Plant Community Composition and Biomass in Gulf Coast Chenier Plain Marshes: Responses to Winter Burning and Structural Marsh Management

Many marshes in the Gulf Coast Chenier Plain, USA, are managed through a combination of fall or winter burning and structural marsh management (i.e., levees and water control structures; hereafter SMM). The goals of winter burning and SMM include improvement of waterfowl and furbearer habitat, maintenance of historic isohaline lines, and creation and maintenance of emergent wetlands. Although management practices are intended to influence the plant community, effects of these practices on primary productivity have not been investigated. Marsh processes, such as vertical accretion and nutrient cycles, which depend on primary productivity may be affected directly or indirectly by winter burning or SMM. We compared Chenier Plain plant community characteristics (species composition and above- and belowground biomass) in experimentally burned and unburned control plots within impounded and unimpounded marshes at 7 months (1996), 19 months (1997), and 31 months (1998) after burning. Burning and SMM did not affect number of plant species or species composition in our experiment. For all three years combined, burned plots had higher live above-ground biomass than did unburned plots. Total above-ground and dead above-ground biomasses were reduced in burned plots for two and three years, respectively, compared to those in unburned control plots. During all three years, belowground biomass was lower in impounded than in unimpounded marshes but did not differ between burn treatments. Our results clearly indicate that current marsh management practices influence marsh primary productivity and may impact other marsh processes, such as vertical accretion, that are dependent on organic matter accumulation and decay.     

METHOD TO IDENTIFY EFFECTWE RIPARIAN BUFFER WIDTHS FOR ATLANTIC SALMON HABITAT PROTECTION1

ABSTRACT: Successful restoration of declining anadromous species is dependent upon effective riparian buffer zone management. Natural resource managers, policy developers and local conservation groups require science‐based information concerning the width at which a given buffer will be effective for its stated purpose. This paper summarizes a method developed in 1999 to determine effective riparian buffer widths for Atlantic salmon habitat protection as part of the Atlantic Salmon Conservation Plan for Seven Maine Rivers. A major assumption of the method is that no two buffers are alike with respect to their effectiveness and that various buffer characteristics dictate the required width for a given level of effectiveness. The method uses a predictive model that generates suggested riparian buffer widths as a function of specific, measurable buffer characteristics (such as slope, soil characteristics, and plant community structure and density) that affect buffer function. The method utilizes a variable‐width, two‐zone approach and specifies land uses that are consistent with desired buffer function within the two zones.     

Tree species control rates of free-living nitrogen fixation in a tropical rain forest

Tropical rain forests represent some of the most diverse ecosystems on earth, yet mechanistic links between tree species identity and ecosystem function in these forests remains poorly understood. Here, using free-living nitrogen (N) fixation as a model, we explore the idea that interspecies variation in canopy nutrient concentrations may drive significant local-scale variation in biogeochemical processes. Biological N fixation is the largest "natural" source of newly available N to terrestrial ecosystems, and estimates suggest the highest such inputs occur in tropical ecosystems. While patterns of and controls over N fixation in these systems remain poorly known, the data we do have suggest that chemical differences among tree species canopies could affect free-living N fixation rates. In a diverse lowland rain forest in Costa Rica, we established a series of vertical, canopy-to-soil profiles for six common canopy tree species, and we measured free-living N fixation rates and multiple aspects of chemistry of live canopy leaves, senesced canopy leaves, bulk leaf litter, and soil for eight individuals of each tree species. Free-living N fixation rates varied significantly among tree species for all four components, and independent of species identity, rates of N fixation ranged by orders of magnitude along the vertical profile. Our data suggest that variations in phosphorus (P) concentration drove a significant fraction of the observed species-specific variation in free-living N fixation rates within each layer of the vertical profile. Furthermore, our data suggest significant links between canopy and forest floor nutrient concentrations; canopy P was correlated with bulk leaf litter P below individual tree crowns. Thus, canopy chemistry may affect a suite of ecosystem processes not only within the canopy itself, but at and beneath the forest floor as well.     

Incorporating anthropogenic variables into a species distribution model to map gypsy moth risk

This paper presents a novel methodology for multi-scale and multi-type spatial data integration in support of insect pest risk/vulnerability assessment in the contiguous United States. Probability of gypsy moth (Lymantria dispar L.) establishment is used as a case study. A neural network facilitates the integration of variables representing dynamic anthropogenic interaction and ecological characteristics. Neural network model (back-propagation network [BPN]) results are compared to logistic regression and multi-criteria evaluation via weighted linear combination, using the receiver operating characteristic area under the curve (AUC) and a simple threshold assessment. The BPN provided the most accurate infestation-forecast predictions producing an AUC of 0.93, followed by multi-criteria evaluation (AUC = 0.92) and logistic regression (AUC = 0.86) when independently validating using post model infestation data. Results suggest that BPN can provide valuable insight into factors contributing to introduction for invasive species whose propagation and establishment requirements are not fully understood. The integration of anthropogenic and ecological variables allowed production of an accurate risk model and provided insight into the impact of human activities.     

