Groundwater vulnerability to selenium in semi-arid environments: Amman Zarqa Basin,Jordan

An evaluation of ~250 samples of groundwater in the Amman Zarqa Basin for selenium along with other major and trace elements showed that concentrations of Se ranged between 0.09 and 742 μg/L, with an average value of about 24 μg/L. Selenium concentrations exceeded the recommended threshold for drinking water of the World Health Organization (WHO; 10 μ/L of Se) in 114 samples, with greater than 50 μg/L (quantity equivalent to the Jordanian standard of the allowed concentration of the element in water) of Se in nine cases. The average concentrations of Se in the lower, middle, and upper aquifers of the basin were 3.41, 32.99, and 9.19 μg/L, respectively. Based on the correlation with geologic formations and the statistical analysis of major/minor constituents and Piper tri-linear diagrams, we suggest that carbonate/phosphate dissolution, oxidation–reduction processes, and fertilizers/irrigation return flow are, together, the primary factors affecting the chemistry of the groundwater. Factor analysis helped to define the relative role of limestone-dolomitic dissolution in the aquifers (calcium, magnesium, and bicarbonate), agricultural activities (sulfate, nitrates, phosphorus, and potassium), oxidation–reduction factor (Eh, Fe, Mn, Cu, Zn, and Se), and anthropogenic (industrial) factor (EC, Fe, Cr, Co, Zn, and As). The high variability in Se concentrations might be related to the possibility of a multi-source origin of Se in the area.     

Origins and scales of hypoxia on the Louisiana shelf: Importance of seasonal plankton dynamics and river nutrients and discharge

Management plans for the Mississippi River Basin call for reductions in nutrient concentrations up to 40% or more to reduce hypoxia in the Gulf of Mexico (GOM), while at the same time the government is considering new farm subsidies to promote development of biofuels from corn. Thus there are possibilities of both increasing and decreasing river nutrients depending on national priorities. River flow rates which also influence the extent of hypoxia on the shelf may be altered by global climate change. We have therefore developed a series of simulations to forecast ecosystem response to alterations in nutrient loading and river flow. We simulate ecosystem response and hypoxia events using a linked model consisting of multiple phytoplankton groups competing for nitrogen, phosphorus and light, zooplankton grazing that is influenced by prey edibility and stoichiometry, sub-pycnocline water-column metabolism that is influenced by sinking fecal pellets and algal cells, and multi-element sediment diagenesis. This model formulation depicts four areas of increasing salinity moving westward away from the Mississippi River point of discharge, where the surface mixed layer, four bottom layers and underlying sediments are represented in each area. The model supports the contention that a 40% decrease in river nutrient will substantially reduce the duration and areal extent of hypoxia on the shelf. But it also suggests that in low and middle salinity areas the hypoxia response is saturated with respect to nutrients, and that in high salinity regions small increases in nutrient and river flow will have disproportionally large effects on GOM hypoxia. The model simulations also suggest that river discharge is a stronger factor influencing hypoxia than river nutrients in the Mississippi River plume. Finally, the model simulations suggest that primary production in the low salinity regions is light limited while primary production in the higher salinity zones is phosphate limited during the May to October period when hypoxia is prevalent in the Mississippi River plume.     

Interhemispheric comparison of recruitment to intertidal communities: pattern persistence and scales of variation

