understanding of basic statistical concepts, such as bias in research and making data-based claims, within the framework of biology.

Primary Image: Website screenshot of an iNaturalist observation (Clasping Milkweed – Asclepias amplexicalis). This image is an example of a data entry on iNaturalist. The data students export from iNaturalist is made up of hundreds, or even thousands, of observations like this one. This image is licensed under Creative Commons Attribution - Share Alike 4.0 International license. Source: Observation by cassi saari, 2014.

Behavioural responses are often the first reaction of an organism to human induced rapid environmental change (HIREC), yet current empirical evidence provides no consensus about the main environmental features that animals respond to behaviourally or which behaviours are responsive to HIREC. To understand how changes in behaviour can be predicted by different forms of HIREC, we conducted a meta-analysis of the existing empirical literature focusing on behavioural responses to five axes of environmental change (climate change, changes in CO2, direct human impact, changes in nutrients and biotic exchanges) in five behavioural domains (aggression, exploration, activity, boldness and sociability) across a range of taxa but with a focus on fish and bird species. Our meta-analysis revealed a general absence of directional behavioural responses to HIREC. However, the absolute magnitude of the effect sizes was large. This means that animals have strong behavioural responses to HIREC, but the re...

Tabular data associated with the article "Ecological condition of mountain lakes in the conterminous United States and vulnerability to human development". All tabular data for lake, catchment, and watershed characteristics and population condition estimates are included.

Managing multiple ecosystem services (ES), including addressing trade-offs between services and preventing ecological surprises, is among the most pressing areas for sustainability research. These challenges require ES research to go beyond the currently common approach of snapshot studies limited to one or two services at a single point in time. We used a spatiotemporal approach to examine changes in nine ES and their relationships from 1971 to 2006 across 131 municipalities in a mixed-use landscape in Quebec, Canada. We show how an approach that incorporates time and space can improve our understanding of ES dynamics. We found an increase in the provision of most services through time; however, provision of ES was not uniformly enhanced at all locations. Instead, each municipality specialized in providing a bundle (set of positively correlated ES) dominated by just a few services. The trajectory of bundle formation was related to changes in agricultural policy and global trends; local biophysical and socioeconomic characteristics explained the bundles' increasing spatial clustering. Relationships between services varied through time, with some provisioning and cultural services shifting from a trade-off or no relationship in 1971 to an apparent synergistic relationship by 2006. By implementing a spatiotemporal perspective on multiple services, we provide clear evidence of the dynamic nature of ES interactions and contribute to identifying processes and drivers behind these changing relationships. Our study raises questions about using snapshots of ES provision at a single point in time to build our understanding of ES relationships in complex and dynamic social-ecological systems.

Humanity has been in an ecological overshoot since the 1970s, where demand for natural resources exceeded that of what the Earth can regenerate. As of 2022, if the world's entire population lived like those in the United States, we would need resources equivalent to five times what our Earth can regenerate to satisfy the global demand.

For a series of studies on the ecosystem service values of chaparral in Southern California, we developed a raster data layer providing an ecological unit classification of the Southern California landscape. This raster dataset is at a 30 meter pixel resolution and partitions the landscape into 37 different ecological unit types. This dataset was derived through a GIS-based cluster analysis of 10 different physiographic variables, namely soil suborder type, terrain geomorphon type, flow accumulation, slope, solar irradiation, annual precipitation, annual minimum temperature, actual evapotranspiration, and climatic water deficit. This partitioning was based on physiographic variables rather than vegetation types because of the wish to have the ecological units reflect biophysical characteristics rather than the historical land use patterns that may influence vegetation. The cluster analysis was performed across a set of 10,000 points randomly placed on a GIS layer stack for the 10 variables. These random points were grouped into 37 discrete clusters using an algorithm called partitioning around medoids. This assignment of points to clusters was then used to train a random forest classifier, which in turn was run across the GIS stack to produce the output raster layer.

This dataset is described in the following book chapter publication:

Underwood, Emma C., Allan D. Hollander, Patrick R. Huber, and Charlie Schrader-Patton. 2018. "Mapping the Value of National Forest Landscapes for Ecosystem Service Provision." In Valuing Chaparral, 245–70. Springer Series on Environmental Management. Springer, Cham. https://doi.org/10.1007/978-3-319-68303-4_9.

Marine visual imaging has become a major assessment tool in the science, policy and public understanding of our seas and oceans. The technology to acquire and process this imagery has significantly evolved in recent years through the development of new camera platforms, camera types, lighting systems and analytical software. These advances have led to new challenges in imaging, including storage and management of `big data, manipulation of digital photos, and the extraction of biological and ecological data. The need to address these challenges, within and beyond the scientific community, is set to substantially increase in the near future, as imaging is increasingly used in the designation and evaluation of marine conservation areas, and for the assessment of environmental baselines and impact monitoring for maritime industry. We review the state of the theory, techniques and technologies associated with each of the steps of marine imaging for observation and research, and to provide an outlook on the future from this active scientific and engineering community that develops and uses it.

