Identifying robust strategies for assisted migration in a competitive stochastic metacommunity.

Assisted migration (AM) is the translocation of species beyond their historical range to locations that are expected to be more suitable under future climate change. However, a relocated population may fail to establish in its donor community if there is high uncertainty in decision-making, climate, and interactions with the recipient ecological community. To quantify the benefit to persistence and risk of establishment failure of AM under different management scenarios (e.g., choosing target species, proportion of population to relocate, and optimal location to relocate), we built a stochastic metacommunity model to simulate several species reproducing, dispersing, and competing on a temperature gradient as temperature increases over time. Without AM, the species were vulnerable to climate change when they had low population sizes, short dispersal, and strong poleward competition. When relocating species that exemplified these traits, AM increased the long-term persistence of the species most when relocating a fraction of the donor population, even if the remaining population was very small or rapidly declining. This suggests that leaving behind a fraction of the population could be a robust approach, allowing managers to repeat AM in case they move the species to the wrong place and at the wrong time, especially when it is difficult to identify a species' optimal climate. We found that AM most benefitted species with low dispersal ability and least benefited species with narrow thermal tolerances, for which AM increased extinction risk on average. Although relocation did not affect the persistence of nontarget species in our simple competitive model, researchers will need to consider a more complete set of community interactions to comprehensively understand invasion potential.

Identificación de Estrategias Sólidas para la Migración Asistida en una Metacomunidad Estocástica Competitiva Resumen La migración asistida es la translocación de especies más allá de su extensión histórica a localidades que se espera sean más adecuadas bajo el cambio climático futuro. Sin embargo, una población reubicada puede no establecerse en su comunidad donante si existe una mucha incertidumbre en cuanto a la toma de decisiones, el clima y las interacciones con la comunidad ecológica receptora. Para cuantificar el beneficio para la persistencia y el riesgo de fallas en el establecimiento de la migración asistida bajo diferentes escenarios de manejo (p. ej.: elección de especies objetivo, proporción de la población a reubicar y localidad óptima para la reubicación) construimos un modelo de metacomunidad estocástica para simular la reproducción, dispersión y competencia de varias especies a lo largo de un gradiente de temperatura conforme la temperatura incrementa con el tiempo. Sin la migración asistida, las especies presentaron vulnerabilidad ante el cambio climático cuando presentaron un tamaño poblacional menor, una dispersión reducida y una competencia fuerte hacia los extremos. Cuando se reubicó a especies con estas características, la migración asistida incrementó más la persistencia a largo plazo de las especies cuando se reubicó una fracción de la población donante, incluso si la población remanente era muy pequeña o se encontraba en una rápida declinación. Esto sugiere que dejar una fracción de la población podría ser una estrategia sólida que permite a los gestores repetir la migración asistida en caso de que muden a la especie al lugar equivocado en el momento equivocado, especialmente cuando es difícil identificar el clima óptimo de la especie. Descubrimos que la migración asistida benefició más a las especies con una baja habilidad de dispersión y tuvo menos beneficios para las especies con una tolerancia térmica reducida, para las que la migración asistida aumentó en promedio el riesgo de extinción. Aunque la reubicación no afectó la persistencia de las especies que no consideramos como objetivo en nuestro modelo competitivo simple, los investigadores necesitarán considerar un conjunto más completo de interacciones comunitarias para entender por completo el potencial de invasión.

Restoring spatiotemporal variability to enhance the capacity for dispersal-limited species to track climate change.