Recruitment variation can be a major source of fluctuation in populations and communities, making it difficult to generalize results. Determining the scales of variation and whether spatial patterns in the supply of individuals are persistent over time can provide insight into spatial generality and the application of conservation and metacommunity models. We examined these issues using eight-year-long data sets of monthly recruitment of intertidal mussels (Mytilus spp., Perumytilus purpuratus, Semimytilus algosus, Brachidontes granulata) and barnacles (Balanus glandula, Chthamalus dalli, Jehlius cirratus, Notochthamalus scabrosus) at sites spanning > 900 km along the coasts of Oregon-northern California (OR-NCA, 45.47-39.43 degrees N) and central Chile (CC, 29.5-34.65 degrees S). We evaluated four general "null" hypotheses: that despite different phylogenies and great spatial separation of these taxa, their similar life history strategies and environmental settings lead to similar patterns of recruitment (1) between hemispheres, (2) in time, (3) in space, and (4) at larger and smaller spatial scales. Hypothesis 1 was rejected: along the OR-NCA coast, rates of recruitment were between two and three orders of magnitude higher, and patterns of seasonality were generally stronger and more coherent across space and time than along CC. Surprisingly, however, further analysis revealed regularities in both time and space for all species, supporting hypotheses 2 and 3. Temporal decorrelation scales were 1-3 months, and characteristic spatial scales of recruitment were approximately 250 km. Contrary to hypothesis 4, for the ecologically dominant species in both hemispheres, recruitment was remarkably persistent at larger mesoscales (kilometers) but was highly stochastic at smaller microscales (meters). Across species, increased recruitment variation at large scales was positively associated with increased persistence. Our results have several implications. Although the two regions span distinct latitudinal ranges, potential forcing processes behind these patterns include similar large-scale climates and topographically locked hydrographic features, such as upwelling. Further, spatial persistence of the recruitment patterns of most species at the mesoscale supports the view that marine protected areas can be powerful conservation and management tools. Finally, persistent and yet contrasting spatial patterns of recruitment among competing species suggest that recent metacommunity models might provide useful representations of the mechanisms involved in species coexistence.     

Bioerosion of coral reefs by two Hawaiian parrotfishes: species, size differences and fishery implications

Parrotfishes can be significant bioeroders and sediment producers on coral reefs. We quantified the bioerosion rates of two similarly sized Hawaiian parrotfishes with two different feeding modes (Scarus rubroviolaceus—a scraper and Chlorurus perspicillatus—an excavator). The results showed that feeding modes did not affect bioerosion rates but that bioerosion rates were size dependent, with largest individuals (S. rubroviolaceus 45–54 cm FL) bioeroding up to 380 ± 67 kg ind⁻¹ year⁻¹. The size for onset of bioerosion capabilities for both species was 15 cm. Grazing by the two species consumed 60% of the carbonate production of the fore reef area, suggesting that large parrotfishes in Hawaii are ecologically important bioeroders. As individual large S. rubroviolaceus contributed disproportionately more to bioerosion and sediment production than the equivalent biomass of smaller conspecifics, management strategies designed to retain normal reef bioerosion rates should seek to preserve the historical size structure of S. rubroviolaceus populations and to especially protect the larger size classes.     

Running to stand still: temperature effects on species richness, species turnover, and functional community dynamics

The information on temperature-mediated changes in biodiversity in local assemblages is scarce and mainly addresses the change in species richness. However, warming may have more consistent effects on species turnover than on the number of species. Moreover, very few studies extended the analysis of changes in biodiversity and species composition to questions of associated ecosystem functions such as primary production. Here, we synthesize 4 case studies employing microalgal microcosms within the Aquashift priority program to ask (1) do warming-related shifts in species richness correspond to changes in the rate of biomass production, (2) do similar relationships prevail for evenness, and (3) do warming-related shifts in species turnover stabilize or destabilize biomass production? Two of the four cases are previously unpublished, and for a third case, the link between diversity and functional consequences of temperature was not analyzed before. We found accelerated loss of species with warming in all cases. Biomass production was lower with lower species richness in most cases but increased with lower evenness. Most importantly, the relation between functional and compositional stability was different between cases: More rapid extinction resulted in more variable biomass in 2 cases conducted with a limited species pool, indicating that compositional destabilization relates to functional variability. By contrast, the only experiment with a large species pool (30 species) allowed previously rare species to become dominant in the community and showed more stable biomass at high turnover, indicating that compensatory dynamics (turnover) can promote functional stability. These 4 independent experiments highlight the need to consider both compositional and functional consequences of altered temperature regimes.     

Agricultural legacies in forest environments: tree communities, soil properties, and light availability.

