Causal analysis of the temperature impact on deep-sea biodiversity

Vulnerability of Eastern Tropical Pacific chondrichthyan fish to climate change

Climate change is an environmental emergency threatening species and ecosystems globally. Oceans have absorbed about 90% of anthropogenic heat and 20%-30% of the carbon emissions, resulting in ocean warming, acidification, deoxygenation, changes in ocean stratification and nutrient availability, and more severe extreme events. Given predictions of further changes, there is a critical need to understand how marine species will be affected. Here, we used an integrated risk assessment framework to evaluate the vulnerability of 132 chondrichthyans in the Eastern Tropical Pacific (ETP) to the impacts of climate change. Taking a precautionary view, we found that almost a quarter (23%) of the ETP chondrichthyan species evaluated were highly vulnerable to climate change, and much of the rest (76%) were moderately vulnerable. Most of the highly vulnerable species are batoids (77%), and a large proportion (90%) are coastal or pelagic species that use coastal habitats as nurseries. Six species of batoids were highly vulnerable in all three components of the assessment (exposure, sensitivity and adaptive capacity). This assessment indicates that coastal species, particularly those relying on inshore nursery areas are the most vulnerable to climate change. Ocean warming, in combination with acidification and potential deoxygenation, will likely have widespread effects on ETP chondrichthyan species, but coastal species may also contend with changes in freshwater inputs, salinity, and sea level rise. This climate-related vulnerability is compounded by other anthropogenic factors, such as overfishing and habitat degradation already occurring in the region. Mitigating the impacts of climate change on ETP chondrichthyans involves a range of approaches that include addressing habitat degradation, sustainability of exploitation, and species-specific actions may be required for species at higher risk. The assessment also highlighted the need to further understand climate change's impacts on key ETP habitats and processes and identified knowledge gaps on ETP chondrichthyan species.

A framework for identifying factors controlling cyanobacterium Microcystis flos-aquae blooms by coupled CCM-ECCM Bayesian networks

Cyanobacterial blooms in freshwater sources are a global concern, and gaining insight into their causes is crucial for effective resource management and control. In this study, we present a novel computational framework for the causal analysis of cyanobacterial harmful algal blooms (cyanoHABs) in Lake Kinneret. Our framework integrates Convergent Cross Mapping (CCM) and Extended CCM (ECCM) causal networks with Bayesian Network (BN) models. The constructed CCM-ECCM causal networks and BN models unveil significant interactions among factors influencing cyanoHAB formation. These interactions have been validated by domain experts and supported by evidence from peer-reviewed publications. Our findings suggest that Microcystis flos-aquae levels are influenced not only by community structure but also by ammonium, phosphate, oxygen, and temperature levels in the weeks preceding bloom occurrences. We demonstrated a non-parametric computational framework for causal analysis of a multivariate ecosystem. Our framework offers a more comprehensive understanding of the underlying mechanisms driving M. flos-aquae blooms in Lake Kinneret. It captures complex interactions and provides an explainable prediction model. By considering causal relationships, temporal dynamics, and joint probabilities of environmental factors, the proposed framework enhances our understanding of cyanoHABs in Lake Kinneret.

Challenges and directions in analytical paleobiology

Over the last 50 years, access to new data and analytical tools has expanded the study of analytical paleobiology, contributing to innovative analyses of biodiversity dynamics over Earth's history. Despite-or even spurred by-this growing availability of resources, analytical paleobiology faces deep-rooted obstacles that stem from the need for more equitable access to data and best practices to guide analyses of the fossil record. Recent progress has been accelerated by a collective push toward more collaborative, interdisciplinary, and open science, especially by early-career researchers. Here, we survey four challenges facing analytical paleobiology from an early-career perspective: (1) accounting for biases when interpreting the fossil record; (2) integrating fossil and modern biodiversity data; (3) building data science skills; and (4) increasing data accessibility and equity. We discuss recent efforts to address each challenge, highlight persisting barriers, and identify tools that have advanced analytical work. Given the inherent linkages between these challenges, we encourage discourse across disciplines to find common solutions. We also affirm the need for systemic changes that reevaluate how we conduct and share paleobiological research.

