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The spatiotemporal relationship between geophysical, environmental, and geochemical responses during volcanic unrest is essentially unknown, making their joint use and interpretation for eruption forecasting challenging. Here, Empirical Orthogonal Functions analysis applied to GPS data allows the separation of the dominant deep‐sourced inflation from environmentally controlled signals associated with extension at Campi Flegrei caldera. This separation bridges the gap between deformation, seismic and geochemical responses, clarifying the processes underlying the ongoing volcanic unrest. Persistent meteoric forcing during the 2017–2018 hydrological year changed the decadal trend of seismic energy and secondary deformation components, pairing their spatial patterns. The result was a block in the carbon dioxide released in 2018 at Solfatara, the primary stress‐release valve at the caldera. The subsequent overpressure weakened the fractured eastern caldera, opening pathways for deep, hot materials to reach the surface. Our results give insight into how environmental forcing can favor volcanic unrest in pressurized calderas. Plain Language Summary Geophysics and geochemistry are two of the most essential disciplines to understand volcanic unrest and eruptions. Finding the link between deformation signals and their seismic and geochemical counterparts is crucial in understanding how a volcano works; however, a time‐resolved 3D analysis of signals sensitive to different processes, from magma migration to environmental forcing, is our best chance to understand how the volcano changes and when an eruption might occur. We borrowed standard oceanic and climatic data analysis techniques and applied them to GPS signals recorded during unrest at Campi Flegrei caldera. The results uncovered small deformation components linked to seismic migrations and variations in carbon dioxide fluxes measured at the Solfatara crater. These components clarify how a drought can weaken the shallowest crust, strengthening ongoing processes generated at depth. A wet hydrological year in the middle of the ongoing drought coincided with decreased emissions of carbon‐bearing fluids from Solfatara, the primary stress‐release valve of the caldera. This stress was eventually released when deep materials rose in the eastern caldera, producing seismicity. Highlighting small components in deformation signals linked to environmental changes appears essential to mark variations in volcanic behavior, in analogy to what is done by ambient noise interferometry. Key Points Advanced deformation analysis detects environmental components linked to seismic migrations and variations in carbon dioxide fluxes A wet hydrological year during a drought closed Solfatara, increasing pressure and breaking the shallow caldera in early 2018 The deep unrest sources cracked the weakened eastern caldera in 2018–2019, causing seismic unrest

Fisheries and natural water resources across the world are under increasing pressure from human activity, including fishing and irrigated agriculture. There is an urgent need for information on the climatic/hydrologic drivers of fishery productivity that can be readily applied to management. We use a generalized linear mixed model framework of catch curve regression to resolve the key climatic/hydrological drivers of recruitment in Barramundi Lates calcarifer using biochronological (otolith aging) data collected from four river-estuary systems in the Northern Territory, Australia. These models were then used to generate estimates of the year class strength (YCS) outcomes of different water abstraction scenarios (ranging from 10% to 40% abstraction per season/annum) for two of the rivers in low, moderate, and high discharge years. Barramundi YCS displayed strong interannual variation and was positively correlated with regional monsoon activity in all four rivers. River-specific analyses identified strong relationships between YCS and several river-specific hydrology variables, including wet and dry season discharge and flow duration. Water abstraction scenario models based on YCS–hydrology relationships predicted reductions of >30% in YCS in several cases, suggesting that increased water resource development in the future may pose risks for Barramundi recruitment and fishery productivity. Our study demonstrates the importance of the tropical monsoon as a driver of Barramundi recruitment and the potential for detrimental impacts of increased water abstraction on fishery productivity. The biochronological and statistical approaches we used have the potential to be broadly applied to inform policy and management of water resource and fisheries.

Phytoplankton community composition was characterized over varying seasonal and river discharge conditions during 5 research cruises across the continental margin of the northern Gulf of Mexico (NGOM). The spatial and temporal patterns of variation in the composition of the algal community were examined using high performance liquid chromatography (HPLC) analyses of phytoplankton pigments in conjunction with classification using the CHEMTAX software (v.1.95). Cluster analysis and principal component analysis were used to identify different regimes and to understand the relationship of the phytoplankton community to biological and environmental variables. The large river dominated margin of the NGOM was characterized by (1) an estuarine and inner shelf regime dominated by diatoms, cryptophytes, cyanobacteria, and chlorophytes; (2) midshelf waters, a transition zone between coastal river-influenced and oligotrophic slope waters, associated with a mixed phytoplankton composition; and (3) a slope water regime typical of oligotrophic ocean conditions with a surface community dominated by cyanobacteria, haptophytes, and prochlorophytes. A chlorophyll fluorescence maximum (CFM) was a regular feature at offshore stations and showed significant differences from that of surface waters in seasonal variability of phytoplankton pigment ratios and community composition. Our findings support the view that large river outflows, along with other environmental variables such as wind forcing and stratification, have a profound influence on phytoplankton communities over a large regional extent in the continental margin waters of the NGOM.

