Functional autoregressive forecasting of long-term seabed evolution

There is a need for decadal predictions of the seabed evolution, for example to inform resurvey strategies when maintaining navigation channels. The understanding of the physical processes involved in morphological evolution, and the viability of process models to accurately model evolution over these time scales, are currently limited. As a result, statistical approaches are used to supply long-term forecasts. In this paper, we introduce a novel statistical approach for this problem: the autoregressive Hilbertian model (ARH). This model naturally assesses the time evolution of spatially-distributed measurements. We apply the technique to a coastal area in the East Anglian coast over the period 1846 to 2002, and compare with two other statistical methods used recently for seabed prediction: the autoregressive model and the EOF model. We evaluate the performance of the three methods by comparing observations and predictions for 2002. The ARH model enables a reduction of 10% of the root mean squared errors. Finally, we compute the variability in the predictions related to time sampling using the jackknife, a method that uses subsamples to quantify uncertainties.     

To preserve or to develop? East Bay dredging project,South Caicos,Turks and Caicos Islands

The Turks and Caicos Islands are currently in the midst of an economic revolution from a marine-based provisional economy to a tourism economy. East Bay, South Caicos, is currently under construction with plans for a 160-unit condominium complex. Included in the project plan is removal of seagrass beds in front of the development to make a sandy beach for tourists. The aims of this study were to (i) describe the bathymetry and benthic habitat coverage of East Bay before dredging takes place and (ii) perform an economic valuation on the turtle grass beds that will be dredged using ecosystem valuation and emergy analysis techniques. The bathymetry survey revealed shallow waters (<1.5 m) until the reef drop off (～650 m offshore). Benthic habitat exhibits zonation following the general progression: sand plain, algal plain, seagrass, coral rubble and seagrass, rock and turf algae, and reef flat. Ecosystem services valued the proposed dredging area at USD $28,807 per year, compared to emergy analysis, which valued the proposed dredging site at USD $32,060 per year. The baselines presented in the study may facilitate a quantitative assessment of dredging impacts on turtle grass once dredging is complete and an economical cost-benefit-analysis of the dredging project to see whether the economic gains outweigh the ecological costs of dredging in front of the East Bay development.     

Long-term changes of heavy metal and sulphur concentrations in ecosystems of the Taymyr Peninsula (Russian Federation) North of the Norilsk Industrial Complex

The Norilsk industrial ore smelting complex (Taymyr Peninsula, Russian Federation) has significantly impacted many components of local terrestrial and aquatic environments. Whether it has had a major impact on the wider Russian Arctic remains controversial as studies are scarce. From 1986 to 2004, data on heavy metal (Cu, Ni, Zn, Hg, Cd and Hg) concentrations in fish (burbot), moss, lichens, periphyton, hydric soils and snow in and around Norilsk and the most northern parts of the Taymyr Peninsula were analysed. Very high concentrations of Cu (203 μg L?1 ± 51 μg L?1) and Ni (113 μg L?1 ± 15 μg L?1) were found in the water of the Schuchya River close to Norilsk. Heavy metal concentrations in burbot liver were highest in Lake Pyasino near Norilsk compared to other study regions that were >100 km distant. From 1989-1996, Cu (121 μg L?1 ± 39 μg L?1 SD), Zn (150 μg L?1) ± 70 μg L?1) and Ni (149 μg L?1 ± 72 μg L?1) snow concentrations were greatest in Norilsk, but were low elsewhere. By 2004, these concentrations had dropped significantly, especially for Cu-74 μg L?1 (±18.7 μg L?1 SD), Zn-81.7 μg L?1 (± 31.3 μg L?1 SD) and Ni-80 μg L?1(±18.0 μg L?1 SD). Norilsk and its surroundings are subject to heavy pollution from the Norilsk metallurgical industry but these are absent from the greater Arctic region due to the prevailing winds and the Byrranga Mountains. Pollution abatement measures have been made so further investigations are necessary in order to assess their efficiency.     

