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Climate change is producing shifts in the distribution and abundance of marine species. Such is the case of kelp forests, important marine ecosystem-structuring species whose distributional range limits have been shifting worldwide. Synthesizing long-term time series of kelp forest observations is therefore vital for understanding the drivers shaping ecosystem dynamics and for predicting responses to ongoing and future climate changes. Traditional methods of mapping kelp from satellite imagery are time-consuming and expensive, as they require high amount of human effort for image processing and algorithm optimization. Here we propose the use of mask region-based convolutional neural networks (Mask R-CNN) to automatically assimilate data from open-source satellite imagery (Landsat Thematic Mapper) and detect kelp forest canopy cover. The analyses focused on the giant kelp Macrocystis pyrifera along the shorelines of southern California and Baja California in the northeastern Pacific. Model hyper-parameterization was tuned through cross-validation procedures testing the effect of data augmentation, and different learning rates and anchor sizes. The optimal model detected kelp forests with high performance and low levels of overprediction (Jaccard’s index: 0.87 ± 0.07; Dice index: 0.93 ± 0.04; over prediction: 0.06) and allowed reconstructing a time series of 32 years in Baja California (Mexico), a region known for its high variability in kelp owing to El Niño events. The proposed framework based on Mask R-CNN now joins the list of cost-efficient tools for long-term marine ecological monitoring, facilitating well-informed biodiversity conservation, management and decision making.

Little is known about the local to regional scale variability in biomass and productivity of many subtidal ecosystems, as appropriate field surveys are both time and labor intensive. Here, we combined high-resolution satellite imagery with aerial photos and diver sampling to assess changes in giant kelpMacrocystis pyriferacanopy cover and biomass along a ~60 km stretch of coastline in the Santa Barbara Channel, California, USA. Our objectives were to (1) develop new methods for estimating giant kelp canopy cover and biomass using satellite imagery, and (2) assess temporal changes in kelp forest biomass across multiple spatial scales. Results of the satellite kelp cover classification compared very favorably with near-coincident high-resolution aerial camera surveys (r² = 0.90). Monthly diver observations of biomass for fixed plots at 3 kelp forest sites were strongly correlated with satellite determinations of normalized difference vegetation index (NDVI) signals (r² = 0.77). This allowed us to examine variation in giant kelp biomass across multiple spatial scales (pixel, plot, site, and region). The relationship between plot scale (40 m) changes in biomass and remote assessments of site scale (~1 km) changes varied among sites and depended on the relative location of the plot and the size of the kelp forest at each site. Changes in biomass among sites were well correlated with each other and with the aggregated regional (~60 km) total. Linking field measurements of giant kelp biomass made on a plot scale with regional estimates made by satellite facilitates an understanding of the regional patterns and drivers of biomass and primary production of giant kelp forest ecosystems.

We took advantage of regional differences in environmental forcing and consumer abundance to examine the relative importance of nutrient availability (bottom-up), grazing pressure (top-down), and storm waves (disturbance) in determining the standing biomass and net primary production (NPP) of the giant kelp Macrocystis pyrifera in central and southern California. Using a nine-year data set collected from 17 sites we show that, despite high densities of sea urchin grazers and prolonged periods of low nutrient availability in southern California, NPP by giant kelp was twice that of central California where nutrient concentrations were consistently high and sea urchins were nearly absent due to predation by sea otters. Waves associated with winter storms were consistently higher in central California, and the loss of kelp biomass to winter wave disturbance was on average twice that of southern California. These observations suggest that the more intense wave disturbance in central California limited NPP by giant kelp under otherwise favorable conditions. Regional patterns of interannual variation in NPP were similar to those of wave disturbance in that year-to-year variation in disturbance and NPP were both greater in southern California. Our findings provide strong evidence that regional differences in wave disturbance overwhelmed those of nutrient supply and grazing intensity to determine NPP by giant kelp. The important role of disturbance in controlling NPP revealed by our study is likely not unique to giant kelp forests, as vegetation dynamics in many systems are dominated by post-disturbance succession with climax communities being relatively uncommon. The effects of disturbance frequency may be easier to detect in giant kelp because it is fast growing and relatively short lived, with cycles of disturbance and recovery occurring on time scales of years. Much longer data sets (decades to centuries) will likely be needed to properly evaluate the role of disturbance relative to other processes in determining patterns of NPP in other systems.

