Geology ReportsSearch

Geology topics

Andrew Allstadt

Publications and source records attributed to Andrew Allstadt.

2 recordsLinked to original sources

Connecting and coordinating conservation action across landscapes through regional planning processes and syntheses

Modern threats to conservation are often global; however, relevant conservation decisions and actions typically occur within local jurisdictions. The socio-ecological complexity of these problems requires collaboration across large landscapes, diverse community interests, and geopolitical boundaries, yet a lack of interoperability of planning products among decision makers, jurisdictions, and objectives impedes collaboration. Here, we provide a working model for the collaborative, iterative development of a landscape conservation design (LCD) in the Midwest region of the United States, the Midwest Conservation Blueprint, and demonstrate its applicability to the coordination of voluntary conservation actions and investments across jurisdictional boundaries. We used spatial prioritization software to synthesize over 20 datasets to develop a basemap of priority lands and waters for conservation across a diverse set of societal and ecological values (e.g., water quality, biodiversity, recreation). The Midwest Conservation Blueprint is a living plan, updated annually based on improvements in underlying data, understanding of local conditions, and public input. Landscape-scale planning is not designed to replace local knowledge or supersede decision-making authorities. However, by synthesizing existing data that represent diverse socio-ecological values and planning at a broader scale, the Midwest Conservation Blueprint documents where there are shared priorities and opportunities for collaborative landscape conservation.

Midwest

Evaluation of downscaled, gridded climate data for the conterminous United States

Weather and climate affect many ecological processes, making spatially continuous yet fine-resolution weather data desirable for ecological research and predictions. Numerous downscaled weather data sets exist, but little attempt has been made to evaluate them systematically. Here we address this shortcoming by focusing on four major questions: (1) How accurate are downscaled, gridded climate data sets in terms of temperature and precipitation estimates?, (2) Are there significant regional differences in accuracy among data sets?, (3) How accurate are their mean values compared with extremes?, and (4) Does their accuracy depend on spatial resolution? We compared eight widely used downscaled data sets that provide gridded daily weather data for recent decades across the United States. We found considerable differences among data sets and between downscaled and weather station data. Temperature is represented more accurately than precipitation, and climate averages are more accurate than weather extremes. The data set exhibiting the best agreement with station data varies among ecoregions. Surprisingly, the accuracy of the data sets does not depend on spatial resolution. Although some inherent differences among data sets and weather station data are to be expected, our findings highlight how much different interpolation methods affect downscaled weather data, even for local comparisons with nearby weather stations located inside a grid cell. More broadly, our results highlight the need for careful consideration among different available data sets in terms of which variables they describe best, where they perform best, and their resolution, when selecting a downscaled weather data set for a given ecological application.

Ecological Applications