Schedule for a one-semester course at Colorado State University (NR 575: Systems Ecology) introducing concepts of model–data assimilation to graduate students in ecology.

This data set includes polygons for ecological provinces within the conterminous United States. This data set contains regional geographic delineations for analysis of ecological relationships across ecological units. Metadata

Environmental change research is plagued by the curse of dimensionality: the number of communities at risk and the number of environmental drivers are both large. This raises the pressing question if a general understanding of ecological effects is achievable. These data show that this is indeed possible. It contains code that calculates the feasibility domain size (a proxy for coexistence) for bi- and tritrophic communities challenged by environmental change. Some of this code simply returns the output of a closed-form expressions (i.e. simple equations), while some rely on simulations that require specific packages. The data also contain presence/absence data of macroinvertebrate taxa and water chemistry variables measured across sites (that are either severely or weakly modified by human activity, quantified via land use) at US streams. With these data, we were able to test if sites that share the same community have similar water chemistry, in other words: how tightly is a community...

The purpose of this dataset is to display the extent of existing Terrestrial Ecological Unit inventory (TEUI) data internally to facilitate inter-agency collaboration. The feature class for this dataset will display polygons of the ecological unit plots, acreages, and percent coverages of National Forest and Grassland administrative boundaries using their common names, with a percent coverage for Land Type and acres of forest per plot.Metadata and Downloads

File List

   SITE INFO.csv (MD5: 6d51faf1d75d50f75ec704e57e262ebf)
   SEED MIX.csv (MD5: 61469ab36c44d41ff6aee18fa1754089)
   PLANT COMMUNITY.csv (MD5: a89e01dfe15b84e3f3b6e980ca80a8a7)
   PLOT LEVEL.csv (MD5: c6bf2615e9e44a42980a21918a2fd024)
  Description
    By assisting the recovery of disturbed or destroyed ecosystems, ecological restoration plays an important role in biodiversity conservation. Moreover, restoration has been heralded as an “acid test” of ecological understanding, by affording the ability to study community assembly, ecosystem function, and human influence over ecosystems across large spatial and long temporal scales. These data sets report the outcome of community assembly, in terms of plant community composition and structure and one important ecosystem function (aboveground biomass production), in 29 prairie restorations in southwestern Michigan. We also report putative forces shaping the outcome of assembly including the species pools (seed mixes applied during restoration), site conditions, landscape context, and land-use history. Detailed knowledge of each restoration effort, including seed mixes used, is unusual and makes these data sets uniquely suited to addressing questions in community assembly by comparing the sown seeds and resulting assembled plant community. For example, we have used the data to test the role of species pools in determining the diversity of assembling communities. We have also used the data to characterize the relative importance of various drivers of community assembly outcomes during restoration, as a step toward resolving the highly contingent and unpredictable outcomes that plague the field of ecological restoration. We suggest that these data sets may prove useful for addressing additional questions in community ecology through the lens of ecological restoration.


      Key words: aboveground biomass; community assembly; ecosystem function; prairie restoration; seed mix; species pool.

Manuscript Abstract: Ecologists have long sought to understand space use and mechanisms underlying patterns observed in nature. We developed an optimality landscape and mechanistic territory model to understand mechanisms driving space use and compared model predictions to empirical reality. We demonstrate our approach using gray wolves (Canis lupus). In the model, simulated animals selected territories to economically acquire resources by selecting patches with greatest value, accounting for benefits, costs, and tradeoffs of defending and using space on the optimality landscape. Our approach successfully predicted and explained first- and second-order space use of wolves, including the population's distribution, territories of individual packs, and influences of prey density, competitor density, human-caused mortality risk, and seasonality. It accomplished this using simple behavioral rules and limited data to inform the optimality landscape. Results contribute evidence that economical territory selection is a mechanistic bridge between space use and animal distribution on the landscape. This approach and resulting gains in knowledge enable predicting effects of a wide range of environmental conditions, contributing to both basic ecological understanding of natural systems and conservation. We expect this approach will demonstrate applicability across diverse habitats and species, and that its foundation can help continue to advance understanding of spatial behavior.

Model & Data Abstract: In support of the above manuscript, all model files and data to re-create the analyses for the manuscript are included on Dryad. The model can be run in NetLogo (installation file included), using the associated input files to build the Montana landscape for wolves. Expertise in NetLogo is strongly recommended for using this model. Output files are likewise included along with code to create each plot in the manuscript and SI. Software files for the model and code to create each plot in the manuscript are located at Zenodo: https://doi.org/10.5281/zenodo.5802243.