In situ polar organic chemical integrative sampling (POCIS) of steroidal estrogens in sewage treatment works discharge and river water

A passive sampler (the polar organic chemical integrative sampler; POCIS) was assessed for its ability to sample natural estrogens (17β-estradiol, E2; estrone, E1 and estriol, E3) and the synthetic estrogen (17α-ethynylestradiol, EE2) in the outlet of a sewage treatment works over several weeks. The performance of the POCIS was investigated and optimised in the laboratory before field deployment with high recoveries (66-99%) were achieved for all estrogens. Moreover, it was shown that POCIS does not exhibit any preferential selectivity towards any of the target compounds. The sampling rates of E1, E2 and E3 were 0.018 ± 0.009, 0.025 ± 0.014 and 0.033 ± 0.019 L d(-1), respectively. Following field deployments of 28 days in the discharge of a sewage works, POCIS was shown to enhance the sensitivity of estrogen detection, especially for E3, and provide time-weighted average (TWA) concentrations of E1, E2 and E3, ranging from undetectable to 12 ng L(-1) upstream of the outflow of a sewage treatment works, 13 to 91 ng L(-1) at the outflow and 8 to 39 ng L(-1) downstream of the outflow. This revealed that E1, E2 and E3 are not completely removed during sewage treatment, with concentrations most likely being maintained by contributions from conjugated estrogen analogues. Grab water samples showed considerable variation in the concentrations of estrogens over a longer period (6 months). The results confirm that POCIS is an effective and non-discriminatory method for the detection of low concentrations of estrogens in the aquatic environment.     

A Method for Ensemble Wildland Fire Simulation

An ensemble simulation system that accounts for uncertainty in long-range weather conditions and two-dimensional wildland fire spread is described. Fuel moisture is expressed based on the energy release component, a US fire danger rating index, and its variation throughout the fire season is modeled using time series analysis of historical weather data. This analysis is used to characterize the seasonal trend in ERC, autocorrelation of residuals, and daily standard deviation and stochastically generate artificial time series of afternoon fuel moisture. Daily wind speed and direction are sampled stochastically from joint probabilities of historical wind speed and direction for the date range of the fire simulation period. Hundreds or thousands of fire growth simulations are then performed using the synthetic fire weather sequences. The performance of these methods is evaluated in terms of the number of ensemble member simulations, one- versus two-dimensional fire spread simulations, and comparison with results from 91 fires occurring from 2007 to 2009. Simulations were found to be in consistent agreement with observations, but trends indicate that the ensemble average of simulated fire sizes were consistently larger than actual fires whereas the farthest extent burned by fires was underestimated.     

Litterfall 15N abundance indicates declining soil nitrogen availability in a free-air CO2 enrichment experiment

Forest productivity increases in response to carbon dioxide (CO2) enrichment of the atmosphere. However, in nitrogen-limited ecosystems, increased productivity may cause a decline in soil nitrogen (N) availability and induce a negative feedback on further enhancement of forest production. In a free-air CO2 enrichment (FACE) experiment, the response of sweetgum (Liquidambar styraciflua L.) productivity to elevated CO2 concentrations [CO2] has declined over time, but documenting an associated change in soil N availability has been difficult. Here we assess the time history of soil N availability through analysis of natural 15N abundance in archived samples of freshly fallen leaf litterfall. Litterfall delta15N declined from 1998 to 2005, and the rate of decline was significantly faster in elevated [CO2]. Declining leaf litterfall delta15N is indicative of a tighter ecosystem N cycle and more limited soil N availability. By integrating N availability over time and throughout the soil profile, temporal dynamics in leaf litterfall delta15N provide a powerful tool for documenting changes in N availability and the critical feedbacks between C and N cycles that will control forest response to elevated atmospheric CO2 concentrations.     

