Applying landscape metrics to species distribution model predictions to characterize internal range structure and associated changes.

Distributional shifts in species ranges provide critical evidence of ecological responses to climate change. Assessments of climate-driven changes typically focus on broad-scale range shifts (e.g. poleward or upward), with ecological consequences at regional and local scales commonly overlooked. While these changes are informative for species presenting continuous geographic ranges, many species have discontinuous distributions-both natural (e.g. mountain or coastal species) or human-induced (e.g. species inhabiting fragmented landscapes)-where within-range changes can be significant. Here, we use an ecosystem engineer species (Sabellaria alveolata) with a naturally fragmented distribution as a case study to assess climate-driven changes in within-range occupancy across its entire global distribution. To this end, we applied landscape ecology metrics to outputs from species distribution modelling (SDM) in a novel unified framework. SDM predicted a 27.5% overall increase in the area of potentially suitable habitat under RCP 4.5 by 2050, which taken in isolation would have led to the classification of the species as a climate change winner. SDM further revealed that the latitudinal range is predicted to shrink because of decreased habitat suitability in the equatorward part of the range, not compensated by a poleward expansion. The use of landscape ecology metrics provided additional insights by identifying regions that are predicted to become increasingly fragmented in the future, potentially increasing extirpation risk by jeopardising metapopulation dynamics. This increased range fragmentation could have dramatic consequences for ecosystem structure and functioning. Importantly, the proposed framework-which brings together SDM and landscape metrics-can be widely used to study currently overlooked climate-driven changes in species internal range structure, without requiring detailed empirical knowledge of the modelled species. This approach represents an important advancement beyond predictive envelope approaches and could reveal itself as paramount for managers whose spatial scale of action usually ranges from local to regional.

Environmental optima for an ecosystem engineer: a multidisciplinary trait-based approach.

A complex interplay of biotic and abiotic factors underpins the distribution of species and operates across different levels of biological organization and life history stages. Understanding ecosystem engineer reproductive traits is critical for comprehending and managing the biodiversity-rich habitats they create. Little is known about how the reproduction of the reef-forming worm, Sabellaria alveolata, varies across environmental gradients. By integrating broad-scale environmental data with in-situ physiological data in the form of biochemical traits, we identified and ranked the drivers of intraspecific reproductive trait variability (ITV). ITV was highest in locations with variable environmental conditions, subjected to fluctuating temperature and hydrodynamic conditions. Our trait selection pointed to poleward sites being the most physiologically stressful, with low numbers of irregularly shaped eggs suggesting potentially reduced reproductive success. Centre-range individuals allocated the most energy to reproduction, with the highest number of intermediate-sized eggs, whilst equatorward sites were the least physiologically stressful, thus confirming the warm-adapted nature of our model organism. Variation in total egg diameter and relative fecundity were influenced by a combination of environmental conditions, which changed depending on the trait and sampling period. An integrated approach involving biochemical and reproductive traits is essential for understanding macro-scale patterns in the face of anthropogenic-induced climate change across environmental and latitudinal gradients.

Coastal warming and wind-driven upwelling: A global analysis.

Long-term sea surface temperature (SST) warming trends are far from being homogeneous, especially when coastal and ocean locations are compared. Using data from NOAA's AVHRR OISST, we have analyzed sea surface temperature trends over the period 1982-2015 at around 3500 worldwide coastal points and their oceanic counterparts with a spatial resolution of 0.25 arc-degrees. Significant warming was observed at most locations although with important differences between oceanic and coastal points. This is especially patent for upwelling regions, where 92% of the coastal locations showed lower warming trends than at neighboring ocean locations. This result strongly suggests that upwelling has the potential to buffer the effects of global warming nearshore, with wide oceanographic, climatic, and biogeographic implications.