The dataset contains data collected through concept maps and questionnaires pre- and post- an educational program for high school students. Concept maps and questionnaires were developed by the project team to assess differences in student understanding and student perceptions of ecological processes and restoration and monitoring efforts by scientists. Both concept maps and questionnaires were distributed at the same time to high school students on the Mississippi Gulf Coast with schools that participated in the CHANGES program. Data collected include concept map scores, which were scored by the project team using Novak’s scoring for using concept mapping as an assessment tool. Questionnaire data include student answers to statements about natural and manmade changes affecting an estuary or savanna ecosystem in a positive or negative way. Students answered through a 5- point Likert scale (strongly disagree to strongly agree). Additionally, students listed stewardship actions they could identify pre- and post- CHANGES program. Data were collected from March 2019 through March 2020. The data collected informed an in-house evaluation of program effectiveness.

This dataset contains information on vegetation at a set of field sites along with associated environmental data extracted from spatial layers and selected ecological statistics. Measurements of vascular plants include species, growth form, height and cover from 1010 point intercepts per plot as well as systematically recorded absences, which are useful for predictive modelling and validation of remote sensing applications. The derived cover estimates are robust and repeatable, allowing comparisons among environments and detection of modest change. The field plots span a rainfall gradient of 129-1437 mm Mean Annual Precipitation ranging from aseasonal to highly seasonal. The dataset consists of a processed version the AusPlots Rangelands dataset with three components: 1) a site table with locality, environmental and summary ecology statistics for each plot; 2) a set of compiled point intercept records identified by individual hits, site visits and plots and; 3) a processed species percent cover against site/visit matrix for ecological analysis. The data have re-use potential for studies on vegetation properties in the Australian rangelands or as a species presence/absence dataset for testing ecological models. The dataset also provides opportunities for generic application such as testing community ecology theories or developing or demonstrating community ecology software, whether using the raw point by point intercept data or the derived percent cover matrix.

Movement patterns and habitat selection of animals have important implications for ecology and evolution. Darwin's finches are a classic model system for ecological and evolutionary studies, yet their spatial ecology remains poorly studied. We tagged and radio-tracked five (three females, two males) medium ground finches (Geospiza fortis) to examine the feasibility of telemetry for understanding their movement and habitat use. Based on 143 locations collected during a three-week period, we analysed, for the first time, home-range size and habitat selection patterns of finches at El Garrapatero, an arid coastal ecosystem on Santa Cruz Island (Galápagos). The average 95% home range and 50% core area for G. fortis in the breeding season were 20.54 ha ± 4.04 ha SE and 4.03 ha ± 1.11 ha SE, respectively. For most of the finches, their home range covered a diverse set of habitats. Three finches positively selected the dry-forest habitat, while the other habitats seemed to be either negatively selected or simply neglected by the finches. In addition, we noted a communal roosting behaviour in an area close to the ocean, where the vegetation is greener and denser than the more inland dry-forest vegetation. We show that telemetry on Darwin’s finches provides valuable data to understand the movement ecology of the species. Based on our results, we propose a series of questions about the ecology and evolution of Darwin’s finches that can be addressed using telemetry. Methods Please, refer to the article and the README.

This body of research contributes to the field of environmental communication, by expanding upon the more traditional notion of one-way 'messaging'. Rather, by integrating theory and practice, environmental communication is posited as developing a community’s own ecological storytelling capacity, and enhancing local capacity to identify and address environmental problems. The work draws from concepts in many fields including media communication, and the environmental humanities, but is grounded in creative practice as research.This item contains the research outputs and supportive evidence documentation for a Type T output, created for submission to REF2021. The article, A crisis discipline: broadening understanding of environmental communication through theory and practice, originally appeared in the The International Journal of Creative Media Research, and can be additionally accessed at the following link: https://doi.org/10.33008/IJCMR.2019.16The film TIMELINE is published on the peer-reviewed site, SCREENWORKS: TIMELINE - Screenworks where the research statement and judges' comments are also included. The film is can be additionally accessed at https://vimeo.com/172669824The list of funding grants below is detailed further in the Research Timeline (see file 2), which provides information on the chronological progression of the overall research.

Time series: benthic taxa abundance data for Dove Station M1 (1972-2012)This file contains data on the abundances (per square metre) of benthic macroinfaunal taxa sampled at Dove Station M1 in the central-western North Sea, 10.5 km east of the Northumberland coast. These data were used to derive the principal components analysed in the paper 'Explaining ecological shifts: The roles of temperature and primary production in the long-term dynamics of benthic faunal composition' by Clare et al. The time series runs from autumn 1972 to autumn 2012. Samples were collected in the spring and autumn of each year, with few exceptions. All taxa that occurred at a density of ten or more individuals per square metre, at any single sampling occasion, are included in this data set.Benthic taxa abundance data Dove Station M1 (1972-2012).csv