Sport and commercial fishing conflicts: A theoretical analysis

A recreational sector is added to a standard commercial fishing optimal control model to identify public decision variables which should be considered when determining optimal population levels and allocating harvestable fish between sport and commercial users. Both linear and nonlinear models are presented. A predator-prey relationship is also considered. Results derived from the models indicate that shortcomings exist with current economic inputs to policy making because of failure to consider relevant bioeconomic relationships. Future research topics to remedy this are discussed.     

Genomic erosion in a demographically recovered bird species during conservation rescue

The pink pigeon (Nesoenas mayeri) is an endemic species of Mauritius that has made a remarkable recovery after a severe population bottleneck in the 1970s to early 1990s. Prior to this bottleneck, an ex situ population was established from which captive-bred individuals were released into free-living subpopulations to increase population size and genetic variation. This conservation rescue led to rapid population recovery to 400–480 individuals, and the species was twice downlisted on the International Union for the Conservation of Nature (IUCN) Red List. We analyzed the impacts of the bottleneck and genetic rescue on neutral genetic variation during and after population recovery (1993–2008) with restriction site-associated sequencing, microsatellite analyses, and quantitative genetic analysis of studbook data of 1112 birds from zoos in Europe and the United States. We used computer simulations to study the predicted changes in genetic variation and population viability from the past into the future. Genetic variation declined rapidly, despite the population rebound, and the effective population size was approximately an order of magnitude smaller than census size. The species carried a high genetic load of circa 15 lethal equivalents for longevity. Our computer simulations predicted continued inbreeding will likely result in increased expression of deleterious mutations (i.e., a high realized load) and severe inbreeding depression. Without continued conservation actions, it is likely that the pink pigeon will go extinct in the wild within 100 years. Conservation rescue of the pink pigeon has been instrumental in the recovery of the free-living population. However, further genetic rescue with captive-bred birds from zoos is required to recover lost variation, reduce expression of harmful deleterious variation, and prevent extinction. The use of genomics and modeling data can inform IUCN assessments of the viability and extinction risk of species, and it helps in assessments of the conservation dependency of populations.     

Global warming and flowering times in Thoreau's Concord: a community perspective

As a result of climate change, many plants are now flowering measurably earlier than they did in the past. However, some species' flowering times have changed much more than others. Data at the community level can clarify the variation in flowering responses to climate change. In order to determine how North American species' flowering times respond to climate, we analyzed a series of previously unstudied records of the dates of first flowering for over 500 plant taxa in Concord, Massachusetts, USA. These records began with six years of observations by the famous naturalist Henry David Thoreau from 1852 to 1858, continued with 16 years of observations by the botanist Alfred Hosmer in 1878 and 1888-1902, and concluded with our own observations in 2004, 2005, and 2006. From 1852 through 2006, Concord warmed by 2.4 degrees C due to global climate change and urbanization. Using a subset of 43 common species, we determined that plants are now flowering seven days earlier on average than they did in Thoreau's times. Plant flowering times were most correlated with mean temperatures in the one or two months just before flowering and were also correlated with January temperatures. Summer-flowering species showed more interannual variation in flowering time than did spring-flowering species, but the flowering times of spring-flowering species correlated more strongly to mean monthly temperatures. In many cases, such as within the genera Betula and Solidago, closely related, co-occurring species responded to climate very differently from one another. The differences in flowering responses to warming could affect relationships in plant communities as warming continues. Common St. John's wort (Hypericum perforatum) and highbush blueberry (Vaccinium corymbosum) are particularly responsive to changes in climate, are common across much of the United States, and could serve as indicators of biological responses to climate change. We discuss the need for researchers to be aware, when using data sets involving multiple observers, of how varying methodologies, sample sizes, and sampling intensities affect the results. Finally, we emphasize the importance of using historical observations, like those of Thoreau and Hosmer, as sources of long-term data and to increase public awareness of biological responses to climate change.