Conserved community structure and simultaneous divergence events in the fig wasps associated with Ficus benjamina in Australia and China

Localised patterns of species diversity can be influenced by many factors, including regional species pools, biogeographic features and interspecific interactions. Despite recognition of these issues, we still know surprisingly little about how invertebrate biodiversity is structured across geographic scales. In particular, there have been few studies of how insect communities vary geographically while using the same plant host. We compared the composition (species, genera) and functional structure (guilds) of the chalcid wasp communities associated with the widespread fig tree, Ficus benjamina, towards the northern (Hainan province, China) and southern (Queensland, Australia) edges of its natural range. Sequence data were generated for nuclear and mtDNA markers and used to delimit species, and Bayesian divergence analyses were used to test patterns of community cohesion through evolutionary time. Both communities host at least 14 fig wasp species, but no species are shared across continents. Community composition is similar at the genus level, with six genera shared although some differ in species diversity between China and Australia; a further three genera occur in only China or Australia. Community functional structure remains very similar in terms of numbers of species in each ecological guild despite community composition differing a little (genera) or a lot (species), depending on taxonomic level. Bayesian clustering analyses favour a single community divergence event across continents over multiple events for different ecological guilds. Molecular dating estimates of lineage splits between nearest inter-continental species pairs are broadly consistent with a scenario of synchronous community divergence from a shared "ancestral community". Fig wasp community structure and genus-level composition are largely conserved in a wide geographic comparison between China and Australia. Moreover, dating analyses suggest that the functional community structure has remained stable for long periods during historic range expansions. This suggests that ecological interactions between species may play a persistent role in shaping these communities, in contrast to findings in some comparable temperate systems

Seasonal variation in the phenology of Atlantic tarpon in the Florida Keys: migration, occupancy, repeatability, and management implications

Atlantic tarponMegalops atlanticusare important mesopredators in the western Atlantic Ocean, and the focus of a popular recreational fishery that targets them throughout their annual migration in the Gulf of Mexico and southeastern USA. Using 4 years of acoustic telemetry data, we quantified the seasonal variation in phenology of arrival and departure, and occupancy for subadult and adultM. atlanticusin the Florida Keys, USA. While detection profiles of subadultM. atlanticus(n = 11) varied in residency and dispersal patterns, all adultM. atlanticusdetection profiles (n = 47) exhibited seasonal residency. The median spring-summer residence period of adultM. atlanticusranged from 40 to 60 d, with a mean of 51 d across years. At the individual level, repeatability in the timing of arrival and duration were high across years, suggesting that photoperiod may be an important migratory cue. Further, the repeatability in the timing of arrival to the Florida Keys for individuals was not associated with sea surface temperature (SST). At the population level, residency corresponded with the spawning season, with the majority of adultM. atlanticusarriving in April once SST reached 26°C, and then departing in June (27-29°C). Highest occupancy probabilities for adultM. atlanticusoccurred in May (26-28°C) and lowest between August and October. Large aggregations ofM. atlanticusthat occur during the spawning season (April-June) are potentially vulnerable to the effects of habitat degradation and angling-related mortality and behavioral changes. These data onM. atlanticusphenology provide insights for implementing science-based strategic management plans.</jats:p

Time lags: insights from the U.S. Long Term Ecological Research Network

Ecosystems across the United States are changing in complex ways that are difficult to predict. Coordinated long-term research and analysis are required to assess how these changes will affect a diverse array of ecosystem services. This paper is part of a series that is a product of a synthesis effort of the U.S. National Science Foundation’s Long Term Ecological Research (LTER) network. This effort revealed that each LTER site had at least one compelling scientific case study about “what their site would look like” in 50 or 100&nbsp;yr. As the site results were prepared, themes emerged, and the case studies were grouped into separate papers along five themes: state change, connectivity, resilience, time lags, and cascading effects and compiled into this special issue. This paper addresses the time lags theme with five examples from diverse biomes including tundra (Arctic), coastal upwelling (California Current Ecosystem), montane forests (Coweeta), and Everglades freshwater and coastal wetlands (Florida Coastal Everglades) LTER sites. Its objective is to demonstrate the importance of different types of time lags, in different kinds of ecosystems, as drivers of ecosystem structure and function and how these can effectively be addressed with long-term studies. The concept that slow, interactive, compounded changes can have dramatic effects on ecosystem structure, function, services, and future scenarios is apparent in many systems, but they are difficult to quantify and predict. The case studies presented here illustrate the expanding scope of thinking about time lags within the LTER network and beyond. Specifically, they examine what variables are best indicators of lagged changes in arctic tundra, how progressive ocean warming can have profound effects on zooplankton and phytoplankton in waters off the California coast, how a series of species changes over many decades can affect Eastern deciduous forests, and how infrequent, extreme cold spells and storms can have enduring effects on fish populations and wetland vegetation along the Southeast coast and the Gulf of Mexico. The case studies highlight the need for a diverse set of LTER (and other research networks) sites to sort out the multiple components of time lag effects in ecosystems

Going Downriver: Patterns and Cues in Hurricane-Driven Movements of Common Snook in a Subtropical Coastal River

Extreme climate events such as hurricanes can influence the movement and distribution of fish and other aquatic vertebrates. However, our understanding of the scale of movement responses and how they vary across taxa and ecosystems remains incomplete. In this study, we used acoustic telemetry data to investigate the movement patterns of common snook (Centropomus undecimalis) in the Florida Coastal Everglades during Hurricane Irma, which made landfall on the southwest Florida coast as a Category 3 storm on 10 September 2017 after passing in close proximity to our study site. We hypothesized that the hurricane resulted in shifts in distribution and that these movements may have been driven by environmental cues stemming from changes in barometric pressure associated with hurricane conditions, fluctuations in water levels (stage) characterizing altered riverine conditions, or a combination of both hurricane and riverine drivers. The data revealed large-scale movements of common snook in the time period surrounding hurricane passage, with 73% of fish detected moving from the upper river into downriver habitats, and some individuals potentially exiting the river. Furthermore, regression model selection indicated that these movements were correlated to both hurricane and riverine conditions, showing increased common snook movement at higher river stage and lower barometric pressure, and stage explaining a larger proportion of model deviance. Animal movement has widespread and diverse ecological implications, and by better understanding the factors that drive movement, we may anticipate how future extreme climate events could affect fish populations in impact-prone regions