Tropical peatlands play an important role in global carbon (C) cycling, but little is known about factors driving carbon dioxide (CO2) and methane (CH4) emissions from these ecosystems, especially production in deeper soils. This study aimed to identify source material and processes regulating C emissions originating deep in three sites in a peatland on the Caribbean coast of Panama. We hypothesized that (1) surface-derived organic matter transported down the soil profile is the primary C source for respiration products at depth and that (2) high lignin content results in hydrogenotrophic methanogenesis as the dominant CH4 production pathway throughout the profile. We used radiocarbon isotopic values to determine whether CO2 and CH4 at depth are produced from modern substrates or ancient deep peat, and we used stable C isotopes to identify the dominant CH4 production pathway. Peat organic chemistry was characterized using 13C solid-state nuclear magnetic resonance spectroscopy (13C-NMR). We found that deep peat respiration products had radiocarbon signatures that were more similar to surface dissolved organic C (DOC) than deep solid peat. These results indicate that surface-derived organic matter was the dominant source for gas production at depth in this peatland, likely because of vertical transport of DOC from the surface to depth. Lignin, which was the most abundant compound (55 %–70 % of C), increased with depth across these sites, whereas other C compounds like carbohydrates did not vary with depth. These results suggest that there is no preferential decomposition of carbohydrates but instead preferential retention of lignin. Stable isotope signatures of respiration products indicated that hydrogenotrophic rather than acetoclastic methanogenesis was the dominant production pathway of CH4 throughout the peat profile. These results show that deep C in tropical peatlands does not contribute greatly to surface fluxes of carbon dioxide, with compounds like lignin preferentially retained. This protection of deep C helps explain how peatland C is retained over thousands of years and points to the vulnerability of this C should anaerobic conditions in these wet ecosystems change.

AIM: We examined (1) the relationships between aboveground tropical forest C storage, biodiversity and environmental drivers and (2) how these relationships inform theory concerning ecosystem function and biodiversity. Experiments have shown that there is a positive relationship between biodiversity and ecosystem functioning, but intense debate exists on the underlying mechanisms. While some argue that mechanisms such as niche complementarity increase ecosystem function, others argue that these relationships are a selection effect. LOCATION: Eleven tropical forests in the Americas, Africa and Asia. METHODS: We analysed the correlates of biodiversity and carbon storage in tropical forests using data from 59 1‐ha tree plots from a standardized global tropical forest biodiversity‐monitoring network. We examined taxonomic and functional diversity, aboveground C storage and environmental variables in order to determine the relationships between biodiversity and carbon storage in natural (non‐plantation) tropical forests. RESULTS: We found that aboveground C storage in tropical forests increased with both taxonomic diversity and functional dominance, specifically the dominance of genera with large maximum diameters, after potential environmental drivers were accounted for (final model R² = 0.38, P < 0.001). MAIN CONCLUSIONS: Our results suggest that niche complementarity and the selection effect are not mutually exclusive: they both play a role in structuring tropical forests. While previous studies have documented relationships between diversity and C storage, these have largely been conducted on small scales in biomes that are relatively species poor compared with tropical forests (e.g. grasslands and temperate or boreal forests). Our results demonstrate that these positive biodiversity–ecosystem functioning relationships are also present in hyperdiverse systems on spatial scales relevant to conservation and management. This insight can be used to inform the conservation and management of tropical forests, which play a critical role in the global carbon cycle and are some of the biologically richest ecosystems on the planet.

Populations of many species display spatially synchronous fluctuations in abundance. Synchrony is most commonly attributed to three processes: factors that influence recruitment (e.g., dispersal, early survival), large-scale environmental variability, and spatially autocorrelated trophic interactions. However it is often difficult to link population synchrony to a specific dominant process, particularly when multiple synchronizing forces are operating. We utilized a new satellite-based data set of giant kelp (Macrocystis pyrifera) canopy biomass to examine population synchrony in southern California kelp forests on spatial scales ranging from 50 m to 300 km and temporal scales ranging from 1 to 11 years. We examined the relationship between synchrony and distance for adult kelp populations, kelp recruits, sea urchin abundance (a major grazer of kelp), and environmental variables known to influence kelp population dynamics. Population synchrony in giant kelp decreased with distance between populations: an initial rapid exponential decrease between 50 m and 1.3 km was followed by a second, large-scale decrease between distances of 1.3 km and 172 km. The 50-m to 1.3-km spatial scale corresponded to the scales of synchrony in the abundance of sea urchins and young kelp recruits, suggesting that local drivers of predation and recruitment influence small-scale synchrony in kelp populations. The spatial correlation patterns of environmental variables, particularly wave height, were similar to the synchrony—distance relationship of kelp populations from 1.3 km to 172 km, suggesting that regional environmental variability, i.e., the Moran effect, was the dominant process affecting synchrony at larger spatial scales. This two-step pattern in the relationship between kelp biomass synchrony and distance was apparent in each of the 11 years of our study. Our results highlight the potential for synthesizing approaches from both landscape and population ecology in order to identify the multiple processes that generate synchrony in population dynamics.

