Abstract: Comprehending the gifts of ecologyStress ecology, climate change, human well-being, andglobal sustainability are popular items (Naeem et al.2009). Given all the challenges in a developing worldwhere the global population is supposed to reach 9.15billion in 2050 (Pimentel et al. 1999; United NationsPopulation Division 2010), policy makers are, for the firsttime, keen on concrete assessments of our world, lookingwith interest and fear to ecological models. Although thediscussion between scientists and politicians is known tobe difficult, too many recent catastrophes during a singleyear - from the British Petroleum oil spill in the Gulf ofMexico (De Gouw et al. 2011) up to the ongoing radioac-tive Fukushima wreckage (Schiermeier 2011) - rapidlyforced a better and constructive interaction betweenapplied ecologists and policy makers at different organi-zation levels. Such an interaction is also reflected by thearising use of internet metrics, blogs, tweets, and socialnetworking - all digital tools that are already more or lesslinked to the thought process that society and policy arecurrently going through. Scientists are used to the Webof Science for selecting the appropriate papers, and policymakers are using methodologies for weighing opinions(Bollen et al. 2009). The latter authors even defined mod-ern science as a‘gift economy’, and they are absolutelyright. What else should happen to improve the interac-tions between policy and research?

Abstract: Introduction The purpose of this study was to assess enrichments in stable carbon and nitrogen isotopes (δ13C and δ15N) in brown-marbled groupers (Epinephelus fuscoguttatus), a marine fish that has been widely used in aquaculture Stable isotope analysis has been used to evaluate dietary sources and the trophic position of fish There is the need to better understand the pattern of isotope enrichment between consumers and diets under laboratory conditions

Abstract: According to the empirical regularity called Taylor's law, the variance of population density in samples of populations is a power of the mean population density. The exponent is often between 1 and 2. Our experiments investigated how genetics, evolution, and environment shape Taylor's law. Genetically different strains (wild type and hypermutator) of the bacterium Pseudomonas fluorescens evolved and were assayed under different environmental conditions (with and without antibiotic rifampicin and bacteriophage SBW25φ2, separately and in combination). Experimental treatments altered the exponent b, but not the power law form, of the relation between variance and mean population density. Bacterial populations treated only with rifampicin had a narrow range of mean population densities and exponent b = 5.43. Populations exposed to rifampicin plus phage had b = 1.51. In ancestral, control, and phage-exposed populations, mean abundance varied widely and b was not significantly different from 2. Evolutionary factors (mutation rate, selection) and ecological factors (abiotic, biotic) jointly influenced b. Taylor's power law relationship accurately and robustly described variance as a function of mean population density, with overall exponent b = 1.89. These and other experiments with different factors acting on bacterial population size support the relevance of models that predict 'universal' patterns of fluctuation scaling.

Abstract: Spatially explicit ecological research has increased substantially in the past 20 years. Most spatial approaches require the definition of a spatial neighbourhood or the region over which spatial relationships are modelled or assessed. Spatial neighbourhood definitions impact analysis results, and there are benefits in considering neighbourhood definitions that better capture ecological processes. The goal of this research is to present a simple and flexible approach in constraining ecological spatial neighbourhoods using terrain data. Using watershed boundaries, we can restrict spatial neighbourhoods from combining populations or processes that should be separated by terrain effects. We demonstrate the need for ecological constraints by way of a simulation study and highlight our approach with a case study examining mountain pine beetle (Dendroctonus ponderosae, Coleoptera; Hopkins) infestation hot spots. Our results demonstrate how failure to constrain neighbourhoods can lead to errors when the spatial signals from unrelated populations are mixed. Also, unconstrained spatial neighbourhoods can unintentionally detect spatial relationships across many scales. There will be benefits to studies that develop new, ecology-based approaches in defining spatial neighbourhoods that better illuminate ecological function of phenomena under study.

Abstract: The Florida coast is one of the most species-rich ecosystems in the world. This paper focuses on the sensitivity of the habitat of threatened and endangered shorebirds to sea level rise induced by climate change, and on the relationship of the habitat with the coastline evolution. We consider the resident Snowy Plover (Charadrius alexandrinus nivosus), and the migrant Piping Plover (Charadrius melodus) and Red Knot (Calidris canutus) along the Gulf Coast of Mexico in Florida. We analyze and model the coupled dynamics of habitat patches of these imperiled shorebirds and of the shoreline geomorphology dictated by land cover change with consideration of the coastal wetlands. The land cover is modeled from 2006 to 2100 as a function of the A1B sea level rise scenario rescaled to 2 m. Using a maximum-entropy habitat suitability model and a set of macroecological criteria we delineate breeding and wintering patches for each year simulated. Evidence of coupled ecogeomorphological dynamics was found by considering the fractal dimension of shorebird occurrence patterns and of the coastline. A scaling relationship between the fractal dimensions of the species patches and of the coastline was detected. The predicted power law of the patch size emerged from scale-free habitat patterns and was validated against 9 years of observations. We predict an overall 16% loss of the coastal landforms from inundation. Despite the changes in the coastline that cause habitat loss, fragmentation, and variations of patch connectivity, shorebirds self-organize by preserving a power-law distribution of the patch size in time. Yet, the probability of finding large patches is predicted to be smaller in 2100 than in 2006. The Piping Plover showed the highest fluctuation in the patch fractal dimension; thus, it is the species at greatest risk of decline. We propose a parsimonious modeling framework to capture macroscale ecogeomorphological patterns of coastal ecosystems. Our results suggest the potential use of the fractal dimension of a coastline as a fingerprint of climatic change effects on shoreline-dependent species. Thus, the fractal dimension is a potential metric to aid decision-makers in conservation interventions of species subjected to sea level rise or other anthropic stressors that affect their coastline habitat.

