Habitat modification affects recruitment of abalone in central New Zealand

The habitat experienced during early life-history stages can determine the number and quality of individuals that recruit to adult populations. In a field experiment, biogenic habitat complexity was manipulated (presence or absence of foliose macroalgae) at two depths (2–3 m and 5–6 m) and the habitat-dependent effects on recruitment of the black foot abalone (Haliotis iris) were examined at three field sites along the south coast of Wellington, New Zealand (41°20′S, 174°47′E), between July and November 2005. Recruit density (<5 weeks post-settlement) was measured on cobbles covered with crustose coralline algae. Habitats of low complexity (barrens treatments) had consistently greater densities of recruits than habitats of high complexity (algae treatments). However, recruits in algae habitats were larger, and for deep habitats, there was greater survival in algae habitats compared with barrens habitats. While depth had no significant effect on early recruit (<2 weeks post-settlement) density, late recruit (<5 weeks post-settlement) density was greater in shallow habitats, and so it seems recruit survival was greater in shallow habitats. In this experiment, algal habitat complexity had strong effects on early recruit abundance, but habitat-dependent variations in recruit growth and survival may modify initial patterns of abundance and determine recruitment to adult abalone populations.     

Predicting intertidal organism temperatures with modified land surface models

Animals and plants in the marine intertidal zone live at the interface between terrestrial and marine environments. This zone is likely to be a sensitive indicator of the effects of climate change in coastal ecosystems, because of several key characteristics including steep environmental gradients, rapid temperature changes during tide transitions, fierce competition for limited space, and a community of mostly sessile organisms. Here we describe a modular modeling approach using modifications to a meteorological land surface model to determine body temperatures of the ecologically dominant rocky intertidal mussel Mytilus californianus, as a tool that can be used as a proxy for ecological performance. We validate model results against in situ measurements made with biomimetic body temperature sensors. Model predictions lie within the range of variability of biomimetic measurements, based on observations over a 4-year period at sites along 1700 km of the US west coast from southern California (34.5°N) to northern Washington (48.4°N). Our modular approach can be easily applied to many situations in the intertidal zone, including bare rock, mussel, barnacle, and algal beds, salt-marsh grasses, and sand- and mud-flats, by modifying the “vegetation layer” in a standard meteorological land surface model. Biophysical models such as these, which link ecological processes to changing climates through predictions of body temperature, are essential for understanding biogeographic patterns of physiological stress and mortality risk.     

Hydrologic and Phosphorus Export Behavior of Small Streams in Commercial Poultry‐Pasture Watersheds1

Romeis, J. Joshua, C. Rhett Jackson, L. Mark Risse, Andrew N. Sharpley, and David E. Radcliffe, 2011. Hydrologic and Phosphorus Export Behavior of Small Streams in Commercial Poultry‐Pasture Watersheds. Journal of the American Water Resources Association (JAWRA) 1‐19. DOI: 10.1111/j.1752‐1688.2011.00521.x Abstract: Few watershed‐scale studies have evaluated phosphorus export in streamflow from commercial poultry‐pasture operations. Continuous streamflow and mixed‐frequency water quality datasets were collected from nine commercial poultry‐pasture (AG) and three forested (FORS) headwater streams (2.4‐44 ha) in the upper Etowah River basin of Georgia to estimate total P (TP) loads and examine variability of hydrologic response and water quality of storm and nonstorm‐flow regimes. Data collection duration ranged from 18 to 22 months, and approximately 1,600 water quality samples were collected. Significant (p < 0.1) inverse relationships were detected between peak flow response variables and both drainage area and fraction of forest cover. Order‐of‐magnitude differences in TP and dissolved reactive P (DRP) concentration were observed between AG and FORS sites and among AG sites. TP yields of FORS sites ranged from 0.01 to 0.1 kg P/ha. Yields of AG sites ranged from 0.031 to 3.17 kg P/ha (median = 0.354 kg P/ha). With 95% confidence intervals, AG yields ranged from 0.025 to 13.1 kg P/ha. These small‐watershed‐scale yields were similar to field‐scale yields measured in other studies in other regions. TP yields were significantly related to area‐weighted Mehlich‐1 soil test P concentrations (p = 0.0073) and base‐flow water sample P concentrations (p ≤ 0.0005). Water quality sampling during base‐flow conditions may be a useful screening tool for P risk‐based management programs.     

