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# Data and code for Does increasing temperature accentuate disease impacts on fisheries species? A meta-analysis [https://doi.org/10.5061/dryad.4j0zpc8jx](https://doi.org/10.5061/dryad.4j0zpc8jx) Update November 12, 2024: Updated colors in TM1R plot*, updated plot labels in Salmoniformes*_figures plot, renamed files to be more reflective of figure descriptions in manuscript. Updated names of files at the end of the READ ME document. ## Description of the data and file structure The attached csv file is the compiled dataset used to perform the meta-analysis described in the manuscript. These data include columns not utilized in the text as these categorical variables were later simplified to increase sample size. These columns were retained in this dataset for transparency purposes. Sources for additional information outside of what was provided in the original studies are described in Appendix S2 and full citations are available in Appendix S4. The column descriptions are as follows: Study: In-text citation for the original manuscript where the mortality data were sourced (See Appendix S2 and S4) Group: the experiment associated with that row of mortality data (see Methods) Temp_C: the temperature at which the experiment was performed in degrees Celsius. Temp_Cent: mean-centered temperature in degrees Celsius. Days_in_study: the duration of the experiment in days. TrueLOR: the calculated log odds ratio from that experiment (see Methods) TrueLORVar: the calculated variance of the log odds ratios (see Methods) Inv_var: inverse of the TrueLORVar variance, used to weight Bayesian model (see Methods) Order: Order of the host species used Class: Class of the host species used Phylum: Phylum of the host species used Superfamily: Superfamily of the host species used Host_mobility: If adult host was mobile in the water column (See Appendix S1) Vertebrae: If adult host has a vertebrae (See Appendix S1) LH_clean: Life stage listed in source paper (See Appendix S1) Temp_zone: Host distribution (See Appendix S1) Salinity: Salinity tolerance of host (See Appendix S1), later simplified into Salinity_simple which was the variable used in the meta-analysis. Parasite_Type: Taxonomic group of Parasite used (See Appendix S1), later simplified into Parasite_Type_simple which was the variable used in the meta-analysis. Host_source: The local source of the experimental animals as described in the paper (See Appendix S1), later simplified into Host_source_simple which was the variable used in the meta-analysis. Motivation_code_2: The motivation of the researchers performing the original study (See Appendix S1). Salinity_simple: Simplified salinity tolerance (See Methods, Table 1, and Appendix S1). LH_simple: Life history of the hosts simplified (See Methods, Table 1, and Appendix S1). Parasite: The parasite used in the study (Appendix S2). Parasite_Type_simple: The simplified parasite taxonomy used in the study (See Methods, Table 1, and Appendix S1). Parasite_transmission3: The mode of transportation of the parasite (See Methods, Table 1, and Appendix S1). Pathogen_type: The life history strategy of the parasite (See Methods, Table 1, and Appendix S1). Parasite_location: If the parasite was an external or internal parasite (See Methods, Table 1, and Appendix S1). Parasite_Transmission_simple: Simplified parasite transmission into single or multiple transmission modes. Not used in the meta-analysis Host_source_simple: Simplified Host source (See Methods, Table 1, and Appendix S1). ## Sharing/Access information Data was derived from the sources listed in Appendix S3 and Appendix S4 in the manuscript. ## Code/Software Attached are R scripts to produce the statistical models and all figures in the manuscript. These were created using R version 4.3.1 (2023-06-16 ucrt) -- "Beagle Scouts" Copyright (C) 2023 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 (64-bit) Final_mods.R : Script with statistical models referenced in paper Host_taxonomony_mod_figure.R: Script that produces Figure 2 and model estimates listed in Table S1. TM1_R_figures2.R: Script to produce model output in Table S2 and Figure 3. Salmoniformes_figures.R: Script to produce model output in Table S3 and Figure 4. Funnel_plot: Script used to produce Figure S2. We compiled data from experimental studies on fisheries species that compared mortality of parasitized and unparasitized hosts at a static temperature. We defined fisheries species to include both invertebrate and vertebrate species that are harvested commercially or recreationally. In Fall 2019, we searched Web of Science following PRISMA protocols (O’Dea et al. 2021) using key terms that would return papers focused on harvested aquatic species, parasites, and diseases, but would exclude papers that were focused on human, environmental or domestic animal health (see Appendix S1 in Supporting Information). This search yielded 1,201 papers. We then screened the abstracts of these papers, and retained only papers that satisfied four criteria: 1) an experiment was performed that included at least one parasite exposure treatment paired with an unexposed control group, 2) temperatures were intended to be constant and not intentionally varied, 3) hosts were from species that constitute a fishery, including those in aquaculture, and 4) estimates of survival or mortality were reported for both infected and uninfected hosts at each temperature treatment. This selection process reduced the number of studies to 386 (Appendix S1 and Figure S1). We obtained full versions of 364 papers (22 papers from the original 386 were unobtainable). We then screened the full text of these papers to ensure a match to our four criteria, which reduced the 364 papers to 70. To increase statistical power to estimate the effect of host Order on parasite-induced mortality, we excluded experiments from hosts in Orders with fewer than three effect sizes. This reduced the number of papers included in our study from 70 to 56 and yielded a total of 287 effect sizes from 131 experiments (several papers included more than one experiment; Appendix S1 and S2, Figure S1). At least two people extracted data from each paper to reduce extraction error. If extracted values differed, the data were re-extracted until there was agreement between the two extractors. For data that were displayed in a graphical format only, we used WebPlotDigitizer (Rohatgi 2022) to extract data. Data (which may have been presented as mortality rates, or proportion surviving) were converted to numbers of host individuals that were dead and alive at the end of the experiment. We also extracted information about the paper itself, including the source of the hosts used in the paper and the motivation for conducting the experiment (see Appendix S1). Finally, we collected additional information about host and parasite traits from outside sources (e.g., other peer reviewed papers, government reports) when necessary to obtain moderator variables (Table 1, Appendix S1 and S2). The moderators (Table 1) were used to test a priori hypotheses regarding how host, parasite, and study design traits influenced how temperature affected parasite-induced mortality. Because our focus was on parasite-induced mortality, we used log odds ratios and the variance surrouding log odds ratio as our effect size to compare host survival in the parasitized vs unparasitized treatments. Rapid warming could drastically alter host-parasite relationships, which is especially important for fisheries crucial to human nutrition and economic livelihoods; yet we lack a synthetic understanding of how warming influences parasite-induced mortality in these systems. We conducted a meta-analysis using 287 effect sizes from 56 empirical papers on harvested aquatic species and determined the relationship between parasite-induced host mortality and temperature and how this relationship was altered by host, parasite and study design traits. Overall, temperature increased parasite-induced host mortality; however, the magnitude and sometimes direction of this relationship varied. Hosts from the order Salmoniformes experienced a greater increase in parasite-induced mortality with temperature than average. Opportunistic parasites were correlated with a greater increase in host mortality with temperature than average, while bacterial parasite-induced mortality was lower than average as temperature increased. Thus, parasites will generally increase host mortality as the environment warms; however, this effect will vary among systems.