Abstract: Denitrification is a process of great environmental importance but is difficult to study in terrestrial ecosystems. Methods for quantifying the process are problematic, variability in activity is high, and temporal and spatial scaling challenges are extreme. Available methods are problematic for a variety of reasons; they change substrate concentrations, disturb the physical setting of the process, lack sensitivity or are prohibitively costly in time and expense. Most fundamentally, it is very difficult to quantify the dominant end-product (N2) of denitrification given its high background concentration in the atmosphere. Spatial and temporal variation in denitrification is high due to control of the process by multiple factors (oxygen, nitrate, carbon, pH, salinity, temperature etc.) that each vary in time and space. A particular challenge is that small areas (hotspots) and brief periods (hot moments) frequently account for a high percentage of N gas flux activity. These phenomena are challenging to account for in measurement, modeling and scaling efforts. The need for scaling is driven by the fact that there is a need for information on this microscale process at the ecosystem, landscape and regional scales where there are concerns about nitrogen effects on soil fertility, water quality and air quality. In this review, I outline the key challenges involved with denitrification and then describe specific opportunities for making progress on these challenges including advances in measurement methods, new conceptual approaches for addressing hotspot and hot moment dynamics, and new remote sensing and geographic information system–based scaling methods. Analysis of these opportunities suggests that we are poised to make great improvements in our understanding of terrestrial denitrification. These improvements will increase our basic science understanding of a complex biogeochemical process and our ability to manage widespread nitrogen pollution problems.

Abstract: Ground-nesting birds experience high levels of nest predation. However, birds can make selection decisions related to nest site location and characteristics that may result in physical, visual, and olfactory impediments to predators. We studied daily survival rate [DSR] of greater sage-grouse (Centrocercus urophasianus) from 2008 to 2010 in an area in Wyoming experiencing large-scale alterations to the landscape. We used generalized linear mixed models to model fixed and random effects, and a correlation within nesting attempts, individual birds, and years. Predation of the nest was the most common source of nest failure (84.7%) followed by direct predation of the female (13.6%). Generally, landscape variables at the nest site (≤ 30 m) were more influential on DSR of nests than features at larger spatial scales. Percentage of shrub canopy cover at the nest site (15-m scale) and distances to natural gas wells and mesic areas had a positive relationship with DSR of nests, whereas distance to roads had a negative relationship with DSR of nests. When added to the vegetation model, maximum wind speed on the day of nest failure and a 1-day lag in precipitation (i.e., precipitation the day before failure) improved model fit whereby both variables negatively influenced DSR of nests. Nest site characteristics that reduce visibility (i.e., shrub canopy cover) have the potential to reduce depredation, whereas anthropogenic (i.e., distance to wells) and mesic landscape features appear to facilitate depredation. Last, predators may be more efficient at locating nests under certain weather conditions (i.e., high winds and moisture).

Abstract: Evaluating the environmental impacts of climate change on water resources and biological components of the landscape is an integral part of hydrologic and ecological investigations, and the resultant land and resource management in the twenty-first century. Impacts of both climate and simulated hydrologic parameters on ecological processes are relevant at scales that reflect the heterogeneity and complexity of landscapes. At present, simulations of climate change available from global climate models [GCMs] require downscaling for hydrologic or ecological applications. Using statistically downscaled future climate projections developed using constructed analogues, a methodology was developed to further downscale the projections spatially using a gradient-inverse-distance-squared approach for application to hydrologic modeling at 270-m spatial resolution. This paper illustrates a methodology to downscale and bias-correct national GCMs to subkilometer scales that are applicable to fine-scale environmental processes. Four scenarios were chosen to bracket the range of future emissions put forth by the Intergovernmental Panel on Climate Change. Fine-scale applications of downscaled datasets of ecological and hydrologic correlations to variation in climate are illustrated. The methodology, which includes a sequence of rigorous analyses and calculations, is intended to reduce the addition of uncertainty to the climate data as a result of the downscaling while providing the fine-scale climate information necessary for ecological analyses. It results in new but consistent data sets for the US at 4 km, the southwest US at 270 m, and California at 90 m and illustrates the utility of fine-scale downscaling to analyses of ecological processes influenced by topographic complexity.

