Identifying exact species extinction risks has been a challenge for scientists for centuries. The IUCN Red List is the most widely accepted classification system, but is sometimes biased towards larger and more easily sampled species. In the article “An integrated trait-based framework to predict extinction risk and guide conservation planning in biodiversity hotspots,” the authors use base knowledge from the IUCN Red List population trends and “expert-perceived” vulnerability of environmental changes as the response variables for determining the risk of extinction for 195 amphibians in the Brazilian Cerrado. This is the world’s most biodiverse savanna as well as the largest. With the creation of this specialized extinction risk framework, the results show that the worldwide extinction risk for amphibians is underestimated by the IUCN.

The data utilized to address the research topic was reports of acts, events or behavior and acts, behavior, or events. The goal of building this framework is so that any biologist can add additional species-specific predicators on top of the basic data obtained from the IUCN. With that goal in mind, the authors obtained that data from public records from the IUCN, expert knowledge and observations; a very in depth data collection method. Although an extensive data collection method, the analysis of the data was through random forest models. They then assessed the accuracy of the models through the percentage of species correctly classified, the percentage of species not threatened that are correctly classified, and percentage of threatened species that are correctly classified with a statistical constant testing for agreement between the two classification systems.

Overall, this article was the most helpful article I have found on my research topic so far. It highlighted various ways to define priority areas for species with a lack of data and what predictors to use when attempting to create a more in depth classification system. This article also makes me question how many more taxa are underestimated for extinction risks. It is a daunting task for a scientist striving to save all the species we co-inhabit this planet with.

Joana Ribeiro, Guarino R. Colli, Janalee P. Caldwell, Amadeu M.V.M. Soares, An integrated trait-based framework to predict extinction risk and guide conservation planning in biodiversity hotspots, Biological Conservation, Volume 195, March 2016, Pages 214-223, ISSN 0006-3207, http://dx.doi.org/10.1016/j.biocon.2015.12.042.

Sourced from the Ecological Restoration journal, authors Rosaleen G. March and Elizabeth H. Smith demonstrate a data analysis technique utilizing spatial data to locate target areas for restoration in their article “Combining Available Spatial Data to De ne Restoration Goals.” The technique utilizes public soil data from Natural Resources Conservation Services (NRCS) website to identify the natural vegetation characteristic with each specific soil type. This creates a base map of “grouped ecological sites” that then is overlaid with current land use and zoning patterns. The authors tested their method on 2 barrier strandplain peninsulas in the Texas Coastal Bend—Lamar and Live Oak peninsulas to find target areas with ease. Results show two target areas including a highway median that would be ideal for restoration. March and Smith use reports of acts, behaviors or events from the Natural Resource Conservation Service (NRCS) to answer their research question. They gathered this data from public records and imagery from the software ArcGIS. This is the same software utilized in spatial studies courses at the University of Redlands and is available on all the PC computers connected to the school’s server for students to use. By adding the current land use patterns over the blocks of potential vegetation based off soil data, target areas are easily identifiable with by just observing the map. This method of data analysis, I believe, is the way of the future. Patterns in data can be easily identified when displayed spatially.

March, R. G., & Smith, E. H. (2011). Combining Available Spatial Data to Define Restoration Goals. Ecological Restoration, 29(3), 252-260.

In the journal Ecology: A publication of the Ecological Society of America, Anne Blach-Overgaard and other ecologists part of the Ecoinformatics and Biodiversity Group in Aarhus, Denmark published an article titled: “Multimillion-year climatic effects on palm species diversity in Africa.” The article demonstrates that the species diversity and richness of the palm species from tropical, subtropical and dry-tropical climates throughout Africa are deeply influenced by historical climatic patterns that runs deeper than previously expected. By obtaining continent-scale data on precipitation, temperature and species richness from the late Miocene period (~10 mya), the Pliocene (~3 mya) and the Last Glacial Maximum (0.021 mya), the results show that climate change affects diversity patterns over multimillion-year “historical legacies” that extended farther back in the geological time scale than previously expected. The article uses a combination of acts, behavior, or events and reports of acts, behavior, or events data to conduct their analysis due to the combination of historical records on the species and data directly surveyed by the ecologists. The data was obtained from public and privates records, as well as detached observation of the species patterns and species distribution modeling created by the authors for this study. Statistical analysis for this study consisted of calculating bivariate correlations between the response variables (species richness) and the potential predictors (temperature and precipitation). A second multivariate analysis was conducted to compare the categorized response variables of total species richness, rain forest species richness and open-habitat species richness. The results included beautiful maps of Africa showing the data collection that easily identify the patterns with intriguing results about how far back climatic changes can affect an entire family of plants. I was initially curious about why the authors chose the palm family (Arecaceae), but they article quickly answered my question by addressing that they are keystone species for tropical and subtropical regions. It just goes to show that what anthropocentric changes to climate we cause today will affect species distribution on the planet for millions of years.

Blach-Overgaard, A., Kissling, W., Dransfield, J., Balslev, H., & Svenning, J. (2013). Multimillion-year climatic effects on palm species diversity in Africa. Ecology, 94(11), 2426-2435. Retrieved from http://www.jstor.org/stable/23597204