Implications for the conservation of deep-water corals in the face of multiple stressors: A case study from the New Zealand region.

The waters around New Zealand are a global hotspot of biodiversity for deep-water corals; approximately one sixth of the known deep-water coral species of the world have been recorded in the region. Deep-water corals are vulnerable to climate-related stressors and from the damaging effects of commercial fisheries. Current protection measures do not account for the vulnerability of deep-water corals to future climatic conditions, which are predicted to alter the distribution of suitable habitat for them. Using recently developed habitat suitability models for 12 taxa of deep-water corals fitted to current and future seafloor environmental conditions (under different future climatic conditions: SSP2 - 4.5 and SSP3 - 7.0) we explore possible levels of spatial protection using the decision-support tool Zonation. Specifically, we assess the impact of bottom trawling on predictions of current distributions of deep-water corals, and then assess the effectiveness of possible protection for deep-water corals, while accounting for habitat refugia under future climatic conditions. The cumulative impact of bottom trawling was predicted to impact all taxa, but particularly the reef-forming corals. Core areas of suitable habitat were predicted to decrease under future climatic conditions for many taxa. We found that designing protection using current day predictions alone, having accounted for the impacts of historic fishing impacts, was unlikely to provide adequate conservation for deep water-corals under future climate change. Accounting for future distributions in spatial planning identified areas which may provide climate refugia whilst still providing efficient protection for current distributions. These gains in conservation value may be particularly important given the predicted reduction in suitable habitat for deep-water corals due to bottom fishing and climate change. Finally, the possible impact that protection measures may have on deep-water fisheries was assessed using a measure of current fishing value (kg km-2 fish) and future fishing value (predicted under future climate change scenarios).

Predator density and timing of arrival affect reef fish community assembly.

Most empirical studies of predation use simple experimental approaches to quantify the effects of predators on prey (e.g., using constant densities of predators, such as ambient vs. zero). However, predator densities vary in time, and these effects may not be well represented by studies that use constant predator densities. Although studies have independently examined the importance of predator density, temporal variability, and timing of arrival (i.e., early or late relative to prey), the relative contribution of these different predator regimes on prey abundance, diversity, and composition remains poorly understood. The hawkfish (Paracirrhites arcatus), a carnivorous coral reef fish, exhibits substantial variability in patch occupancy, density, and timing of arrival to natural reefs. Our field experiments demonstrated that effects of hawkfish on prey abundance depended on both hawkfish density and the timing of their arrival, but not on variability in hawkfish density. Relative to treatments without hawkfish, hawkfish presence reduced prey abundance by 50%. This effect increased with a doubling of hawkfish density (an additional 33% reduction), and when hawkfish arrived later during community development (a 34% reduction). Hawkfish did not affect within-patch diversity (species richness), but they increased between-patch diversity (beta) based on species incidence (22%), and caused shifts in species composition. Our results suggest that the timing of predator arrival can be as important as predator density in modifying prey abundance and community composition.

Order of arrival affects competition in two reef fishes.

Many communities experience repeated periods of colonization due to seasonally regenerating habitats or pulsed arrival of young-of-year. When an individual's persistence in a community depends upon the strength of competitive interactions, changes in the timing of arrival relative to the arrival of a competitor can modify competitive strength and, ultimately, establishment in the community. We investigated whether the strength of intracohort competitive interactions between recent settlers of the reef fishes Thalassoma hardwicke and T. quinquevittatum are dependent on the sequence and temporal separation of their arrival into communities. To achieve this, we manipulated the sequence and timing of arrival of each species onto experimental patch reefs by simulating settlement pulses and monitoring survival and aggressive interactions. Both species survived best in the absence of competitors, but when competitors were present, they did best when they arrived at the same time. Survival declined as each species entered the community progressively later than its competitor and as aggression by its competitor increased. Intraspecific effects of resident T. hardwicke were similar to interspecific effects. This study shows that the strength of competition depends not only on the identity of competitors, but also on the sequence and timing of their interactions, suggesting that when examining interaction strengths, it is important to identify temporal variability in the direction and magnitude of their effects. Furthermore, our findings provide empirical evidence for the importance of competitive lotteries in the maintenance of species diversity in demographically open marine systems.

Generalized linear mixed models: a practical guide for ecology and evolution.

How should ecologists and evolutionary biologists analyze nonnormal data that involve random effects? Nonnormal data such as counts or proportions often defy classical statistical procedures. Generalized linear mixed models (GLMMs) provide a more flexible approach for analyzing nonnormal data when random effects are present. The explosion of research on GLMMs in the last decade has generated considerable uncertainty for practitioners in ecology and evolution. Despite the availability of accurate techniques for estimating GLMM parameters in simple cases, complex GLMMs are challenging to fit and statistical inference such as hypothesis testing remains difficult. We review the use (and misuse) of GLMMs in ecology and evolution, discuss estimation and inference and summarize 'best-practice' data analysis procedures for scientists facing this challenge.