Project description:Isolation of the Caribbean Sea from the tropical Eastern Pacific by uplift of the Isthmus of Panama in the late Pliocene was associated with major, taxonomically variable, shifts in Caribbean biotic composition, and extinction, but inferred causes of these biological changes have remained elusive. We addressed this through falsifiable hypotheses about how independently determined historical changes in oceanographic conditions may have been responsible. The most striking environmental change was a sharp decline in upwelling intensity as measured from decreases in intra-annual fluctuations in temperature and consequently in planktonic productivity. We then hypothesized three general categories of biological response based upon observed differences in natural history between the oceans today. These include changes in feeding ecology, life histories, and habitats. As expected, suspension feeders and predators became rarer as upwelling declined. However, predicted increases in benthic productivity by reef corals, and benthic algae were drawn out over more than 1 Myr as seagrass and coral reef habitats proliferated; a shift that was itself driven by declining upwelling. Similar time lags occurred for predicted shifts in reproductive life history characteristics of bivalves, gastropods, and bryozoans. Examination of the spatial variability of biotic change helps to understand the time lags. Many older species characteristic of times before environmental conditions had changed tended to hang on in progressively smaller proportions of locations until they became extinct as expected from metapopulation theory and the concept of extinction debt. Faunal turnover may not occur until a million or more years after the environmental changes ultimately responsible.
Project description:Understanding relationships between physical drivers and biological response is central to advancing ecological knowledge. Wind is the physical forcing mechanism in coastal upwelling systems, however lags between wind input and biological responses are seldom quantified for marine predators. Lags were examined between wind at an upwelling source, decreased temperatures along the upwelling plume's trajectory, and blue whale occurrence in New Zealand's South Taranaki Bight region (STB). Wind speed and sea surface temperature (SST) were extracted for austral spring-summer months between 2009 and 2019. A hydrophone recorded blue whale vocalizations October 2016-March 2017. Timeseries cross-correlation analyses were conducted between wind speed, SST at different locations along the upwelling plume, and blue whale downswept vocalizations (D calls). Results document increasing lag times (0-2 weeks) between wind speed and SST consistent with the spatial progression of upwelling, culminating with increased D call density at the distal end of the plume three weeks after increased wind speeds at the upwelling source. Lag between wind events and blue whale aggregations (n = 34 aggregations 2013-2019) was 2.09 ± 0.43 weeks. Variation in lag was significantly related to the amount of wind over the preceding 30 days, which likely influences stratification. This study enhances knowledge of physical-biological coupling in upwelling ecosystems and enables improved forecasting of species distribution patterns for dynamic management.
Project description:The whale shark Rhincodon typus is an endangered, highly migratory species with a wide, albeit patchy, distribution through tropical oceans. Ten aerial survey flights along the southern Mozambican coast, conducted between 2004-2008, documented a relatively high density of whale sharks along a 200 km stretch of the Inhambane Province, with a pronounced hotspot adjacent to Praia do Tofo. To examine the residency and movement of whale sharks in coastal areas around Praia do Tofo, where they may be more susceptible to gill net entanglement, we tagged 15 juveniles with SPOT5 satellite tags and tracked them for 2-88 days (mean = 27 days) as they dispersed from this area. Sharks travelled between 10 and 2,737 km (mean = 738 km) at a mean horizontal speed of 28 ± 17.1 SD km day-1. While several individuals left shelf waters and travelled across international boundaries, most sharks stayed in Mozambican coastal waters over the tracking period. We tested for whale shark habitat preferences, using sea surface temperature, chlorophyll-a concentration and water depth as variables, by computing 100 random model tracks for each real shark based on their empirical movement characteristics. Whale sharks spent significantly more time in cooler, shallower water with higher chlorophyll-a concentrations than model sharks, suggesting that feeding in productive coastal waters is an important driver of their movements. To investigate what this coastal habitat choice means for their conservation in Mozambique, we mapped gill nets during two dedicated aerial surveys along the Inhambane coast and counted gill nets in 1,323 boat-based surveys near Praia do Tofo. Our results show that, while whale sharks are capable of long-distance oceanic movements, they can spend a disproportionate amount of time in specific areas, such as along the southern Mozambique coast. The increasing use of drifting gill nets in this coastal hotspot for whale sharks is likely to be a threat to regional populations of this iconic species.
Project description:Economic growth is associated with the diversification of economic activities, which can be observed via the evolution of product export baskets. Exporting a new product is dependent on having, and acquiring, a specific set of capabilities, making the diversification process path-dependent. Taking an agnostic view on the identity of the capabilities, here we derive a probabilistic model for the directed dynamical process of capability accumulation and product diversification of countries. Using international trade data, we identify the set of pre-existing products, the product Ecosystem, that enables a product to be exported competitively. We construct a directed network of products, the Eco Space, where the edge weight corresponds to capability overlap. We uncover a modular structure, and show that low- and middle-income countries move from product communities dominated by small Ecosystem products to advanced (large Ecosystem) product clusters over time. Finally, we show that our network model is predictive of product appearances.
Project description:Coastal Sabkhas are mudflats found in arid coastal regions that are located within the supratidal zone when high rates of evaporation lead to high salinity. While evaporitic minerals often accumulate underneath the surface, the microbial mats are present on the surface of Sabkhas. Coastal Sabkha, an under-studied ecosystem in Qatar, has the potential to store blue carbon. In the present study, we investigated the carbon storage capacity of two Sabkhas from contrasting geological backgrounds. The spatial and temporal variabilities of the carbon stocks were examined. The results showed that both studied Sabkhas exhibit a considerable potential for soil carbon storage with carbon stocks of 109.11 ± 7.07 Mg C ha-1 and 67.77 ± 18.10 Mg C ha-1 in Dohat Faishakh and Khor al Adaid Sabkha respectively. These values fall within the reported range for carbon stocks in coastal Sabkhas in the region (51-194 Mg C ha-1). Interestingly, the carbon stocks in the sediments of the Sabkhas were higher than those in the sediments of Qatari mangroves (50.17 ± 6.27 Mg C ha-1). These finding suggest that coastal Sabkhas can serve as blue carbon ecosystems in arid environments.