Temperate deciduous forests across much of Europe and eastern North America reflect legacies of past land use, particularly in the diversity and composition of plant communities. Intense disturbances, such as clearing forests for agriculture, may cause persistent environmental changes that continue to shape vegetation patterns as landscapes recover. We assessed the long-term consequences of agriculture for environmental conditions in central New York forests, including tree community structure and composition, soil physical and chemical properties, and light availability. To isolate the effects of agriculture, we compared 20 adjacent pairs of forests that were never cleared for agriculture (primary forests) and forests that established 85-100 years ago on plowed fields (secondary forests). Tree communities in primary and secondary forests had similar stem density, though secondary forests had 14% greater basal area. Species composition differed dramatically between the two forest types, with primary forests dominated by Acer saccharum and Fagus grandifolia and secondary forests by Acer rubrum and Pinus strobus. Primary and secondary forests showed no consistent differences in soil physical properties or in the principal gradient of soil fertility associated with soil pH. Within stands, however, soil water content and pH were more variable in primary forests. Secondary forest soils had 15% less organic matter, 16% less total carbon, and 29% less extractable phosphorus in the top 10 cm than adjacent primary stands, though the ranges of the forest types mostly overlapped. Understory light availability in primary and secondary forests was similar. These results suggest that, within 100 years, post-agricultural stands have recovered conditions comparable to less disturbed forests in many attributes, including tree size and number, soil physical properties, soil chemical properties associated with pH, and understory light availability. The principal legacies of agriculture that remain in these forests are the reduced levels of soil organic matter, carbon, and phosphorus; the spatial homogenization of soil properties; and the altered species composition of the vegetation.     

Statistics for correlated data: phylogenies, space, and time.

Here we give an introduction to the growing number of statistical techniques for analyzing data that are not independent realizations of the same sampling process--in other words, correlated data. We focus on regression problems, in which the value of a given variable depends linearly on the value of another variable. To illustrate different types of processes leading to correlated data, we analyze four simulated examples representing diverse problems arising in ecological studies. The first example is a comparison among species to determine the relationship between home-range area and body size; because species are phylogenetically related, they do not represent independent samples. The second example addresses spatial variation in net primary production and how this might be affected by soil nitrogen; because nearby locations are likely to have similar net primary productivity for reasons other than soil nitrogen, spatial correlation is likely. In the third example, we consider a time-series model to ask whether the decrease in density of a butterfly species is the result of decreases in its host-plant density; because the population density of a species in one generation is likely to affect the density in the following generation, time-series data are often correlated. The fourth example combines both spatial and temporal correlation in an experiment in which prey densities are manipulated to determine the response of predators to their food supply. For each of these examples, we use a different statistical approach for analyzing models of correlated data. Our goal is to give an overview of conceptual issues surrounding correlated data, rather than a detailed tutorial in how to apply different statistical techniques. By dispelling some of the mystery behind correlated data, we hope to encourage ecologists to learn about statistics that could be useful in their own work. Although at first encounter these techniques might seem complicated, they have the power to simplify ecological research by making more types of data and experimental designs open to statistical evaluation.     

Multiple indicators, partially ordered sets, and linear extensions: Multi-criterion ranking and prioritization