Asynchronous fluctuations in abundance between species with similar ecological roles can stabilize food webs and support coexistence. Sardine ( Sardinops spp.) and anchovy ( Engraulis spp.) have long been used as an example of this pattern because low-frequency variation in catches of these species appears to occur out of phase, suggesting that fisheries and generalist predators could be buffered against shifts in productivity of a single species. Using landings data and biomass and recruitment estimates from five regions, we find that species do not have equivalent peak abundances, suggesting that high abundance in one species does not compensate for low abundance in the other. We find that globally there is a stronger pattern of asynchrony in landings compared to biomass, such that landings data have exaggerated the patterns of asynchrony. Finally, we show that power to detect decadal asynchrony is poor, requiring a time series more than twice the length of the period of fluctuation. These results indicate that it is unlikely that the dynamics of these two species are compensatory enough to buffer fisheries and predators from changes in abundance, and that the measurements of asynchrony have largely been a statistical artefact of using short time series and landings data to infer ecology.

Animals make behavioural and reproductive decisions that maximise their lifetime reproductive success, and thus their fitness, in light of periodic and stochastic variability of the environment. Modelling the variation of an individual's energy levels formalises this tradeoff and helps to quantify the population‐level consequences of stressors (e.g. disturbance from human activities and environmental change) that can affect behaviour or physiology. In this study, we develop a dynamic state variable model for the spatially explicit behaviour, physiology and reproduction of a female, long‐lived, migratory marine vertebrate. The model can be used to investigate the spatio‐temporal patterns of behaviour and reproduction that allow an individual to maximise its overall reproductive output. We parametrised the model for eastern North Pacific blue whalesBalaenoptera musculus, and used it to predict the effects of changing environmental conditions and increasing human disturbance on the population's vital rates. In baseline conditions, the model output had high fidelity to observed energy dynamics, movement patterns and reproductive strategies. Simulated scenarios suggested that environmental changes could have severe consequences on the population's vital rates, but that individuals could tolerate high levels of anthropogenic disturbance. However, this ability depended on where, when and how often disturbance occurred. In scenarios with both environmental change and anthropogenic disturbance, synergistic interactions caused stronger effects than in isolation. In general, larger body size offered a buffer against stochasticity and disturbance, and, consequently, we predicted juveniles to be more susceptible to disturbance. We also predicted that females prioritise their own survival at the expense of the current reproductive attempt, presumably the result of their long lifespan. Our approach provides a general framework to make predictions of the cumulative and synergistic effects of human disturbance and climate change on migratory populations, which can inform effective management and conservation efforts.