Abstract: Although fire as a critical ecological process shapes the Florida Everglades landscape, researchers lack landscape-based approach for fire management. The interactive effect of fire, nutrients, water depth, and invasive cattails (Typha spp.) on vegetation communities is of special concern for ecosystem restoration. In particular, questions concerning the effect of fire on nutrient release and, by extension, the potential thereof to stimulate sawgrass (Cladium jamaicense Crantz) re-growth and cattail expansion under varying hydrological conditions are of immediate relevance to ecologists and land managers who work to restore the Everglades. In late April of 1999, a 42,875 ha surface fire, including a 100 ha peat fire, burned the northern section of Water Conservation Area 3A (WCA-3A) in the Everglades. In this study, total phosphorus (TP) in soil, surface water, pore-water, and vegetation was sampled at non-burned, surface-burned and peat-burned areas within one and five months after the burn. Four years after the initial fire, field data were collected in a large scale survey to analyze how the 1999 fire affected cattail distribution in the altered landscape of high soil TP and cattail habitats. Existing GIS maps were utilized to select field sampling locations and to provide additional information for the analysis. The analyses showed that five months after the fire, sawgrass biomass re-growth was about 5 times higher in burned areas (611 ± 47 g/m2) than in non-burned areas (102 ± 18 g/m2). Sawgrass re-growth in water depths less than 30 cm was 4.9 ± 0.4 g/m2/day while sawgrass re-growth in water depths deeper than 60 cm decreased to 0.5 ± 0.3 g/m2/day. Cattail biomass re-growth in peat-burned areas was as high as 1,079 ± 38 g/m2. The data also showed that post-fire cattail expansion could be related to cattail stands existing before the fire. Furthermore, post-fire cattail appeared more significant expansion in the areas with soil TP above 900 mg/kg than in that with soil TP below 900 mg/kg. The data showed that fire within altered landscapes (e.g. high soil TP and/or cattail) of the Everglades could stimulate the re-growth and expansion of cattails, and post-fire re-growth of sawgrass could be severely impeded by deep water after a surface-burn. This research indicates that fire continues to be an effective ecological process for maintaining the Everglades; therefore, ecologists and land managers may have to reevaluate the future management of natural fire with regard to its dynamic relationship with high soil TP and cattail expansion in the altered Everglades landscape.

Abstract: The emergent wetland species Typha domingensis (cattail) is a native Florida Everglades monocotyledonous macrophyte. It has become invasive due to anthropogenic disturbances and is out-competing other vegetation in the region, especially in areas historically dominated by Cladium jamaicense (sawgrass). There is a need for a quantitative, deterministic model in order to accurately simulate the regional-scale cattail dynamics in the Everglades. The Regional Simulation Model (RSM), combined with the Transport and Reaction Simulation Engine (TARSE), was adapted to simulate ecology. This provides a framework for user-defineable equations and relationships and enables multiple theories with different levels of complexity to be tested simultaneously. Five models, or levels, of increasing complexity were used to simulate cattail dynamics across Water Conservation Area 2A (WCA2A), which is located just south of Lake Okeechobee, in Florida, USA. These levels of complexity were formulated to correspond with five hypotheses regarding the growth and spread of cattail. The first level of complexity assumed a logistic growth pattern to test whether cattail growth is density dependent. The second level of complexity built on the first and included a Habitat Suitability Index (HSI) factor influenced by water depth to test whether this might be an important factor for cattail expansion. The third level of complexity built on the second and included an HSI factor influenced by soil phosphorus concentration to test whether this is a contributing factor for cattail expansion. The fourth level of complexity built on the third and included an HSI factor influenced by (a level 1–simulated) sawgrass density to determine whether sawgrass density impacted the rate of cattail expansion. The fifth level of complexity built on the fourth and included a feedback mechanism whereby the cattail densities influenced the sawgrass densities to determine the impact of inter-species interactions on the cattail dynamics. All the simulation results from the different levels of complexity were compared to observed data for the years 1995 and 2003. Their performance was analyzed using a number of different statistics that each represent a different perspective on the ecological dynamics of the system. These statistics include box-plots, abundance-area curves, Moran’s I, and classified difference. The statistics were summarized using the Nash-Sutcliffe coefficient. The results from all of these comparisons indicate that the more complex level 4 and level 5 models were able to simulate the observed data with a reasonable degree of accuracy. A user-defineable, quantitative, deterministic modeling framework was introduced and tested against various hypotheses. It was determined that the more complex models (levels 4 and 5) were able to adequately simulate the observed patterns of cattail densities within the WCA2A region. These models require testing for uncertainty and sensitivity of their various parameters in order to better understand them but could eventually be used to provide insight for management decisions concerning the WCA2A region and the Everglades in general.