Detecting and attributing the causes of biodiversity change: needs, gaps and solutions

This issue addresses the multifaceted problems of understanding biodiversity change to meet emerging international development and conservation goals, national economic accounting and diverse community needs. Recent international agreements highlight the need to establish monitoring and assessment programmes at national and regional levels. We identify an opportunity for the research community to develop the methods for robust detection and attribution of biodiversity change that will contribute to national assessments and guide conservation action. The 16 contributions of this issue address six major aspects of biodiversity assessment: connecting policy to science, establishing observation, improving statistical estimation, detecting change, attributing causes and projecting the future. These studies are led by experts in Indigenous studies, economics, ecology, conservation, statistics, and computer science, with representations from Asia, Africa, South America, North America and Europe. The results place biodiversity science in the context of policy needs and provide an updated roadmap for how to observe biodiversity change in a way that supports conservation action via robust detection and attribution science. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

Inferring a Causal Relationship between Environmental Factors and Respiratory Infections Using Convergent Cross-Mapping

The incidence of respiratory infections in the population is related to many factors, among which environmental factors such as air quality, temperature, and humidity have attracted much attention. In particular, air pollution has caused widespread discomfort and concern in developing countries. Although the correlation between respiratory infections and air pollution is well known, establishing causality between them remains elusive. In this study, by conducting theoretical analysis, we updated the procedure of performing the extended convergent cross-mapping (CCM, a method of causal inference) to infer the causality between periodic variables. Consistently, we validated this new procedure on the synthetic data generated by a mathematical model. For real data in Shaanxi province of China in the period of 1 January 2010 to 15 November 2016, we first confirmed that the refined method is applicable by investigating the periodicity of influenza-like illness cases, an air quality index, temperature, and humidity through wavelet analysis. We next illustrated that air quality (quantified by AQI), temperature, and humidity affect the daily influenza-like illness cases, and, in particular, the respiratory infection cases increased progressively with increased AQI with a time delay of 11 days.

Temperature and nutrients drive eco-phenotypic dynamics in a microbial food web

Anthropogenic increases in temperature and nutrient loads will likely impact food web structure and stability. Although their independent effects have been reasonably well studied, their joint effects-particularly on coupled ecological and phenotypic dynamics-remain poorly understood. Here we experimentally manipulated temperature and nutrient levels in microbial food webs and used time-series analysis to quantify the strength of reciprocal effects between ecological and phenotypic dynamics across trophic levels. We found that (1) joint-often interactive-effects of temperature and nutrients on ecological dynamics are more common at higher trophic levels, (2) temperature and nutrients interact to shift the relative strength of top-down versus bottom-up control, and (3) rapid phenotypic change mediates observed ecological responses to changes in temperature and nutrients. Our results uncover how feedback between ecological and phenotypic dynamics mediate food web responses to environmental change. This suggests important but previously unknown ways that temperature and nutrients might jointly control the rapid eco-phenotypic feedback that determine food web dynamics in a changing world.

Distribution and predicted climatic refugia for a reef-building cold-water coral on the southeast US margin

Climate change is reorganizing the planet's biodiversity, necessitating proactive management of species and habitats based on spatiotemporal predictions of distributions across climate scenarios. In marine settings, climatic changes will predominantly manifest via warming, ocean acidification, deoxygenation, and changes in hydrodynamics. Lophelia pertusa, the main reef-forming coral present throughout the deep Atlantic Ocean (>200 m), is particularly sensitive to such stressors with stark reductions in suitable habitat predicted to accrue by 2100 in a business-as-usual scenario. However, with new occurrence data for this species along with higher-resolution bathymetry and climate data, it may be possible to locate further climatic refugia. Here, we synthesize new and published biogeographic, geomorphological, and climatic data to build ensemble, multi-scale habitat suitability models for L. pertusa on the continental margin of the southeast United States (SEUS). We then project these models in two timepoints (2050, 2100) and four climate change scenarios to characterize the occurrence probability of this critical cold-water coral (CWC) habitat now and in the future. Our models reveal the extent of reef habitat in the SEUS and corroborate it as the largest currently known essentially continuous CWC reef province on earth, and also predict abundance of L. pertusa to identify key areas, including those outside areas currently protected from bottom-contact fishing. Drastic reductions in L. pertusa climatic suitability index emerged primarily after 2050 and were concentrated at the shallower end (<~550 m) of the regional distribution under the Gulf Stream main axis. Our results thus suggest a depth-driven climate refuge effect where deeper, cooler reef sites experience lesser declines. The strength of this effect increases with climate scenario severity. Taken together, our study has implications for the regional and global management of this species, portending changes in the biodiversity reliant on CWC habitats and the critical ecosystem services they provide.