This paper is concerned with the question of ranking a finite collection of objects when a suite of indicator values is available for each member of the collection. The objects can be represented as a cloud of points in indicator space, but the different indicators (coordinate axes) typically convey different comparative messages and there is no unique way to rank the objects while taking all indicators into account. A conventional solution is to assign a composite numerical score to each object by combining the indicator information in some fashion. Consciously or otherwise, every such composite involves judgments (often arbitrary or controversial) about tradeoffs or substitutability among indicators. Rather than trying to combine indicators, we take the view that the relative positions in indicator space determine only a partial ordering and that a given pair of objects may not be inherently comparable. Working with Hasse diagrams of the partial order, we study the collection of all rankings that are compatible with the partial order (linear extensions). In this way, an interval of possible ranks is assigned to each object. The intervals can be very wide, however. Noting that ranks near the ends of each interval are usually infrequent under linear extensions, a probability distribution is obtained over the interval of possible ranks. This distribution, called the rank-frequency distribution, turns out to be unimodal (in fact, log-concave) and represents the degree of ambiguity involved in attempting to assign a rank to the corresponding object. Stochastic ordering of probability distributions imposes a partial order on the collection of rank-frequency distributions. This collection of distributions is in one-to-one correspondence with the original collection of objects and the induced ordering on these objects is called the cumulative rank-frequency (CRF) ordering; it extends the original partial order. Although the CRF ordering need not be linear, it can be iterated to yield a fixed point of the CRF operator. We hypothesize that the fixed points of the CRF operator are exactly the linear orderings. The CRF operator treats each linear extension as an equal voter in determining the CRF ranking. It is possible to generalize to a weighted CRF operator by giving linear extensions differential weights either on mathematical grounds (e.g., number of jumps) or empirical grounds (e.g., indicator concordance). Explicit enumeration of all possible linear extensions is computationally impractical unless the number of objects is quite small. In such cases, the rank-frequencies can be estimated using discrete Markov chain Monte Carlo (MCMC) methods.     

Scanning electron microscopy study of the gills,scales and erythrocytes of Anabas testudineus upon exposure to chlorpyrifos

The present study was undertaken to assess the toxicity of sublethal concentrations (125, 250, and 375 µg L^?1) of chlorpyrifos on Anabas testudineus for 21 days. The morphological changes on the gills, scales, and erythrocytes of A. testudineus were observed using scanning electron microscopy. Gill alterations included highly active mucous cells, epithelial hyperplasia, and fusion of secondary lamellae. The scales showed damaged lepidonts. Oozed out cytoplasmic content and lobopodial projections were observed in the erythrocytes after exposure to chlorpyrifos.     

Hierarchical dominance structure in reintroduced California condors: correlates, consequences, and dynamics

Populations of reintroduced California condors (Gymnogyps californianus) develop complex social structures and dynamics to maintain stable group cohesion, and birds that do not successfully integrate into group hierarchies have highly impaired survivability. Consequently, improved understanding of condor socioecology is needed to inform conservation management strategies. We report on the dominance structure of free-ranging condors and identify the causes and consequences of rank in condor populations by matching social status with the behavioral and physical correlates of individual birds. We characterized the hierarchical social structure of wild condor populations as mildly linear, despotic, and dynamic. Condor social groups were not egalitarian and dominance hierarchies regulated competitive access to food resources. Absence of kin-based social groups also indicated that condor social structure is individualistic. Agonistic interactions among condors were strongly unidirectional, but the overall linearity and steepness of their hierarchies was low. Although one aggressive male maintained the highest dominance rank across the 3-year observation period, there was considerable fluidity in social status among condors within middle and lower rank orders. Older condors were more dominant than younger birds and younger males supplanted older females over time to achieve higher status. Dominance rank did not predict the amount of time that a bird spent feeding at a carcass or the frequency that a bird was interrupted while feeding. Thus, younger, less dominant birds are able to obtain sufficient nutrition in wild social populations.     

The importance of space, time, and stochasticity to the demography and management of Alliaria petiolata

