Assigning trend-based conservation status despite high uncertainty.

Estimates of temporal trends in species' occupancy are essential for conservation policy and planning, but limitations to the data and models often result in very high trend uncertainty. A critical source of uncertainty that degrades scientific credibility is that caused by disagreement among studies or models. Modelers are aware of this uncertainty but usually only partially estimate it and communicate it to decision makers. At the same time, there is growing awareness that full disclosure of uncertainty is critical for effective translation of science into policies and plans. But what are the most effective approaches to estimating uncertainty and communicating uncertainty to decision makers? We explored how alternative approaches to estimating and communicating uncertainty of species trends could affect decisions concerning conservation status of freshwater fishes. We used ensemble models to propagate trend uncertainty within and among models and communicated this uncertainty with categorical distributions of trend direction and magnitude. All approaches were designed to fit an established decision-making system used to assign species conservation status by the New Zealand government. Our results showed how approaches that failed to fully disclose uncertainty, while simplifying the information presented, could hamper species conservation or lead to ineffective decisions. We recommend an approach that was recently used effectively to communicate trend uncertainty to a panel responsible for setting the conservation status of New Zealand's freshwater fishes.

Designación del estado de conservación basada en tendencias a pesar de gran incertidumbre Resumen Las estimaciones de las tendencias temporales de la presencia de especies son esenciales para la planeación de la conservación y sus políticas, pero las limitaciones de los datos y los modelos suelen derivar en una incertidumbre muy elevada en cuanto a las tendencias. Los desacuerdos entre los estudios y los modelos son una fuente importante de incertidumbre que contribuye a la degradación de la credibilidad científica. Los modeladores están conscientes de esta incertidumbre, pero casi nunca la estiman o comunican por completo a los responsables de las decisiones. Al mismo tiempo, cada vez hay mayor conciencia de que divulgar esta incertidumbre es importante para que la ciencia se traduzca efectivamente en políticas y planes. ¿Pero cuáles son las estrategias más efectivas para estimar la incertidumbre y comunicarla a los responsables de las decisiones? Exploramos cómo las estrategias alternativas para estimar y comunicar la incertidumbre que rodea a las tendencias de las especies podría afectar las decisiones con respecto al estado de conservación de los peces de agua dulce. Usamos modelos de conjuntos para propagar la incertidumbre dentro y entre modelos y comunicamos esta incertidumbre con distribuciones categóricas de la dirección y magnitud de la tendencia. Diseñamos todas las estrategias para que se ajustaran a un sistema establecido de toma de decisiones que usa el gobierno de Nueva Zelanda para designar el estado de conservación de las especies. Nuestros resultados mostraron cómo las estrategias que no divulgaron por completo la incertidumbre, mientras simplificaban la información presentada, podrían dificultar la conservación de las especies o llevar a decisiones poco efectivas. Recomendamos una estrategia que se usó recientemente para comunicar eficientemente la incertidumbre de las tendencias a un panel responsable de establecer el estado de conservación de los peces de agua dulce de Nueva Zelanda.

Metabolism drives distribution and abundance in extremophile fish.

Differences in population density between species of varying size are frequently attributed to metabolic rates which are assumed to scale with body size with a slope of 0.75. This assumption is often criticised on the grounds that 0.75 scaling of metabolic rate with body size is not universal and can vary significantly depending on species and life-history. However, few studies have investigated how interspecific variation in metabolic scaling relationships affects population density in different sized species. Here we predict inter-specific differences in metabolism from niche requirements, thereby allowing metabolic predictions of species distribution and abundance at fine spatial scales. Due to the differences in energetic efficiency required along harsh-benign gradients, an extremophile fish (brown mudfish, Neochanna apoda) living in harsh environments had slower metabolism, and thus higher population densities, compared to a fish species (banded kokopu, Galaxias fasciatus) in physiologically more benign habitats. Interspecific differences in the intercepts for the relationship between body and density disappeared when species mass-specific metabolic rates, rather than body sizes, were used to predict density, implying population energy use was equivalent between mudfish and kokopu. Nevertheless, despite significant interspecific differences in the slope of the metabolic scaling relationships, mudfish and kokopu had a common slope for the relationship between body size and population density. These results support underlying logic of energetic equivalence between different size species implicit in metabolic theory. However, the precise slope of metabolic scaling relationships, which is the subject of much debate, may not be a reliable indicator of population density as expected under metabolic theory.

The scaling of population persistence with carrying capacity does not asymptote in populations of a fish experiencing extreme climate variability.

Despite growing concerns regarding increasing frequency of extreme climate events and declining population sizes, the influence of environmental stochasticity on the relationship between population carrying capacity and time-to-extinction has received little empirical attention. While time-to-extinction increases exponentially with carrying capacity in constant environments, theoretical models suggest increasing environmental stochasticity causes asymptotic scaling, thus making minimum viable carrying capacity vastly uncertain in variable environments. Using empirical estimates of environmental stochasticity in fish metapopulations, we showed that increasing environmental stochasticity resulting from extreme droughts was insufficient to create asymptotic scaling of time-to-extinction with carrying capacity in local populations as predicted by theory. Local time-to-extinction increased with carrying capacity due to declining sensitivity to demographic stochasticity, and the slope of this relationship declined significantly as environmental stochasticity increased. However, recent 1 in 25 yr extreme droughts were insufficient to extirpate populations with large carrying capacity. Consequently, large populations may be more resilient to environmental stochasticity than previously thought. The lack of carrying capacity-related asymptotes in persistence under extreme climate variability reveals how small populations affected by habitat loss or overharvesting, may be disproportionately threatened by increases in extreme climate events with global warming.

Drought survival is a threshold function of habitat size and population density in a fish metapopulation.

Because smaller habitats dry more frequently and severely during droughts, habitat size is likely a key driver of survival in populations during climate change and associated increased extreme drought frequency. Here, we show that survival in populations during droughts is a threshold function of habitat size driven by an interaction with population density in metapopulations of the forest pool dwelling fish, Neochanna apoda. A mark-recapture study involving 830 N. apoda individuals during a one-in-seventy-year extreme drought revealed that survival during droughts was high for populations occupying pools deeper than 139 mm, but declined steeply in shallower pools. This threshold was caused by an interaction between increasing population density and drought magnitude associated with decreasing habitat size, which acted synergistically to increase physiological stress and mortality. This confirmed two long-held hypotheses, firstly concerning the interactive role of population density and physiological stress, herein driven by habitat size, and secondly, the occurrence of drought survival thresholds. Our results demonstrate how survival in populations during droughts will depend strongly on habitat size and highlight that minimum habitat size thresholds will likely be required to maximize survival as the frequency and intensity of droughts are projected to increase as a result of global climate change.