Global scale forecasts of range shifts in response to global warming have provided vital insight into predicted species redistribution. We build on that insight by examining whether local warming will affect habitat on spatiotemporal scales relevant to regional agencies. We used generalized additive models to quantify the realized habitat of 46 temperate/boreal marine species using 41+ years of survey data from 35°N–48°N in the Northwest Atlantic. We then estimated change in a “realized thermal habitat index” under short-term (2030) and long-term (2060) warming scenarios. Under the 2030 scenario, ∼10% of species will lose realized thermal habitat at the national scale (USA and Canada) but planktivores are expected to lose significantly in both countries which may result in indirect changes in their predators’ distribution. In contrast, by 2060 in Canada, the realized habitat of 76% of species will change (55% will lose, 21% will gain) while in the USA, the realized habitat of 85% of species will change (65% will lose, 20% will gain). If all else were held constant, the ecosystem is projected to change radically based on thermal habitat alone. The magnitude of the 2060 warming projection (∼1.5–3°C) was observed in 2012 affirming that research is needed on effects of extreme “weather” in addition to increasing mean temperature. Our approach can be used to aggregate at smaller spatial scales where temperate/boreal species are hypothesized to have a greater loss at ∼40°N. The uncertainty associated with climate change forecasts is large, yet resource management agencies still have to address climate change. How? Since many fishery agencies do not plan beyond 5 years, a logical way forward is to incorporate a “realized thermal habitat index” into the stock assessment process. Over time, decisions would be influenced by the amount of suitable thermal habitat, in concert with gradual or extreme warming.
Resource managers need climate adaptation tools. We build on a popular tool, the climate change vulnerability assessment (CCVA), to identify vulnerable marine species. Only warming was considered, as warming is expected to have earlier impacts in the offshore than other climate drivers, and projections of other climate drivers are not well developed. For this reason, we coin our generalized, semi-quantitative method the “Vulnerability to Projected Warming Assessment” (VPWA) as opposed to using the broader term, CCVA. We refine the typical “exposure” component to be a function of gain/loss of thermal habitat at multiple life stages. We also build on the traditional logic approach of CCVAs. We produce scores for each species, and use a null distribution through Monte Carlo simulations to identify the most vulnerable species. We evaluate the vulnerability of 33 fish and invertebrate species, on the scale of the Scotian Shelf, Canada, to two warming scenarios, mild and severe, based on regional trends and projections. At smaller spatial scales, we evaluate populations of a subset of these species. Populations in the southwest portion of the domain are found to be more vulnerable than those in the northeast. Overall, our results indicate that 45% of populations may be vulnerable under a severe (+3°C) warming scenario, including currently endangered, threatened, and commercial populations (e.g. southwestern Atlantic cod, Smooth skate, Snow crab), while only one species has a relatively high vulnerability score under the mild (+0.7°C) scenario (Moustache sculpin). Populations triaged by relative vulnerability to regional warming should help managers prioritize resources and identify knowledge gaps. For this reason, and for its biological and ecological underpinnings, our method has broad relevance within the marine science and management field. As more information become available, our VPWA can be used as a stepping-stone in the continued development of CCVA methods.
We have learned much about the impacts of warming on the productivity and distribution of marine organisms, but less about the impact of warming combined with other environmental stressors, including oxygen depletion. Also, the combined impact of multiple environmental stressors requires evaluation at the scales most relevant to resource managers. We use the Gulf of St. Lawrence, Canada, characterized by a large permanently hypoxic zone, as a case study. Species distribution models were used to predict the impact of multiple scenarios of warming and oxygen depletion on the local density of three commercially and ecologically important species. Substantial changes are projected within 20-40 years. A eurythermal depleted species already limited to shallow, oxygen-rich refuge habitat (Atlantic cod) may be relatively uninfluenced by oxygen depletion but increase in density within refuge areas with warming. A more stenothermal, deep-dwelling species (Greenland halibut) is projected to lose ~55% of its high-density areas under the combined impacts of warming and oxygen depletion. Another deep-dwelling, more eurythermal species (Northern shrimp) would lose ~4% of its high-density areas due to oxygen depletion alone, but these impacts may be buffered by warming, which may increase density by 8% in less hypoxic areas, but decrease density by ~20% in the warmest parts of the region. Due to local climate variability and extreme events, and that our models cannot project changes in species sensitivity to hypoxia with warming, our results should be considered conservative. We present an approach to effectively evaluate the individual and cumulative impacts of multiple environmental stressors on a species-by-species basis at the scales most relevant to managers. Our study may provide a basis for work in other low-oxygen regions and should contribute to a growing literature base in climate science, which will continue to be of support for resource managers as climate change accelerates.
gration rate increases with island area and decreases with isolation, while extinction rate decreases with island area and increases with isolation. It is becoming increasingly recognized that these rates, and subsequently the parameters of the SAR, vary with species interactions, such as predator−prey interactions, and species traits (body size, diet generality, and trophic group;
a b s t r a c tMarine Protected Areas (MPAs) are proposed to help conserve marine biodiversity and ecological integrity. There is much guidance on the optimal design of MPAs but once potential MPAs are identified there is little guidance on defining the final no-take boundaries. This is especially problematic in temperate zones where ecological boundaries are "fuzzy", which can be quite complicated during a consultation process involving the government and divergent stakeholder groups. More decision-support tools are needed to help stakeholders and government agencies objectively compare conservation and socio-economic trade-offs among proposed boundary options. To that end, we developed a method to identify which boundary minimizes spatial overlap of highly vulnerable species and a dominant stressor. We used the recently proposed boundary options of a candidate MPA in Atlantic Canada to illustrate our method. We evaluated the vulnerability of 23 key species to bottom trawling, the most prevalent stressor in the area. We then compared the spatial overlap of the most vulnerable species and the 2002-2011 footprint of bottom trawling among boundary options. The best boundary option was identified as that which minimized spatial overlap and total area. This approach identifies boundary options which provide the greatest protection of vulnerable species from their most significant stressor, at limited socio-economic cost. It is an objective decision-support tool to help stakeholders agree on final boundaries for MPAs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.