Project description:Spatial variation in the composition of communities is the product of many biotic and environmental interactions. A neglected factor in the analysis of community distribution patterns is the multi-scale nature of the data, which has implications for understanding ecological processes and the development of conservation and environmental management practice. Drawing on recently established multivariate spatial analyses, we investigate whether including relationships between spatial structure and abiotic variables enable us to better discern patterns of species and communities across scales. Data comprised 1200 macrozoobenthic samples collected over an array of distances (30 cm to 1 km) in three New Zealand harbours, as well as commonly used abiotic variables, such as sediment characteristics and chlorophyll a concentrations, measured at the same scales. Moran's eigenvector mapping was used to extract spatial scales at which communities were structured. Benthic communities, representing primarily bivalves, polychaetes and crustaceans, were spatially structured at four spatial scales, i.e. >100 m, 50-100 m, 50-15 m, and < 15 m. A broad selection of abiotic variables contributed to the large-scale variation, whereas a more limited set explained part of the fine-scale community structure. Across all scales, less than 30% of the variation in spatial structure was captured by our analysis. The large number of species (48) making up the 10 highest species scores based on redundancy analyses illustrate the variability of species-scale associations. Our results emphasise that abiotic variables and biodiversity are related at all scales investigated and stress the importance of assessing the relationship between environmental variables and the abundance and distribution of biological assemblages across a range of different scales.
Project description:Sea noise collected over 2003 to 2017 from the Perth Canyon, Western Australia was analysed for variation in the South Eastern Indian Ocean pygmy blue whale song structure. The primary song-types were: P3, a three unit phrase (I, II and III) repeated with an inter-song interval (ISI) of 170-194 s; P2, a phrase consisting of only units II & III repeated every 84-96 s; and P1 with a phrase consisting of only unit II repeated every 45-49 s. The different ISI values were approximate multiples of each other within a season. When comparing data from each season, across seasons, the ISI value for each song increased significantly through time (all fits had p << 0.001), at 0.30 s/Year (95%CI 0.217-0.383), 0.8 s/Year (95%CI 0.655-1.025) and 1.73 s/Year (95%CI 1.264-2.196) for the P1, P2 and P3 songs respectively. The proportions of each song-type averaged at 21.5, 24.2 and 56% for P1, P2 and P3 occurrence respectively and these ratios could vary by up to ± 8% (95% CI) amongst years. On some occasions animals changed the P3 ISI to be significantly shorter (120-160 s) or longer (220-280 s). Hybrid song patterns occurred where animals combined multiple phrase types into a repeated song. In recent years whales introduced further complexity by splitting song units. This variability of song-type and proportions implies abundance measure for this whale sub population based on song detection needs to factor in trends in song variability to make data comparable between seasons. Further, such variability in song production by a sub population of pygmy blue whales raises questions as to the stability of the song types that are used to delineate populations. The high level of song variability may be driven by an increasing number of background whale callers creating 'noise' and so forcing animals to alter song in order to 'stand out' amongst the crowd.
Project description:Acoustic communication is an important aspect of reproductive, foraging and social behaviours for many marine species. Northeast Pacific blue whales (Balaenoptera musculus) produce three different call types-A, B and D calls. All may be produced as singular calls, but A and B calls also occur in phrases to form songs. To evaluate the behavioural context of singular call and phrase production in blue whales, the acoustic and dive profile data from tags deployed on individuals off southern California were assessed using generalized estimating equations. Only 22% of all deployments contained sounds attributed to the tagged animal. A larger proportion of tagged animals were female (47%) than male (13%), with 40% of unknown sex. Fifty per cent of tags deployed on males contained sounds attributed to the tagged whale, while only a few (5%) deployed on females did. Most calls were produced at shallow depths (less than 30 m). Repetitive phrasing (singing) and production of singular calls were most common during shallow, non-lunging dives, with the latter also common during surface behaviour. Higher sound production rates occurred during autumn than summer and they varied with time-of-day: singular call rates were higher at dawn and dusk, while phrase production rates were highest at dusk and night.
Project description:In terrestrial systems, the green wave hypothesis posits that migrating animals can enhance foraging opportunities by tracking phenological variation in high-quality forage across space (i.e., "resource waves"). To track resource waves, animals may rely on proximate cues and/or memory of long-term average phenologies. Although there is growing evidence of resource tracking in terrestrial migrants, such drivers remain unevaluated in migratory marine megafauna. Here we present a test of the green wave hypothesis in a marine system. We compare 10 years of blue whale movement data with the timing of the spring phytoplankton bloom resulting in increased prey availability in the California Current Ecosystem, allowing us to investigate resource tracking both contemporaneously (response to proximate cues) and based on climatological conditions (memory) during migrations. Blue whales closely tracked the long-term average phenology of the spring bloom, but did not track contemporaneous green-up. In addition, blue whale foraging locations were characterized by low long-term habitat variability and high long-term productivity compared with contemporaneous measurements. Results indicate that memory of long-term average conditions may have a previously underappreciated role in driving migratory movements of long-lived species in marine systems, and suggest that these animals may struggle to respond to rapid deviations from historical mean environmental conditions. Results further highlight that an ecological theory of migration is conserved across marine and terrestrial systems. Understanding the drivers of animal migration is critical for assessing how environmental changes will affect highly mobile fauna at a global scale.