Spatial and life history variation in a trait-based species vulnerability and impact model.

Anthropogenic pressures threaten biodiversity, necessitating conservation actions founded on robust ecological models. However, prevailing models inadequately capture the spatiotemporal variation in environmental pressures faced by species with high mobility or complex life histories, as data are often aggregated across species' life histories or spatial distributions. We highlight the limitations of static models for dynamic species and incorporate life history variation and spatial distributions for species and stressors into a trait-based vulnerability and impact model. We use green sea turtles in the Greater Caribbean Region to demonstrate how vulnerability and anthropogenic impact for a dynamic species change across four life stages. By incorporating life stages into a trait-based vulnerability model, we observed life stage-specific vulnerabilities that were otherwise unnoticed when using an aggregated trait value set. Early life stages were more vulnerable to some stressors, such as inorganic pollution or marine heat waves, and less vulnerable to others, such as bycatch. Incorporating spatial distributions of stressors and life stages revealed impacts differ for each life stage across spatial areas, emphasizing the importance of stage-specific conservation measures. Our approach showcases the importance of incorporating dynamic processes into ecological models and will enable better and more targeted conservation actions for species with complex life histories and high mobility.

At-risk marine biodiversity faces extensive, expanding, and intensifying human impacts.

Human activities and climate change threaten marine biodiversity worldwide, though sensitivity to these stressors varies considerably by species and taxonomic group. Mapping the spatial distribution of 14 anthropogenic stressors from 2003 to 2013 onto the ranges of 1271 at-risk marine species sensitive to them, we found that, on average, species faced potential impacts across 57% of their ranges, that this footprint expanded over time, and that the impacts intensified across 37% of their ranges. Although fishing activity dominated the footprint of impacts in national waters, climate stressors drove the expansion and intensification of impacts. Mitigating impacts on at-risk biodiversity is critical to supporting resilient marine ecosystems, and identifying the co-occurrence of impacts across multiple taxonomic groups highlights opportunities to amplify the benefits of conservation management.

Changes in ocean health in British Columbia from 2001 to 2016.

Effective management of marine systems requires quantitative tools that can assess the state of the marine social-ecological system and are responsive to management actions and pressures. We applied the Ocean Health Index (OHI) framework to retrospectively assess ocean health in British Columbia annually from 2001 to 2016 for eight goals that represent the values of British Columbia's coastal communities. We found overall ocean health improved over the study period, from 75 (out of 100) in 2001 to 83 in 2016, with scores for inhabited regions ranging from 68 (North Coast, 2002) to 87 (West Vancouver Island, 2011). Highest-scoring goals were Tourism & Recreation (average 94 over the period) and Habitat Services (100); lowest-scoring goals were Sense of Place (61) and Food Provision (64). Significant increases in scores over the time period occurred for Food Provision (+1.7 per year), Sense of Place (+1.4 per year), and Coastal Livelihoods (+0.6 per year), while Habitat Services (-0.01 per year) and Biodiversity (-0.09 per year) showed modest but statistically significant declines. From the results of our time-series analysis, we used the OHI framework to evaluate impacts of a range of management actions. Despite challenges in data availability, we found evidence for the ability of management to reduce pressures on several goals, suggesting the potential of OHI as a tool for assessing the effectiveness of marine resource management to improve ocean health. Our OHI assessment provides an important comprehensive evaluation of ocean health in British Columbia, and our open and transparent process highlights opportunities for improving accessibility of social and ecological data to inform future assessment and management of ocean health.

Our path to better science in less time using open data science tools.

Reproducibility has long been a tenet of science but has been challenging to achieve-we learned this the hard way when our old approaches proved inadequate to efficiently reproduce our own work. Here we describe how several free software tools have fundamentally upgraded our approach to collaborative research, making our entire workflow more transparent and streamlined. By describing specific tools and how we incrementally began using them for the Ocean Health Index project, we hope to encourage others in the scientific community to do the same-so we can all produce better science in less time.

Aligning marine species range data to better serve science and conservation.

Species distribution data provide the foundation for a wide range of ecological research studies and conservation management decisions. Two major efforts to provide marine species distributions at a global scale are the International Union for Conservation of Nature (IUCN), which provides expert-generated range maps that outline the complete extent of a species' distribution; and AquaMaps, which provides model-generated species distribution maps that predict areas occupied by the species. Together these databases represent 24,586 species (93.1% within AquaMaps, 16.4% within IUCN), with only 2,330 shared species. Differences in intent and methodology can result in very different predictions of species distributions, which bear important implications for scientists and decision makers who rely upon these datasets when conducting research or informing conservation policy and management actions. Comparing distributions for the small subset of species with maps in both datasets, we found that AquaMaps and IUCN range maps show strong agreement for many well-studied species, but our analysis highlights several key examples in which introduced errors drive differences in predicted species ranges. In particular, we find that IUCN maps greatly overpredict coral presence into unsuitably deep waters, and we show that some AquaMaps computer-generated default maps (only 5.7% of which have been reviewed by experts) can produce odd discontinuities at the extremes of a species' predicted range. We illustrate the scientific and management implications of these tradeoffs by repeating a global analysis of gaps in coverage of marine protected areas, and find significantly different results depending on how the two datasets are used. By highlighting tradeoffs between the two datasets, we hope to encourage increased collaboration between taxa experts and large scale species distribution modeling efforts to further improve these foundational datasets, helping to better inform science and policy recommendations around understanding, managing, and protecting marine biodiversity.