A Multi‐Agency Nutrient Dataset Used to Estimate Loads,Improve Monitoring Design,and Calibrate Regional Nutrient SPARROW Models1

Saad, David A., Gregory E. Schwarz, Dale M. Robertson, and Nathaniel L. Booth, 2011. A Multi‐Agency Nutrient Dataset Used to Estimate Loads, Improve Monitoring Design, and Calibrate Regional Nutrient SPARROW Models. Journal of the American Water Resources Association (JAWRA) 47(5):933‐949. DOI: 10.1111/j.1752‐1688. 2011.00575.x Abstract: Stream‐loading information was compiled from federal, state, and local agencies, and selected universities as part of an effort to develop regional SPAtially Referenced Regressions On Watershed attributes (SPARROW) models to help describe the distribution, sources, and transport of nutrients in streams throughout much of the United States. After screening, 2,739 sites, sampled by 73 agencies, were identified as having suitable data for calculating long‐term mean annual nutrient loads required for SPARROW model calibration. These sites had a wide range in nutrient concentrations, loads, and yields, and environmental characteristics in their basins. An analysis of the accuracy in load estimates relative to site attributes indicated that accuracy in loads improve with increases in the number of observations, the proportion of uncensored data, and the variability in flow on observation days, whereas accuracy declines with increases in the root mean square error of the water‐quality model, the flow‐bias ratio, the number of days between samples, the variability in daily streamflow for the prediction period, and if the load estimate has been detrended. Based on compiled data, all areas of the country had recent declines in the number of sites with sufficient water‐quality data to compute accurate annual loads and support regional modeling analyses. These declines were caused by decreases in the number of sites being sampled and data not being entered in readily accessible databases.     

Movements and wintering areas of breeding age Thick-billed Murre <Emphasis Type="Italic">Uria lomvia</Emphasis> from two colonies in Nunavut,Canada

The non-breeding movements of marine birds were poorly known until recently, but this information is essential to understanding the risk to different geographical populations from events on the wintering grounds. We tracked the migration routes and wintering areas of Thick-billed Murre Uria lomvia from two breeding colonies in eastern Canada: Coats Island in northern Hudson Bay and The Minarets, Baffin Island, during the period August 2007–May 2008 using geolocation loggers. Birds from The Minarets moved south rapidly post-breeding and wintered principally off Newfoundland and southern Labrador, or between Newfoundland and southern Greenland, remaining south of 55°N until at least the spring equinox. Those from Coats Island remained in Hudson Bay until at least mid-November, after which they moved rapidly through Hudson Strait to winter in southern Davis Strait and the northern Labrador Sea, mostly north of 55°N. Many individuals stayed throughout the winter in areas of heavy ice cover. Adults from the two colonies appear to be completely segregated in winter and those from Coats Island probably did not enter the area of the winter hunt in Newfoundland. Unexpectedly, some birds from The Minarets wintered in waters beyond the continental slope and outside the distribution of pack ice, demonstrating that particular individuals can be wholly pelagic throughout the winter. Coats Island birds returned through Hudson Strait as soon as open water areas became available in spring. Their sojourn in Hudson Bay coincided very closely with the occurrence of areas with <90% ice cover. In spite of the relatively large error in positions obtained from geolocation loggers, our results demonstrated the value of these devices by uncovering a number of previously unknown aspects of Thick-billed Murre non-breeding ecology in the Northwest Atlantic. Comparison of the non-breeding ecology based on SST experienced in winter show that the winter niche is broader than hitherto assumed, demonstrating that separate populations may experience different selection in the face of climate change.     

Prey selection in <Emphasis Type="Italic">Octopus rubescens</Emphasis>: possible roles of energy budgeting and prey nutritional composition

This study explores the relationship between energy budgeting and prey choice of Octopus rubescens. Seventeen male Octopus rubescens were collected between June 2006 and August 2007 from Admiralty Bay, Washington. Prey choices made by individuals in the laboratory deviated widely from those expected from a simple optimal foraging model. O. rubescens chose the crab Hemigrapsus nudus over the clam Nuttallia obscurata as prey by a ratio of 3:1, even though prey energy content and handling times suggested that this octopus could obtain 10 times more energy intake per unit time when choosing the latter compared to the former prey species. Octopus energy budgets were similar when consuming either of the prey species except for lipid extraction efficiency that was significantly higher in octopuses consuming H. nudus. This suggests that lipid digestibility may play an important role in the prey choice of O. rubescens.     

The ability of a benthic elasmobranch to discriminate between biological and artificial electric fields

To investigate the ability of elasmobranchs to distinguish between differing prey-type electric fields we examined the electroreceptive foraging behaviour of a model species, Scyliorhinus canicula (small-spotted catshark). Catshark preferences were studied by behaviourally conditioning them to swim through narrow tunnels, and on exit presenting them simultaneously with two different electric fields. Their subsequent choices of the following paired options were recorded; (i) Two artificial electric fields (dipole electrodes) with different magnitude direct current (D.C.), (ii) Two artificial electric fields, one D.C. and the other alternating current (A.C.), of the same magnitude, and (iii) similar magnitude, natural and artificial D.C. electric fields associated with shore crabs and dipole electrodes respectively. We found a highly significant preference for the stronger D.C. electric field and a less pronounced, but still significant, preference for the A.C. electric field rather than the D.C. electric field. No preference was demonstrated between the artificial and natural D.C. electric fields. The findings are discussed in relation to the animal’s diet and ecology and with regard to anthropogenic sources of electric fields within their habitat.     