Climate refugia are areas where species can persist through climate change with little to no movement. Among the factors associated with climate refugia are high spatial heterogeneity, such that there is only a short distance between current and future optimal climates, as well as biotic or abiotic environmental factors that buffer against variability in time. However, these types of climate refugia may be declining due to anthropogenic homogenization of environments and degradation of environmental buffers. To quantify the potential for restoration of refugia-like environmental conditions to increase population persistence under climate change, we simulated a population's capacity to track their temperature over space and time given different levels of spatial and temporal variability in temperature. To determine how species traits affected the efficacy of restoring heterogeneity, we explored an array of values for species' dispersal ability, thermal tolerance, and fecundity. We found that species were more likely to persist in environments with higher spatial heterogeneity and lower environmental stochasticity. When simulating a management action that increased the spatial heterogeneity of a previously homogenized environment, species were more likely to persist through climate change, and population sizes were generally higher, but there was little effect with mild temperature change. The benefits of heterogeneity restoration were greatest for species with limited dispersal ability. In contrast, species with longer dispersal but lower fecundity were more likely to benefit from a reduction in environmental stochasticity than an increase in spatial heterogeneity. Our results suggest that restoring environments to refugia-like conditions could promote species' persistence under the influence of climate change in addition to conservation strategies such as assisted migration, corridors, and increased protection.

Comparing management strategies for conserving communities of climate-threatened species with a stochastic metacommunity model.

Many species are shifting their ranges to keep pace with climate change, but habitat fragmentation and limited dispersal could impede these range shifts. In the case of climate-vulnerable foundation species such as tropical reef corals and temperate forest trees, such limitations might put entire communities at risk of extinction. Restoring connectivity through corridors, stepping-stones or enhanced quality of existing patches could prevent the extinction of several species, but dispersal-limited species might not benefit if other species block their dispersal. Alternatively, managers might relocate vulnerable species between habitats through assisted migration, but this is generally a species-by-species approach. To evaluate the relative efficacy of these strategies, we simulated the climate-tracking of species in randomized competitive metacommunities with alternative management interventions. We found that corridors and assisted migration were the most effective strategies at reducing extinction. Assisted migration was especially effective at reducing the extinction likelihood for short-dispersing species, but it often required moving several species repeatedly. Assisted migration was more effective at reducing extinction in environments with higher stochasticity, and corridors were more effective at reducing extinction in environments with lower stochasticity. We discuss the application of these approaches to an array of systems ranging from tropical corals to temperate forests. This article is part of the theme issue 'Ecological complexity and the biosphere: the next 30 years'.

Acoustic sequences in non-human animals: a tutorial review and prospectus.

Animal acoustic communication often takes the form of complex sequences, made up of multiple distinct acoustic units. Apart from the well-known example of birdsong, other animals such as insects, amphibians, and mammals (including bats, rodents, primates, and cetaceans) also generate complex acoustic sequences. Occasionally, such as with birdsong, the adaptive role of these sequences seems clear (e.g. mate attraction and territorial defence). More often however, researchers have only begun to characterise - let alone understand - the significance and meaning of acoustic sequences. Hypotheses abound, but there is little agreement as to how sequences should be defined and analysed. Our review aims to outline suitable methods for testing these hypotheses, and to describe the major limitations to our current and near-future knowledge on questions of acoustic sequences. This review and prospectus is the result of a collaborative effort between 43 scientists from the fields of animal behaviour, ecology and evolution, signal processing, machine learning, quantitative linguistics, and information theory, who gathered for a 2013 workshop entitled, 'Analysing vocal sequences in animals'. Our goal is to present not just a review of the state of the art, but to propose a methodological framework that summarises what we suggest are the best practices for research in this field, across taxa and across disciplines. We also provide a tutorial-style introduction to some of the most promising algorithmic approaches for analysing sequences. We divide our review into three sections: identifying the distinct units of an acoustic sequence, describing the different ways that information can be contained within a sequence, and analysing the structure of that sequence. Each of these sections is further subdivided to address the key questions and approaches in that area. We propose a uniform, systematic, and comprehensive approach to studying sequences, with the goal of clarifying research terms used in different fields, and facilitating collaboration and comparative studies. Allowing greater interdisciplinary collaboration will facilitate the investigation of many important questions in the evolution of communication and sociality.