Fine-scale spatial homogenization of microbial habitats: a multivariate index of headwater wetland complex condition.

With growing public awareness that wetlands are important to society, there are intensifying efforts to understand the ecological condition of those wetlands that remain, and to develop indicators of wetland condition. Indicators based on soils are not well developed and are absent in some current assessment protocols; these could be advantageous, particularly for soils, which are complex habitats for plants, invertebrates, and microbial communities. In this study, we examine whether multivariate soil indicators, correlated with microbial biomass and community composition, can be used to distinguish reference standard (i.e., high condition) headwater wetland complexes from impacted headwater wetland complexes in central Pennsylvania, USA. Our reference standard sites existed in forested landscapes, while our impacted sites were situated in multi-use landscapes and were affected by a range of land-use legacies in the 1900s. We found that current assessment protocols are likely underrepresenting sampling needs to accurately represent site mean soil properties. On average, more samples were required to represent soil property means in reference standard sites compared to impacted sites. Reference standard and impacted sites also had noticeably different types of microbial habitats for the two multivariate soil indices assessed, and impacted sites were more homogenized in terms of the fine-scale (i.e., 1 and 5 m) spatial variability of these indices. Our study shows promise for the use of multivariate soil indices as indicators of wetland condition and provides insights into the sample sizes and scales at which soil sampling should occur during assessments. Future work is needed to test the generalizability of these findings across wetland types and ecoregions and establish definitive links between structural changes in microbial habitats and changes in wetland soil functioning.

Grassland productivity in response to nutrient additions and herbivory is scale-dependent.

Vegetation response to nutrient addition can vary across space, yet studies that explicitly incorporate spatial pattern into experimental approaches are rare. To explore whether there are unique spatial scales (grains) at which grass response to nutrients and herbivory is best expressed, we imposed a large (∼3.75 ha) experiment in a South African coastal grassland ecosystem. In two of six 60 נ60 m grassland plots, we imposed a scaled sampling design in which fertilizer was added in replicated sub-plots (1 נ1 m, 2 נ2 m, and 4 נ4 m). The remaining plots either received no additions or were fertilized evenly across the entire area. Three of the six plots were fenced to exclude herbivory. We calculated empirical semivariograms for all plots one year following nutrient additions to determine whether the scale of grass response (biomass and nutrient concentrations) corresponded to the scale of the sub-plot additions and compared these results to reference plots (unfertilized or unscaled) and to plots with and without herbivory. We compared empirical semivariogram parameters to parameters from semivariograms derived from a set of simulated landscapes (neutral models). Empirical semivariograms showed spatial structure in plots that received multi-scaled nutrient additions, particularly at the 2 נ2 m grain. The level of biomass response was predicted by foliar P concentration and, to a lesser extent, N, with the treatment effect of herbivory having a minimal influence. Neutral models confirmed the length scale of the biomass response and indicated few differences due to herbivory. Overall, we conclude that interpretation of nutrient limitation in grasslands is dependent on the grain used to measure grass response and that herbivory had a secondary effect.

Population Dynamics and Flight Phenology Model of Codling Moth Differ between Commercial and Abandoned Apple Orchard Ecosystems.

Apple orchard management practices may affect development and phenology of arthropod pests, such as the codling moth (CM), Cydia pomonella (L.) (Lepidoptera: Tortricidae), which is a serious internal fruit-feeding pest of apples worldwide. Estimating population dynamics and accurately predicting the timing of CM development and phenology events (for instance, adult flight, and egg-hatch) allows growers to understand and control local populations of CM. Studies were conducted to compare the CM flight phenology in commercial and abandoned apple orchard ecosystems using a logistic function model based on degree-days accumulation. The flight models for these orchards were derived from the cumulative percent moth capture using two types of commercially available CM lure baited traps. Models from both types of orchards were also compared to another model known as PETE (prediction extension timing estimator) that was developed in 1970s to predict life cycle events for many fruit pests including CM across different fruit growing regions of the United States. We found that the flight phenology of CM was significantly different in commercial and abandoned orchards. CM male flight patterns for first and second generations as predicted by the constrained and unconstrained PCM (Pennsylvania Codling Moth) models in commercial and abandoned orchards were different than the flight patterns predicted by the currently used CM model (i.e., PETE model). In commercial orchards, during the first and second generations, the PCM unconstrained model predicted delays in moth emergence compared to current model. In addition, the flight patterns of females were different between commercial and abandoned orchards. Such differences in CM flight phenology between commercial and abandoned orchard ecosystems suggest potential impact of orchard environment and crop management practices on CM biology.