Wavelet analysis is a powerful tool that is already in use throughout science and engineering. The versatility and attractiveness of the wavelet approach lie in its decomposition properties, principally its time-scale localization. It is especially relevant to the analysis of non-stationary systems, i.e., systems with short-lived transient components, like those observed in ecological systems. Here, we review the basic properties of the wavelet approach for time-series analysis from an ecological perspective. Wavelet decomposition offers several advantages that are discussed in this paper and illustrated by appropriate synthetic and ecological examples. Wavelet analysis is notably free from the assumption of stationarity that makes most methods unsuitable for many ecological time series. Wavelet analysis also permits analysis of the relationships between two signals, and it is especially appropriate for following gradual change in forcing by exogenous variables.

A conspicuous season–diversity relationship (SDR) can be seen in seasonal environments, often with a defined peak in active species diversity in the growing season. We ask is this a general pattern and are other patterns possible? In addition, we ask what is the ultimate cause of this pattern and can we understand it using existing ecological theory? To accomplish this task, we assembled a global database on changes in species diversity through time in seasonal environments for different taxa and habitats and also conducted a modeling study in an attempt to replicate observed patterns. Our global database includes terrestrial and aquatic habitats, temperate, tropical, and polar environments, and taxa from disparate groups including vertebrates, insects, and plankton. We constructed nine alternative models that vary in assumptions on type of seasonal forcing, responses to that forcing, species niches, and types of species interactions. We found that most guilds of species exhibit a repeatable SDR across years. For north temperate ecosystems, active species diversity generally peaks mid‐year. The peak for a guild is generally more pronounced in terrestrial habitats than aquatic habitats and more pronounced in temperate and polar regions than the tropics. We now have evidence that at least several different habitat and taxa types are likely to have multiple peaks in diversity in a year, for example, guilds of both aquatic microbes and desert vertebrates can show a bimodal or multimodal SDR. We compared all nine candidate models in their ability to explain the patterns and match their assumptions to the data. Some performed considerably better than others in being able to match the different patterns. We conclude that a model that includes both temperature niches and environmental feedbacks is necessary to explain the different SDRs. We use such a model to make predictions about how the SDR could be impacted by climate change. More effort should be put into documenting and understanding baseline seasonal patterns in diversity in order to predict future responses to global change.

Using MODIS-Aqua satellite observations, this study analyzes the spatiotemporal distribution characteristics of particulate organic carbon (POC) in China’s marginal seas from 2003 to 2024. The statistical relationships between various marine environmental variables, including sea surface temperature (SST), nutrients, and primary production (PP), and POC concentrations are explored using partial least squares path modeling (PLS-PM). Finally, a box model approach is conducted to assess the POC budget in the study area. The results indicate that the POC concentration in the marginal seas of China generally exhibits a characteristic of being high in spring and low in summer. The highest concentration of POC is observed in the Bohai Sea, followed by the Yellow Sea, and the lowest in the East China Sea, with coastal waters exhibiting higher POC concentrations compared to the central areas. The spatial distribution and seasonal changes in POC are jointly influenced by PP, water mass exchange, resuspended sediments, and terrestrial inputs. Large-scale climate modes show statistical associations with POC concentration in the open waters of China’s marginal seas. PP and respiratory consumption are identified as the predominant input and output fluxes, respectively, in China’s marginal seas. This study enriches the understanding of carbon cycling processes and carbon sink mechanisms in marginal seas.

Microorganisms are able to colonise abiotic surfaces in marine waters, supporting ecological and biogeochemical functions. In turn, environmental factors may determine the accrual and activity of microbial biofilms. The environment is subject to global climate change and pollution by plastic, and therefore we focused on the response of natural marine biofilm on common plastic items (bottles) to seasonality, increases in temperature, and light regime in experimental systems. Chlorophyll-a, prokaryotic abundance and replication frequency, organic matter (OM), and enzymatic activity were measured. Statistical analysis indicated that different environmental conditions modified the biofilms. Summer conditions favoured photoautotrophic organisms. The increase of photoautotrophic biomass could have caused the prokaryotic microorganisms’ lowest abundances. Temperature rise affected chlorophyll-a and increased hydrolytic activities, responsible for OM degradation, as also recorded in the absence of light. In winter, temperature variation led to a delayed increase of enzymatic activity, suggesting the need for a time lag to potentiate OM recycling. The correlations between prokaryotic abundance and the other variables highlighted tighter links in cases of temperature alteration. Our results indicated that a potential temperature increase, and light limitation due to plastic sinking in the water column, could modify the biofilm community, increasing the role of prokaryotic organisms.