Controls over foliar N:P ratios in tropical rain forests

Correlations between foliar nutrient concentrations and soil nutrient availability have been found in multiple ecosystems. These relationships have led to the use of foliar nutrients as an index of nutrient status and to the prediction of broadscale patterns in ecosystem processes. More recently, a growing interest in ecological stoichiometry has fueled multiple analyses of foliar nitrogen:phosphorus (N:P) ratios within and across ecosystems. These studies have observed that N:P values are generally elevated in tropical forests when compared to higher latitude ecosystems, adding weight to a common belief that tropical forests are generally N rich and P poor. However, while these broad generalizations may have merit, their simplicity masks the enormous environmental heterogeneity that exists within the tropics; such variation includes large ranges in soil fertility and climate, as well as the highest plant species diversity of any biome. Here we present original data on foliar N and P concentrations from 150 mature canopy tree species in Costa Rica and Brazil, and combine those data with a comprehensive new literature synthesis to explore the major sources of variation in foliar N:P values within the tropics. We found no relationship between N:P ratios and either latitude or mean annual precipitation within the tropics alone. There is, however, evidence of seasonal controls; in our Costa Rica sites, foliar N:P values differed by 25% between wet and dry seasons. The N:P ratios do vary with soil P availability and/or soil order, but there is substantial overlap across coarse divisions in soil type, and perhaps the most striking feature of the data set is variation at the species level. Taken as a whole, our results imply that the dominant influence on foliar N:P ratios in the tropics is species variability and that, unlike marine systems and perhaps many other terrestrial biomes, the N:P stoichiometry of tropical forests is not well constrained. Thus any use of N:P ratios in the tropics to infer larger-scale ecosystem processes must comprehensively account for the diversity of any given site and recognize the broad range in nutrient requirements, even at the local scale.     

Displaced honey bees perform optimal scale-free search flights

Honey bees (Apis mellifera) are regularly faced with the task of navigating back to their hives from remote food sources. They have evolved several methods to do this, including compass-directed "vector" flights and the use of landmarks. If these hive-centered mechanisms are disrupted, bees revert to searching for the hive, but the nature and efficiency of their searching strategy have hitherto been unknown. We used harmonic radar to record the flight paths of honey bees that were searching for their hives. Our subsequent analysis of these paths revealed that they can be represented by a series of straight line segments that have a scale-free, Lévy distribution with an inverse-square-law tail. We show that these results, combined with the "no preferred direction" characteristic of the segments, demonstrate that the bees were flying an optimal search pattern. Lévy movements have already been identified in a number of other animals. Our results are the best reported example where the movements are mostly attributable to the adoption of an optimal, scale-free searching strategy.     

Determining association networks in social animals: choosing spatial–temporal criteria and sampling rates

Social Network Analysis has become an important methodological tool for advancing our understanding of human and animal group behaviour. However, researchers tend to rely on arbitrary distance and time measures when defining ‘contacts’ or ‘associations’ between individuals based on preliminary observation. Otherwise, criteria are chosen on the basis of the communication range of sensor devices (e.g. bluetooth communication ranges) or the sampling frequencies of collection devices (e.g. Global Positioning System devices). Thus, researchers lack an established protocol for determining both relevant association distances and minimum sampling rates required to accurately represent the network structure under investigation. In this paper, we demonstrate how researchers can use experimental and statistical methods to establish spatial and temporal association patterns and thus correctly characterise social networks in both time and space. To do this, we first perform a mixing experiment with Merino sheep (Ovis aries) and use a community detection algorithm that allows us to identify the spatial and temporal distance at which we can best identify clusters of previously familiar sheep. This turns out to be within 2–3 m of each other for at least 3 min. We then calculate the network graph entropy rate—a measure of ease of spreading of information (e.g. a disease) in a network—to determine the minimum sampling rate required to capture the variability observed in our sheep networks during distinct activity phases. Our results indicate the need for sampling intervals of less than a minute apart. The tools that we employ are versatile and could be applied to a wide range of species and social network datasets, thus allowing an increase in both the accuracy and efficiency of data collection when exploring spatial association patterns in gregarious species.