Using a trait‐based dark diversity approach to evaluate natural recovery potential in forests

Abstract

Utilizing ecosystems' natural recovery potential is crucial for enhancing the scale and efficacy of restoration efforts. However, this potential is currently underutilized in restoration ecology, and barriers to natural species recruitment remain poorly understood. In this study, we develop an analytical framework that combines trait‐based and dark diversity approaches to evaluate understory plant community recovery in smelter‐impacted forests and identify factors limiting recovery for absent species. A community completeness index (CCI) was calculated in 18 naturally recovering smelter‐impacted forests and three reference forests in Sudbury, Ontario, Canada. The CCI was used to identify sites that deviate the most from their target communities and was compared to traditionally used indicators of plant recovery. Community weighted means (CWM) of traits for observed and dark diversity species were compared, and principal components analysis was used to identify relationships between traits of observed and missing species among study sites. Species unable to recover passively (i.e. with high dark diversity probabilities) were generally tall and/or large seeded. Understory plant community recovery was structured along two functional gradients, plant economics and size, which both coincided with distance to the smelter. Dark diversity and trait analyses were useful for identifying barriers to natural recovery and, therefore, providing guidance on targeted restoration actions. We conclude by discussing the limitations and opportunities of the dark diversity approach in a restoration context, highlighting the importance of carefully defining habitat‐specific species pools and critically assessing the ecological significance of dark diversity probabilities.