Modelling landscape effects on density-contact rate relationships of deer in eastern Alberta: Implications for chronic wasting disease

Managing wildlife diseases requires an understanding of disease transmission, which may be strongly affected by host population density and landscape features. Transmission models are typically fit from time-series disease prevalence data and modelled based on how the contact rate among hosts is affected by density, which is often assumed to be a linear (density-dependent transmission) or constant (frequency-dependent transmission) relationship. However, long-term time-series data is unavailable for emerging diseases, and this approach cannot account for independent effects of landscape. We developed a mechanistic model based on ecological data to empirically derive the contact rate-density relationship in white-tailed and mule deer in an enzootic region of chronic wasting disease (CWD) in Alberta, Canada and to determine whether it was affected by landscape. Using data collected from aerial surveys and GPS-telemetry, we developed empirical relationships predicting deer group size, home range size, and habitat selection to iteratively simulate deer distributions across a range of densities and landscapes. We calculated a relative measure of total per-capita contact rate, which is proportional to the number of other deer contacted per individual per unit time, for each distribution as the sum of pairwise contact rates between a target deer and all other individuals. Each pairwise contact rate was estimated from an empirical relationship developed from GPS-telemetry data predicting pairwise contact rates as a function of home range overlap and landscape structure. Total per-capita contact rates increased as a saturating function of density, supporting a transmission model intermediate between density- and frequency-dependent transmission. This pattern resulted from group sizes that reached an asymptote with increasing deer density, although this relationship was mediated by tree and shrub coverage in the landscape, such that in heavily wooded areas, the contact rate saturated at much lower densities. These results suggest that CWD management based on herd reductions, which require a density-dependent contact rate to be effective, may have variable effects on disease across a single management region. The novel mechanistic approach we employed for estimating effects of density and landscape on transmission is a powerful complement to typical data-fitting approaches for modelling disease transmission.     

Using simulation to explore the functional relationships of terrestrial carnivore population indices

Population indices based on visits to detection stations commonly are used to monitor wildlife populations. Inferences about populations are based on 1 of 2 measures: (1) change in the proportion of stations visited at least once or (2) change in the cumulative number of visits by unique individuals. The functional relationships between index responses and population density is poorly understood and can lead to misinterpretation of index data when an incorrect functional relationship (e.g. linear) is assumed. We created a flexible simulation environment to study the response of detection-based population indices under a wide variety of conditions meant to reflect species life history and study design. Proportional indices exhibited non-linear saturating responses to changes in population density while cumulative indices responded linearly. Shapes of responses were functions of home range sizes, individual detection probabilities, and spatial arrangement of animals and sampling stations. Non-linear relationships of proportional indices lead to under-estimation of mean population density when data are aggregated from multiple detection stations deployed in a heterogeneous landscape. Cumulative indices have significant statistical advantages over proportional indices including smaller sample sizes required to detect density change, linearity, consistent index responses across a wide range of densities, and ability to aggregate data to meet minimum sample size requirements. Our simulation provides a flexible tool for the interpretation of station-based population indices.     

Characterization of biological responses under different environmental conditions: A hierarchical modeling approach

A natural river system is organized as a nested hierarchy of interconnected habitats with specific environmental conditions to which the biological community has adapted. Due to this hierarchical structure, identifying the role of different stressors on the biological community is a formidable task. Efforts trying to link stressors to biological integrity have always been bound to the geographic scale of the selected study area, leading to scale-specific results. In this research, an attempt is made to lift this limitation and develop a hierarchical, scale-sensitive methodology that can identify the significant environmental stressors to the biological community at different scales. Sites with similar background environmental conditions are clustered using self-organizing maps (SOM). This is used to identify stressors which affect the biological community throughout the area of study - called environmental gradients or large-scale stressors. Subsequently, these clusters of similar observations (sampling sites) are progressively sub-divided using environmental variables with a significant but localized effect on the biological community - called small-scale stressors. A parent group of sites is split only when the resulting sub-groups have significantly different biological responses. At the end of this recursive sites decomposition procedure, the original set of observations is organized as a tree of environmentally homogeneous groups of observations characterized by unique biological responses to multiple stressors with different geographic extents. The developed hierarchical analysis methodology has been validated using a large-size dataset of environmental observations from the State of Ohio. Our results show that habitat degradation and increased nutrient loading are the large-scale stressors with a widespread impact in Ohio. Other stressors, such as heavy metals, pH or nitrate concentrations have significant albeit localized effects on biological integrity.