The Psychiatric Emergency Service (PES) has evolved into a separate service with its own space and staff specialized for the handling of psychiatric emergencies. A study of trends in our PES reveals increased need for children's services, issues with managed care and an expansion in the use of the PES as a filter for the mental health system in dealing with substance abuse. Education and research have been added to the missions of the PES and there is strong potential for future development in this area. PESs of the future may be very different, with advances in communication, safety, computerized records and databases. New dilemmas in balancing the patient's right to confidentiality and autonomy against the potential of these advances are bound to occur.

Synthesizing long-term observations at multiple scales is vital for understanding the environmental drivers of ecosystem dynamics. We assessed the role of several environmental drivers in explaining temporal and spatial patterns in the abundance of giant kelpMacrocystis pyriferain the Santa Barbara Channel between 1984 and 2009. We developed a novel method for estimating the canopy biomass of giant kelp from Landsat 5 Thematic Mapper satellite imagery, which allowed us to examine the dynamics of giant-kelp biomass on spatial scales ranging from 100s of m² to 100s of km² and temporal scales ranging from several weeks to 25 yr. Comparisons of changes in canopy biomass with oceanographic and climatic data revealed that winter losses of regional kelp canopy biomass were positively correlated with significant wave height (r² = 0.50), while spring recoveries were negatively correlated with sea surface temperature (r² = 0.30; used as a proxy for nutrient availability). On interannual timescales, regional kelp-canopy biomass lagged the variations in wave heights, sea surface temperatures, and the North Pacific Gyre Oscillation index by 3 yr, indicating that these factors affect cycles of kelp recruitment and mortality. Results from cluster analysis showed that the response of kelp biomass to environmental conditions varied among different subregions of the Santa Barbara Channel. The dynamics of kelp biomass in exposed regions were related to wave disturbance, while kelp dynamics in sheltered regions tracked sea surface temperatures more closely. These results depict a high level of regional heterogeneity in the biomass dynamics of this important foundation species.

Within the endemic invertebrate faunas of hydrothermal vents, five biogeographic provinces are recognized. Invertebrates at two Indian Ocean vent fields (Kairei and Edmond) belong to a sixth province, despite ecological settings and invertebrate-bacterial symbioses similar to those of both western Pacific and Atlantic vents. Most organisms found at these Indian Ocean vent fields have evolutionary affinities with western Pacific vent faunas, but a shrimp that ecologically dominates Indian Ocean vents closely resembles its Mid-Atlantic counterpart. These findings contribute to a global assessment of the biogeography of chemosynthetic faunas and indicate that the Indian Ocean vent community follows asymmetric assembly rules biased toward Pacific evolutionary alliances.

It has been hypothesized that the δ 13C values of chemoautotrophs at deep-sea hydrothermal vents, which cluster in two groups around -11‰ and -30‰, are due to variation in isotopic discrimination by different forms of RubisCO. The most enriched δ 13C values are from the vestimentiferan tubeworm Riftia pachyptila, whose bacterial endosymbionts provide essentially all of its organic carbon via CO2 fixation by a form II RubisCO. The kinetic parameters of purified R. pachyptila symbiont RubisCO were determined to assess the degree to which the δ 13C values of tubeworm biomass are due to isotopic fractionation during CO2 fixation by this enzyme. Like most form II enzymes, the $\\text{K}_{\\text{CO}_{2}}$ is high, at 240 μmol L-1, whereas the CO2/O2 specificity factor (Ω) is low, at 8.6. The ε value, which is proportional to the degree of isotopic discrimination by the enzyme, was determined to be 19.5‰, lower than that for form I RubisCO. This low ε value supports the hypothesis that the degree of isotopic fractionation during CO2 fixation appears to be an important influence on the δ 13C values of R. pachyptila biomass. Our results indicate that it is necessary to consider RubisCO ε values in interpreting δ 13C values from autotrophs.