As population modeling is increasingly called upon to guide policy and management, it is important that we understand not only the central tendencies of our study systems, but the consequences of their variation in space and time as well. The invasive plant Alliaria petiolata (garlic mustard) is actively managed in the United States and is the focus of a developing biological control program. Two weevils (Coleoptera: Curculionidae: Ceutorhynchus) that reduce fecundity (C. alliariae) and rosette survival plus fecundity (C. scrobicollis) are under consideration for release pending host specificity testing. We used a demographic modeling approach to (1) quantify variability in A. petiolata growth and vital rates and (2) assess the potential for single- or multiple-agent biocontrol to suppress growth of 12 A. petiolata populations in Illinois and Michigan studied over three plant generations. We used perturbation analyses and simulation models with stochastic environments to estimate stochastic growth rates (lambda(S)) and predict the probability of successful management using either a single biocontrol agent or two agent species together. Not all populations exhibited invasive dynamics. Estimates of lambda(S) ranged from 0.78 to 2.21 across sites, while annual, deterministic growth (lambda) varied up to sevenfold within individual sites. Given our knowledge of the biocontrol agents, this analysis suggests that C. scrobicollis alone may control A. petiolata at up to 63% of our study sites where lambda >1, with the combination of both agents predicted to succeed at 88% of sites. Across sites and years, the elasticity rankings were dependent on lambda. Reductions of rosette survival, fecundity, or germination of new seeds are predicted to cause the greatest reduction of lambda in growing populations. In declining populations, transitions affecting seed bank survival have the greatest effect on lambda. This contrasts with past analyses that varied parameters individually in an otherwise constant matrix, which may yield unrealistic predictions by decoupling natural parameter covariances. Overall, comparisons of stochastic and deterministic growth rates illustrate how analyses of individual populations or years could misguide management or fail to characterize complex traits such as invasiveness that emerge as attributes of populations rather than species.     

Spatial scaling of avian population dynamics: population abundance, growth rate, and variability

Synchrony in population fluctuations has been identified as an important component of population dynamics. In a previous study, we determined that local-scale (<15-km) spatial synchrony of bird populations in New England was correlated with synchronous fluctuations in lepidopteran larvae abundance and with the North Atlantic Oscillation. Here we address five questions that extend the scope of our earlier study using North American Breeding Bird Survey data. First, do bird populations in eastern North America exhibit spatial synchrony in abundances at scales beyond those we have documented previously? Second, does spatial synchrony depend on what population metric is analyzed (e.g., abundance, growth rate, or variability)? Third, is there geographic concordance in where species exhibit synchrony? Fourth, for those species that exhibit significant geographic concordance, are there landscape and habitat variables that contribute to the observed patterns? Fifth, is spatial synchrony affected by a species' life history traits? Significant spatial synchrony was common and its magnitude was dependent on the population metric analyzed. Twenty-four of 29 species examined exhibited significant synchrony in population abundance: mean local autocorrelation (rho)= 0.15; mean spatial extent (mean distance where rho=0) = 420.7 km. Five of the 29 species exhibited significant synchrony in annual population growth rate (mean local autocorrelation = 0.06, mean distance = 457.8 km). Ten of the 29 species exhibited significant synchrony in population abundance variability (mean local autocorrelation = 0.49, mean distance = 413.8 km). Analyses of landscape structure indicated that habitat variables were infrequent contributors to spatial synchrony. Likewise, we detected no effects of life history traits on synchrony in population abundance or growth rate. However, short-distance migrants exhibited more spatially extensive synchrony in population variability than either year-round residents or long-distance migrants. The dissimilarity of the spatial extent of synchrony across species suggests that most populations are not regulated at similar spatial scales. The spatial scale of the population synchrony patterns we describe is likely larger than the actual scale of population regulation, and in turn, the scale of population regulation is undoubtedly larger than the scale of individual ecological requirements.     

Chihuahuan Desert kangaroo rats: nonlinear effects of population dynamics, competition, and rainfall

Using long-term data on two kangaroo rats in the Chihuahuan Desert of North America, we fitted logistic models including the exogenous effects of seasonal rainfall patterns. Our aim was to test the effects of intraspecific interactions and seasonal rainfall in explaining and predicting the numerical fluctuations of these two kangaroo rats. We found that logistic models fit both data sets quite well; Dipodomys merriami showed lower maximum per capita growth rates than Dipodomys ordii, and in both cases logistic models were nonlinear. Summer rainfall appears to be the most important exogenous effect for both rodent populations; models including this variable were able to predict independent data better than models including winter rainfall. D. merriami was also negatively affected by another kangaroo rat (Dipodomys spectabilis), consistent with previous experimental evidence. We hypothesized that summer rainfall influences the carrying capacity of the environment by affecting seed availability and the intensity of intraspecific competition.