The Portal Project: a long-term study of a Chihuahuan desert ecosystem

Ernest, S. K. Morgan; Yenni, Glenda M.; Allington, Ginger R.H.; Bledsoe, Ellen K.; Em, Christensen; Rm, Díaz Romero; Geluso, Keith; Goheen,; Guo, Qinfeng; Heske, Edward J.; Kelt, Douglas A.; Meiners, Joan M.; Munger, James C.; Restrepo, Carla; Da, Samson; Mr, Schutzenhofer; Skupski, Marian P.; Supp,; Thibault, Katherine M.; Taylor, Shawn D.; White, Ethan P.; H, Ye; Dw, Davidson; Jh, Brown; Tj, Valone

doi:10.1101/332783

Cited by 19 publications

(26 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Portal Project is a long-term ecological study situated in the Chihuahuan Desert (2 km north and 6.5 km east of Portal, Arizona, US). Researchers have been continuously collecting data at the site since 1977, including data on the abundance of rodent and plant species (monthly and twice yearly, respectively) and climatic factors such as air temperature and precipitation (daily) (Brown, 1998; Ernest et al, 2009, 2016, 2018). The site consists of 24 50m x 50m experimental plots.…”

Section: System Backgroundmentioning

confidence: 99%

Developing an automated iterative near-term forecasting system for an ecological study

White

Yenni

Taylor

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

131. Most forecasts for the future state of ecological systems are conducted once and 14 never updated or assessed. As a result, many available ecological forecasts are not 15 based on the most up-to-date data, and the scientific progress of ecological 16 forecasting models is slowed by a lack of feedback on how well the forecasts 17 perform. 18 2. Iterative near-term ecological forecasting involves repeated daily to annual scale 19 1 forecasts of an ecological system as new data becomes available and regular 20 assessment of the resulting forecasts. We demonstrate how automated iterative 21 near-term forecasting systems for ecology can be constructed by building one to 22 conduct monthly forecasts of rodent abundances at the Portal Project, a long-term 23 study with over 40 years of monthly data. This system automates most aspects of 24 the six stages of converting raw data into new forecasts: data collection, data 25 sharing, data manipulation, modeling and forecasting, archiving, and presentation 26 of the forecasts. 273. The forecasting system uses R code for working with data, fitting models, making 28 forecasts, and archiving and presenting these forecasts. The resulting pipeline is 29 automated using continuous integration (a software development tool) to run the 30 entire pipeline once a week. The cyberinfrastructure is designed for long-term 31 maintainability and to allow the easy addition of new models. Constructing this 32 forecasting system required a team with expertise ranging from field site 33 experience to software development. 34 4. Automated near-term iterative forecasting systems will allow the science of 35 ecological forecasting to advance more rapidly and provide the most up-to-date 36 forecasts possible for conservation and management. These forecasting systems 37 will also accelerate basic science by allowing new models of natural systems to 38 be quickly implemented and compared to existing models. Using existing 39 technology, and teams with diverse skill sets, it is possible for ecologists to build 40 automated forecasting systems and use them to advance our understanding of 41 natural systems. 42 Forecasting the future state of ecological systems is important for management, 45 conservation, and evaluation of how well models capture the processes governing 46 ecological systems (Clark et al., 2001; Tallis & Kareiva, 2006; Díaz et al., 2015; Dietze, 47 2017). In 2001, Clark et al. (2001 called for a more central role of forecasting in 48 ecology. Since then, an increasing number of ecological forecasts are being published 49 that focus on societally important questions from daily to decadal time scales (Dietze et 50 al., 2018). At daily scales, ecological forecasts predict the occurrence of environmental 51 issues like toxic algal blooms (Stumpf et al., 2009) and pollen (Prank et al., 2013). At 52 monthly scales, forecasts are used to predict the stocks of fisheries (NOAA, 2016) and 53 the probability of coral bleaching events (Liu et al., 2018). At decada...

show abstract

Section: System Backgroundmentioning

confidence: 99%

Developing an automated iterative near-term forecasting system for an ecological study

White

Yenni

Taylor

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…A variety of initiatives provide freely available data sets to be slotted into existing courses for specific learning objectives (e.g., the Portal Project Teaching Database, Ernest et al 2015; NEON Teaching Data Subsets, https://dx.doi.org/10.6084/m9.figshare.2009586.v9 ). It is also becoming more common for instructors to openly share their full course materials.…”

Section: Changes In Mindsetmentioning

confidence: 99%

Skills and Knowledge for Data-Intensive Environmental Research

Hampton¹,

Jones²,

Wasser³

et al. 2017

BioScience

Self Cite

View full text Add to dashboard Cite

The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap.

show abstract

“…Rodent abundance and composition data are collected monthly using Sherman live traps (Ernest et al. ). We identify trapped individuals to species and give each rodent an individualizing marker (previously toe and ear tags, now exclusively passive integrated transponder [PIT] tags).…”

Section: Methodsmentioning

confidence: 99%

Temporal changes in species composition affect a ubiquitous species’ use of habitat patches

Bledsoe

Ernest

2019

Ecology

Self Cite

View full text Add to dashboard Cite

Across landscapes, shifts in species composition often co‐occur with shifts in structural or abiotic habitat features, making it difficult to disentangle the role of competitors and environment on assessments of patch quality. Using over two decades of rodent community data from a long‐term experiment, we show that a small, ubiquitous granivore (Chaetodipus penicillatus) shifted its use of different experimental treatments with the establishment of a novel competitor, C. baileyi. Shifts in residency, probability of movement between patches, and the arrival of new individuals in patches altered which treatment supported the highest abundances of C. penicillatus. Our results suggest that the establishment of a new species worsened the quality of the originally preferred treatment, likely by impacting resource availability. Paradoxically, the presence of the new species also increased C. penicillatus’ use of the less preferred treatment, potentially through shifts in the competitive network on those plots.

show abstract

The Portal Project: a long-term study of a Chihuahuan desert ecosystem

Cited by 19 publications

References 20 publications

Developing an automated iterative near-term forecasting system for an ecological study

Developing an automated iterative near-term forecasting system for an ecological study

Skills and Knowledge for Data-Intensive Environmental Research

Temporal changes in species composition affect a ubiquitous species’ use of habitat patches

Contact Info

Product

Resources

About