Aim The temporal structure (colour) of environmental variation influences population fluctuations, extinction risk and community stability. However, it is unclear whether environmental covariates linked to population fluctuations are distinguishable from a purely random process (white noise). We aimed to estimate colour coefficients and relative support for three models commonly representing coloured stochastic processes, in environmental series linked to terrestrial animal population fluctuations. Location North America and Eurasia. Time period 1901–2002. Major taxa studied Birds, insects and mammals. Methods We analysed multiple abiotic environmental covariates, comparing point estimates and confidence intervals of temporal structure in competing models fitted using white noise, autoregressive [AR(1)] and 1/f processes in the time domain and the frequency domain (where time series were analysed after decomposition into different sinusoidal frequencies and their relative powers). All animal time series were sampled annually for ≤ 50 years, potentially inflating type II errors. We also considered 101‐year series of matched environmental covariates, performing a statistical power analysis evaluating our ability to draw robust conclusions. Results Temperature‐related variables were associated with the largest fraction of population fluctuations. Ninety‐three per cent of shorter environmental series were indistinguishable from white noise, limited by time‐series length and associated with wide confidence intervals. The longer environmental series analysed in the time domain offered sufficiently high statistical power to identify correctly colour estimates ≥ |0.27|, indicating that 20% of series were best described by a slightly reddened noise process. Main conclusions Focusing on the short time‐scales typically available for ecologists, most environmental variables associated with terrestrial animal population fluctuations are best characterized by white noise processes, although type II errors are common. The correct detection of intermediately coloured noise with power 0.8 requires ≥ 16 data points in the time domain or ≥ 47 points in the frequency domain. Over longer time‐scales, where type II errors are less likely, one‐fifth of populations are associated with coloured (often reddened) variables.

Understanding what factors drive fluctuations in the abundance of endangered species is a difficult ecological problem but a major requirement to attain effective management and conservation success. The ecological traits of large mammals make this task even more complicated, calling for integrative approaches. We develop a framework combining individual-based modelling and statistical inference to assess alternative hypotheses on brown bear dynamics in the Cantabrian range (Iberian Peninsula). Models including the effect of environmental factors on mortality rates were able to reproduce three decades of variation in the number of females with cubs of the year (Fcoy), including the decline that put the population close to extinction in the mid-nineties, and the following increase in brown bear numbers. This external effect prevailed over density-dependent mechanisms (sexually selected infanticide and female reproductive suppression), with a major impact of climate driven changes in resource availability and a secondary role of changes in human pressure. Predicted changes in population structure revealed a nonlinear relationship between total abundance and the number of Fcoy, highlighting the risk of simple projections based on indirect abundance indices. This study demonstrates the advantages of integrative, mechanistic approaches and provides a widely applicable framework to improve our understanding of wildlife dynamics.

Marine populations often show considerable variation in their productivity, including regime shifts. Of special interest are prolonged shifts to low recruitment and low abundance which occur in many fish populations despite reductions in fishing pressure. One of the possible causes for the lack of recovery has been suggested to be the Allee effect (depensation). Nonetheless, both regime shifts and the Allee effect are empirically emerging patterns but provide no explanation about the underlying mechanisms. Environmental forcing, on the other hand, is known to induce population fluctuations and has also been suggested as one of the primary challenges for recovery. In the present study, we build upon recently developed Bayesian change-point models to explore the contribution of food and climate as external drivers in recruitment regime shifts, while accounting for density-dependent mechanisms (compensation and depensation). Food availability is approximated by the copepod community. Temperature is included as a climatic driver. Three demersal fish populations in the Irish Sea are studied: Atlantic cod ( Gadus morhua ), whiting ( Merlangius merlangus ) and common sole ( Solea solea ). We demonstrate that, while spawning stock biomass undoubtedly impacts recruitment, abiotic and biotic drivers can have substantial additional impacts, which can explain regime shifts in recruitment dynamics or low recruitment at low population abundances. Our results stress the importance of environmental forcing to capture variability in fish recruitment.