Abiotic and biotic controls on local spatial distribution and performance of Boechera stricta.

This study investigates the relative influence of biotic and abiotic factors on community dynamics using an integrated approach and highlights the influence of space on genotypic and phenotypic traits in plant community structure. We examined the relative influence of topography, environment, spatial distance, and intra- and interspecific interactions on spatial distribution and performance of Boechera stricta (rockcress), a close perennial relative of model plant Arabidopsis. First, using Bayesian kriging, we mapped the topography and environmental gradients and explored the spatial distribution of naturally occurring rockcress plants and two neighbors, Taraxacum officinale (dandelion) and Solidago missouriensis (goldenrod) found in close proximity within a typical diverse meadow community across topographic and environmental gradients. We then evaluated direct and indirect relationships among variables using Mantel path analysis and developed a network displaying abiotic and biotic interactions in this community. We found significant spatial autocorrelation among rockcress individuals, either because of common microhabitats as displayed by high density of individuals at lower elevation and high soil moisture area, or limited dispersal as shown by significant spatial autocorrelation of naturally occurring inbred lines, or a combination of both. Goldenrod and dandelion density around rockcress does not show any direct relationship with rockcress fecundity, possibly due to spatial segregation of resources. However, dandelion density around rockcress shows an indirect negative influence on rockcress fecundity via herbivory, indicating interspecific competition. Overall, we suggest that common microhabitat preference and limited dispersal are the main drivers for spatial distribution. However, intra-specific interactions and insect herbivory are the main drivers of rockcress performance in the meadow community.

Spatial distribution of tree species governs the spatio-temporal interaction of leaf area index and soil moisture across a forested landscape.

Quantifying coupled spatio-temporal dynamics of phenology and hydrology and understanding underlying processes is a fundamental challenge in ecohydrology. While variation in phenology and factors influencing it have attracted the attention of ecologists for a long time, the influence of biodiversity on coupled dynamics of phenology and hydrology across a landscape is largely untested. We measured leaf area index (L) and volumetric soil water content (θ) on a co-located spatial grid to characterize forest phenology and hydrology across a forested catchment in central Pennsylvania during 2010. We used hierarchical Bayesian modeling to quantify spatio-temporal patterns of L and θ. Our results suggest that the spatial distribution of tree species across the landscape created unique spatio-temporal patterns of L, which created patterns of water demand reflected in variable soil moisture across space and time. We found a lag of about 11 days between increase in L and decline in θ. Vegetation and soil moisture become increasingly homogenized and coupled from leaf-onset to maturity but heterogeneous and uncoupled from leaf maturity to senescence. Our results provide insight into spatio-temporal coupling between biodiversity and soil hydrology that is useful to enhance ecohydrological modeling in humid temperate forests.

Post-fire spatial patterns of soil nitrogen mineralization and microbial abundance.

Stand-replacing fires influence soil nitrogen availability and microbial community composition, which may in turn mediate post-fire successional dynamics and nutrient cycling. However, fires create patchiness at both local and landscape scales and do not result in consistent patterns of ecological dynamics. The objectives of this study were to (1) quantify the spatial structure of microbial communities in forest stands recently affected by stand-replacing fire and (2) determine whether microbial variables aid predictions of in situ net nitrogen mineralization rates in recently burned stands. The study was conducted in lodgepole pine (Pinus contorta var. latifolia) and Engelmann spruce/subalpine fir (Picea engelmannii/Abies lasiocarpa) forest stands that burned during summer 2000 in Greater Yellowstone (Wyoming, USA). Using a fully probabilistic spatial process model and Bayesian kriging, the spatial structure of microbial lipid abundance and fungi-to-bacteria ratios were found to be spatially structured within plots two years following fire (for most plots, autocorrelation range varied from 1.5 to 10.5 m). Congruence of spatial patterns among microbial variables, in situ net N mineralization, and cover variables was evident. Stepwise regression resulted in significant models of in situ net N mineralization and included variables describing fungal and bacterial abundance, although explained variance was low (R²<0.29). Unraveling complex spatial patterns of nutrient cycling and the biotic factors that regulate it remains challenging but is critical for explaining post-fire ecosystem function, especially in Greater Yellowstone, which is projected to experience increased fire frequencies by mid 21(st) Century.