Spatial asynchrony and cross-scale climate interactions in populations of a coldwater stream fish.

Climate change affects populations over broad geographic ranges due to spatially autocorrelated abiotic conditions known as the Moran effect. However, populations do not always respond to broad-scale environmental changes synchronously across a landscape. We combined multiple datasets for a retrospective analysis of time-series count data (5-28 annual samples per segment) at 144 stream segments dispersed over nearly 1,000 linear kilometers of range to characterize the population structure and scale of spatial synchrony across the southern native range of a coldwater stream fish (brook trout, Salvelinus fontinalis), which is sensitive to stream temperature and flow variations. Spatial synchrony differed by life stage and geographic region: it was stronger in the juvenile life stage than in the adult life stage and in the northern sub-region than in the southern sub-region. Spatial synchrony of trout populations extended to 100-200 km but was much weaker than that of climate variables such as temperature, precipitation, and stream flow. Early life stage abundance changed over time due to annual variation in summer temperature and winter and spring stream flow conditions. Climate effects on abundance differed between sub-regions and among local populations within sub-regions, indicating multiple cross-scale interactions where climate interacted with local habitat to generate only a modest pattern of population synchrony over space. Overall, our analysis showed higher degrees of response heterogeneity of local populations to climate variation and consequently population asynchrony than previously shown based on analysis of individual, geographically restricted datasets. This response heterogeneity indicates that certain local segments characterized by population asynchrony and resistance to climate variation could represent unique populations of this iconic native coldwater fish that warrant targeted conservation. Advancing the conservation of this species can include actions that identify such priority populations and incorporate them into landscape-level conservation planning. Our approach is applicable to other widespread aquatic species sensitive to climate change.

Estimating thermal performance curves from repeated field observations.

Estimating thermal performance of organisms is critical for understanding population distributions and dynamics and predicting responses to climate change. Typically, performance curves are estimated using laboratory studies to isolate temperature effects, but other abiotic and biotic factors influence temperature-performance relationships in nature reducing these models' predictive ability. We present a model for estimating thermal performance curves from repeated field observations that includes environmental and individual variation. We fit the model in a Bayesian framework using MCMC sampling, which allowed for estimation of unobserved latent growth while propagating uncertainty. Fitting the model to simulated data varying in sampling design and parameter values demonstrated that the parameter estimates were accurate, precise, and unbiased. Fitting the model to individual growth data from wild trout revealed high out-of-sample predictive ability relative to laboratory-derived models, which produced more biased predictions for field performance. The field-based estimates of thermal maxima were lower than those based on laboratory studies. Under warming temperature scenarios, field-derived performance models predicted stronger declines in body size than laboratory-derived models, suggesting that laboratory-based models may underestimate climate change effects. The presented model estimates true, realized field performance, avoiding assumptions required for applying laboratory-based models to field performance, which should improve estimates of performance under climate change and advance thermal ecology.

The rise of novelty in ecosystems.

Rapid and ongoing change creates novelty in ecosystems everywhere, both when comparing contemporary systems to their historical baselines, and predicted future systems to the present. However, the level of novelty varies greatly among places. Here we propose a formal and quantifiable definition of abiotic and biotic novelty in ecosystems, map abiotic novelty globally, and discuss the implications of novelty for the science of ecology and for biodiversity conservation. We define novelty as the degree of dissimilarity of a system, measured in one or more dimensions relative to a reference baseline, usually defined as either the present or a time window in the past. In this conceptualization, novelty varies in degree, it is multidimensional, can be measured, and requires a temporal and spatial reference. This definition moves beyond prior categorical definitions of novel ecosystems, and does not include human agency, self-perpetuation, or irreversibility as criteria. Our global assessment of novelty was based on abiotic factors (temperature, precipitation, and nitrogen deposition) plus human population, and shows that there are already large areas with high novelty today relative to the early 20th century, and that there will even be more such areas by 2050. Interestingly, the places that are most novel are often not the places where absolute changes are largest; highlighting that novelty is inherently different from change. For the ecological sciences, highly novel ecosystems present new opportunities to test ecological theories, but also challenge the predictive ability of ecological models and their validation. For biodiversity conservation, increasing novelty presents some opportunities, but largely challenges. Conservation action is necessary along the entire continuum of novelty, by redoubling efforts to protect areas where novelty is low, identifying conservation opportunities where novelty is high, developing flexible yet strong regulations and policies, and establishing long-term experiments to test management approaches. Meeting the challenge of novelty will require advances in the science of ecology, and new and creative. conservation approaches.