Abstract. Human activities are drastically altering water and material flows in river systems across Asia. These anthropogenic perturbations have rarely been linked to the carbon (C) fluxes of Asian rivers that may account for up to 40–50 % of the global fluxes. The primary object of this review was to provide a conceptual framework for assessing human impacts on Asian river C fluxes, along with a latest update on anthropogenic alterations of riverine C fluxes, focusing on the impacts of water pollution and river impoundments on CO2 outgassing from the rivers draining South, Southeast, and East Asian regions that account for the largest fraction of river discharge and C exports from Asia and Oceania. Recent booms in dam construction across Asia have created a host of environmental problems; yet only a small number of studies have explicitly investigated altered rates of greenhouse gas (GHG) emissions and organic C transport. There have been contrasting reports on impoundment effects: decreases in GHG emissions in the reservoirs exhibiting enhanced primary production vs. increased emissions from the flooded vegetation and soils in the early years following dam construction or from the impounded river reaches and downstream estuaries during the monsoon period. These contrasting results suggest that the rates of metabolic processes in the impounded and downstream reaches can greatly vary longitudinally over time, as a combined result of diel shifts in the balance between autotrophy and heterotrophy, seasonal fluctuations between the dry and monsoon periods, and a long-term change from a leaky post-construction phase to a gradual C sink. Rapid pace of urbanization across southern and eastern Asian regions has dramatically increased municipal water withdrawal, generating annually 120.2 km3 of wastewater in 24 countries, which comprises 38.6 % of the global municipal wastewater production (311.6 km3). Although the municipal wastewater constitutes only 0.9 % of the renewable surface water, it can disproportionately affect the receiving river water, particularly downstream of rapidly expanding metropolitan areas, including eutrophication, increases in the amount and lability of organic C, and pulse emissions of CO2 and other greenhouse gases (GHGs). As reviewed for three representative rivers (the Ganges, Mekong, and Yellow River), the lower reaches of these rivers and their polluted tributaries tend to exhibit higher levels of organic C and the partial pressure of CO2 (pCO2) than the eutrophic reservoirs and less impacted upstream reaches. More field measurements of pCO2, together with accurate flux calculations based on river-specific model parameters, are urgently required to provide more accurate estimates of GHG emissions from the Asian rivers that are now underrepresented in the global C budgets. Researchers working on individual river systems need to be linked to collaborative research networks to facilitate global synthesis of local field data. These synthesis efforts, combined with conceptual and mathematical models, will contribute to a better understanding of how anthropogenic perturbations in rapidly urbanizing watersheds across Asia and other continents enhance discontinuities in riverine metabolic processes and C fluxes and hence transform the natural river assumed in the long-standing river continuum model to an anthropogenic system.

Climate change impacts on vertebrates have consequences for marine ecosystem structures and services. We review marine fish, mammal, turtle, and seabird responses to climate change and discuss their potential for adaptation. Direct and indirect responses are demonstrated from every ocean. Because of variation in research foci, observed responses differ among taxonomic groups (redistributions for fish, phenology for seabirds). Mechanisms of change are (i) direct physiological responses and (ii) climate-mediated predator-prey interactions. Regional-scale variation in climate-demographic functions makes range-wide population dynamics challenging to predict. The nexus of metabolism relative to ecosystem productivity and food webs appears key to predicting future effects on marine vertebrates. Integration of climate, oceanographic, ecosystem, and population models that incorporate evolutionary processes is needed to prioritize the climate-related conservation needs for these species.

Barotropic (surface) and baroclinic (internal) tides were measured at four mooring sites during a field investigation of acoustic propagation characteristics and physical oceanography in the northern South China Sea. The mooring positions were in a line moving up the shallow portion of a continental slope at water depths between 350 and 85 m. Using time series of temperature and velocity, at several depths, 1‐month series of semidiurnal and diurnal species internal tidal energy flux vectors were computed for three sites, with a 14‐day series computed for the fourth (shallow) site. The internal tides had a temporal signature that was not in complete accord with the barotropic tides, showing an enhancement of diurnal internal tides with respect to semidiurnal. Bathymetric slope, barotropic tidal fluid particle trajectories, and scale of generation site versus internal tide wavelength are investigated as possible causes of the differing response of the species.

Picoeukaryotes are a taxonomically diverse group of organisms less than 2 micrometers in diameter. Photosynthetic marine picoeukaryotes in the genus Micromonas thrive in ecosystems ranging from tropical to polar and could serve as sentinel organisms for biogeochemical fluxes of modern oceans during climate change. These broadly distributed primary producers belong to an anciently diverged sister clade to land plants. Although Micromonas isolates have high 18 S ribosomal RNA gene identity, we found that genomes from two isolates shared only 90% of their predicted genes. Their independent evolutionary paths were emphasized by distinct riboswitch arrangements as well as the discovery of intronic repeat elements in one isolate, and in metagenomic data, but not in other genomes. Divergence appears to have been facilitated by selection and acquisition processes that actively shape the repertoire of genes that are mutually exclusive between the two isolates differently than the core genes. Analyses of the Micromonas genomes offer valuable insights into ecological differentiation and the dynamic nature of early plant evolution.