Incorporating physiological knowledge into correlative species distribution models minimizes bias introduced by the choice of calibration area.

Correlative species distribution models (SDMs) are important tools to estimate species' geographic distribution across space and time, but their reliability heavily relies on the availability and quality of occurrence data. Estimations can be biased when occurrences do not fully represent the environmental requirement of a species. We tested to what extent species' physiological knowledge might influence SDM estimations. Focusing on the Japanese sea cucumber Apostichopus japonicus within the coastal ocean of East Asia, we compiled a comprehensive dataset of occurrence records. We then explored the importance of incorporating physiological knowledge into SDMs by calibrating two types of correlative SDMs: a naïve model that solely depends on environmental correlates, and a physiologically informed model that further incorporates physiological information as priors. We further tested the models' sensitivity to calibration area choices by fitting them with different buffered areas around known presences. Compared with naïve models, the physiologically informed models successfully captured the negative influence of high temperature on A. japonicus and were less sensitive to the choice of calibration area. The naïve models resulted in more optimistic prediction of the changes of potential distributions under climate change (i.e., larger range expansion and less contraction) than the physiologically informed models. Our findings highlight benefits from incorporating physiological information into correlative SDMs, namely mitigating the uncertainties associated with the choice of calibration area. Given these promising features, we encourage future SDM studies to consider species physiological information where available. Supplementary Information: The online version contains supplementary material available at 10.1007/s42995-024-00226-0.

Effect of trade on global aquatic food consumption patterns.

Globalization of fishery products is playing a significant role in shaping the harvesting and use of aquatic foods, but a vigorous debate has focused on whether the trade is a driver of the inequitable distribution of aquatic foods. Here, we develop species-level mass balance and trophic level identification datasets for 174 countries and territories to analyze global aquatic food consumption patterns, trade characteristics, and impacts from 1976 to 2019. We find that per capita consumption of aquatic foods has increased significantly at the global scale, but the human aquatic food trophic level (HATL), i.e., the average trophic level of aquatic food items in the human diet, is declining (from 3.42 to 3.18) because of the considerable increase in low-trophic level aquaculture species output relative to that of capture fisheries since 1976. Moreover, our study finds that trade has contributed to increasing the availability and trophic level of aquatic foods in >60% of the world's countries. Trade has also reduced geographic differences in the HATL among countries over recent decades. We suggest that there are important opportunities to widen the current focus on productivity gains and economic outputs to a more equitable global distribution of aquatic foods.

Risk from future climate change to Pakistan's protected area network: A composite analysis for hotspot identification.

As climate change becomes a primary driver of global ecosystem deterioration and biodiversity loss, protected areas (PAs) are posed to play a crucial conservation role. At a global scale, 17 % of land is currently covered by PAs; a figure expected to reach 30 % by 2030 under the UN post-2020 global biodiversity framework. However, focusing only on the percent coverage of PAs without assessing their efficacy may not accomplish the intended conservation goals. Here, we present the first assessment of the risk from climate change to existing PAs and non-protected lands across Pakistan by combining data on the local exposure and vulnerability of 409 species of birds, mammals, reptiles and amphibians to multidimensional changes in climate by mid (2040-2060) and late (2061-2080) century under two climate emission scenarios (RCP4.5 and RCP8.5). We find that between 7 % (2050 RCP4.5) and 19 % (2080 RCP8.5) of the current network of PAs, mostly located in the eastern and southeastern parts of the country, are projected to be under future extreme risk (i.e., highly exposed areas containing highly vulnerable communities). Importantly, hotspots of risk within these PAs are projected to significantly expand over time and with increasing severity of the scenario. In contrast, PAs in the northern part of the country are projected to remain under moderate to low risk. Results are subject to variability across the country reflecting interesting differences in climate change exposure and species vulnerability between protected and non-protected lands. Importantly, significantly lower level of risks from future climate change are projected for PAs than non-protected lands across emission scenarios and periods suggesting potential candidate areas for the future expansion of the country's PA network. Our analysis provides novel insights that can help inform conservation decisions and management at a time when the country is investing in ambitious efforts to expand its network of protected areas.