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Algorithm selection for optimal ecological monitoring design

While all algorithms outperformed simple random samples, performance differences were negligible between algorithms and it is recommended that practitioners choose algorithms based on feature availability, which varies greatly between algorithms.

Deciphering Probabilistic Species Interaction Networks

Two approaches to inferring binary interactions from probabilistic ones are presented that account for these differences and it is shown that systematic biases arise when directly inferring local networks from metawebs.
PubMed (opens in a new tab)

Exposure of western United States bird communities to predicted high severity fire

Fire is a pervasive biogeographic process that shapes biodiversity globally and is now experiencing unprecedented changes. Despite well documented impacts of fires on biodiversity, we do not know…
Springer Nature (opens in a new tab)

The role of AI in ecology’s computational carbon footprint

Publisher (opens in a new tab)

Site selection algorithms for optimal ecological monitoring design

Comprehensive monitoring of biodiversity to direct conservation action is foundational to addressing the ongoing biodiversity crisis. As integrative monitoring programs increasingly come online in…
PubMed (opens in a new tab)

Biodiversity monitoring for a just planetary future

This work examines two contentious questions that arise as it considers the disparities in biodiversity data and their consequences in the wake of contemporary biodiversity policy: Are the best available data really a suitable standard?
Science (opens in a new tab)
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