Publications by authors named "B McKay Allred"

Positive outcomes from undergraduate research experiences (UREs) have resulted in calls to broaden and diversify participation in research. However, we have little understanding of what demographics are reported and considered in the analyses of student outcomes from UREs. Without this information, it is impossible to assess whether participation in UREs has been diversified and how outcomes may vary by participant identity.

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Article Synopsis
  • Understanding the extent of subsurface drainage (tile-drain) is crucial for analyzing landscape responses to rainfall and soil management impacts on stream health and water quality.
  • A UNet machine-learning model was developed to detect tile-drain networks in satellite images without needing detailed data on soil or terrain, achieving high accuracy similar to expert manual tracing.
  • The model performed best in spring conditions, identifying tile drains with 93%-96% accuracy, thus helping to manage nutrient and sediment flow which is essential for addressing issues like harmful algal blooms.
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Animal movement patterns are affected by complex interactions between biotic and abiotic landscape conditions, and these patterns are being altered by weather variability associated with a changing climate. Some animals, like the American plains bison ( L.; hereafter, plains bison), are considered keystone species, thus their response to weather variability may alter ecosystem structure and biodiversity patterns.

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Historically, relying on plot-level inventories impeded our ability to quantify large-scale change in plant biomass, a key indicator of conservation practice outcomes in rangeland systems. Recent technological advances enable assessment at scales appropriate to inform management by providing spatially comprehensive estimates of productivity that are partitioned by plant functional group across all contiguous US rangelands. We partnered with the Sage Grouse and Lesser Prairie-Chicken Initiatives and the Nebraska Natural Legacy Project to demonstrate the ability of these new datasets to quantify multi-scale changes and heterogeneity in plant biomass following mechanical tree removal, prescribed fire, and prescribed grazing.

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In this era of global environmental change and rapid regime shifts, managing core areas that species require to survive and persist is a grand challenge for conservation. Wildlife monitoring data are often limited or local in scale. The emerging ability to map and track spatial regimes (i.

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