Jenny L. McCune

Quantifying temporal change in biodiversity: challenges and opportunities

Growing concern about biodiversity loss underscores the need to quantify and understand temporal change. Here, we review the opportunities presented by biodiversity time series, and address three related issues: (i) recognizing the characteristics of temporal data; (ii) selecting appropriate statistical procedures for analysing temporal data; and (iii) inferring and forecasting biodiversity change. With regard to the first issue, we draw attention to defining characteristics of biodiversity time series—lack of physical boundaries, uni-dimensionality, autocorrelation and directionality—that inform the choice of analytic methods. Second, we explore methods of quantifying change in biodiversity at different timescales, noting that autocorrelation can be viewed as a feature that sheds light on the underlying structure of temporal change. Finally, we address the transition from inferring to forecasting biodiversity change, highlighting potential pitfalls associated with phase-shifts and novel conditions.

Plant Biodiversity Change Across Scales During the Anthropocene

Plant communities have undergone dramatic changes in recent centuries, although not all such changes fit with the dominant biodiversity-crisis narrative used to describe them. At the global scale, future declines in plant species diversity are highly likely given habitat conversion in the tropics, although few extinctions have been documented for the Anthropocene to date (<0.1%). Nonnative species introductions have greatly increased plant species richness in many regions of the world at the same time that they have led to the creation of new hybrid polyploid species by bringing previously isolated congeners into close contact. At the local scale, conversion of primary vegetation to agriculture has decreased plant diversity, whereas other drivers of change-e.g., climate warming, habitat fragmentation, and nitrogen deposition-have highly context-dependent effects, resulting in a distribution of temporal trends with a mean close to zero. These results prompt a reassessment of how conservation goals are defined and justified.

Using plant traits to predict the sensitivity of colonizations and extirpations to landscape context

Theory suggests that species with different traits will respond differently to landscape fragmentation. Studies have shown that the presence of species in fragments of varying size, shape and connectivity is dependent on plant traits related to dispersal ability, persistence and disturbance tolerance. However, the role of traits in determining long-term plant community changes in response to changing landscape context is not well understood. We used data from resurveys of 184 plots to test the ability of nine plant traits to predict colonizations and extirpations between 1968 and 2009 based on the surrounding landscape context. We related apparent colonizations and extirpations to road density, naturally vegetated area and patch shape and then tested for significant relationships between a tendency for positive or negative associations and plant traits. Exotic, herbaceous, annual, shade-intolerant species and species with higher specific leaf area were more likely than others to colonize plots with higher road density, lower amount of naturally vegetated area and higher edge-to-area ratio. However, extirpations were rarely predictable based on traits. The role of landscape context in structuring plant community change over the past four decades in the 184 plots resurveyed was largely mediated by colonization events, suggesting that trait-based extirpations occur with a longer post-fragmentation time lag or, alternatively, that extirpation is more stochastic with respect to plant traits than is colonization.

Context-dependent interactions and the regulation of species richness in freshwater fish

Species richness is regulated by a complex network of scale-dependent processes. This complexity can obscure the influence of limiting species interactions, making it difficult to determine if abiotic or biotic drivers are more predominant regulators of richness. Using integrative modeling of freshwater fish richness from 721 lakes along an 11o latitudinal gradient, we find negative interactions to be a relatively minor independent predictor of species richness in lakes despite the widespread presence of predators. Instead, interaction effects, when detectable among major functional groups and 231 species pairs, were strong, often positive, but contextually dependent on environment. These results are consistent with the idea that negative interactions internally structure lake communities but do not consistently ‘scale-up’ to regulate richness independently of the environment. The importance of environment for interaction outcomes and its role in the regulation of species richness highlights the potential sensitivity of fish communities to the environmental changes affecting lakes globally.Species richness patterns are driven by biotic and abiotic factors, the relative strengths of which are unclear. Here, the authors test how species interactions or environmental traits influence fish richness across over 700 Canadian lakes, showing a surprisingly small role of negative interactions.