The Relative Influences of Climate and Competition on Tree Growth along Montane Ecotones in the Rocky Mountains

Distribution shifts of tree species are likely to be highly dependent upon population performance at distribution edges. Understanding the drivers of aspects of performance, such as growth, at distribution edges is thus crucial to accurately predicting responses of tree species to climate change. Here, we use a Bayesian model and sensitivity analysis to partition the effects of climate and crowding, as a metric of competition, on radial growth of three dominant conifer species along montane ecotones in the Rocky Mountains. These ecotones represent upper and lower distribution edges of two species, and span the distribution interior of the third species. Our results indicate a greater influence of climate (i.e., temperature and precipitation) than crowding on radial growth. Competition importance appears to increase towards regions of more favorable growing conditions, and precise responses to crowding and climate vary across species. Overall, our results suggest that climate will likely be the most important determinant of changes in tree growth at distribution edges of these montane conifers in the future

Toward an Improved Conceptual Understanding of North American Tree Species Distributions

Species distributions have often been assumed to represent climatic limitations, yet recent evidence has challenged these assumptions and emphasized the potential importance of biotic interactions, dispersal limitation, and disturbance. Despite significant investigation into these factors, an integrated understanding of where and when they may be important is lacking. Here, we review evidence for the factors underlying the historical and contemporary distributions of North American tree species and argue that a cohesive conceptual framework must be informed by an understanding of species ecological and evolutionary history. We further demonstrate that available evidence offers little indication of a significant, independent influence of biotic interactions or dispersal limitation on species distributions. Disturbance may provide important constraints on distributions in limited contexts. Overall, historic and contemporary evidence suggests that species distributions are strongly influenced by climate, yet examples of disequilibrium with climate abound. We propose that differences among life stages and the impacts of human land use may contribute to explain these inconsistencies and are deserving of greater research attention

Do Community-Level Models Account for the Effects of Biotic Interactions? A Comparison of Community-Level and Species Distribution Modeling of Rocky Mountain Conifers

Community-level models (CLMs) aim to improve species distribution modeling (SDM) methods by attempting to explicitly incorporate the influences of interacting species. However, the ability of CLMs to appropriately account for biotic interactions is unclear. We applied CLM and SDM methods to predict the distributions of three dominant conifer tree species in the U.S. Rocky Mountains and compared CLM and SDM predictive accuracy as well as the ability of each approach to accurately reproduce species co-occurrence patterns. We specifically evaluated the performance of two statistical algorithms, MARS and CForest, within both CLM and SDM frameworks. Across all species, differences in SDM and CLM predictive accuracy were slight and can be attributed to differences in model structure rather than accounting for the effects of biotic interactions. In addition, CLMs generally over-predicted species cooccurrence, while SDMs under-predicted cooccurrence. Our results demonstrate no real improvement in the ability of CLMs to account for biotic interactions relative to SDMs. We conclude that alternative modeling approaches are needed in order to accurately account for the effects of biotic interactions on species distributions

Infiltration and short-term movement of nitrogen in a silt-loam soil typical of rice cultivation in Arkansas

Rice production in Arkansas is one of the top three crop commodities in terms of cash receipts. Researchers and farmers report that nitrogen (N) needs to be managed according to a variety of factors with two important ones being soil and fertilizer type. The objectives of this experiment were to determine: 1) the degree to which floodwater-incorporated N applied as urea or as ammonium sulfate infiltrates intact cores (7.2-cm dia., 10-cm depth) containing DeWitt siltloam soil, and 2) the distribution of N during 12 h of ponding. Inorganic-N concentrations were analyzed at 2-cm depth intervals in cores following removal of the flood. Nitrogen from applied fertilizer was recovered as ammonium. Ammonium sulfate-N remained in the top 4 cm of soil with concentrations of 375 µg N g-1 in the surface 2 cm and 300 µg N g-1 at the 2 - 4 cm depth after 12 hr of ponding. At all depth intervals below 4 cm, ammonium sulfate-N remained below 30 µg N g-1. In contrast, after 12 h of ponding, N in soil receiving urea was 105 µg N g-1 in the top 2 cm and 173 µg N g-1 at 2-4 cm. At 4-6, 6-8, and 8-10 cm, N was 109, 108, and 35 µg N g-1, respectively, after 12 h of ponding. These results demonstrate immediate and deeper movement of ammonium into silt loam soil receiving urea as compared to ammonium sulfate, demonstrating how the form of N in fertilizer affects its movement into the soil profile

Solutions Network Formulation Report. Using NASA Sensors to Perform Crop Type Assessment for Monitoring Insect Resistance in Corn

The EPA (U.S. Environmental Protection Agency) is tasked to monitor for insect pest resistance to transgenic crops. Several models have been developed to understand the resistance properties of insects. The Population Genetics Simulator model is used in the EPA PIRDSS (Pest Infestation and Resistance Decision Support System). The EPA Office of Pesticide Programs uses the DSS to help understand the potential for insect pest resistance development and the likelihood that insect pest resistance will negatively affect transgenic corn. Once the DSS identifies areas of concern, crews are deployed to collect insect pest samples, which are tested to identify whether they have developed resistance to the toxins in transgenic corn pesticides. In this candidate solution, VIIRS (Visible/Infrared Imager/Radiometer Suite) vegetation index products will be used to build hypertemporal layerstacks for crop type and phenology assessment. The current phenology attribute is determined by using the current time of year to index the expected growth stage of the crop. VIIRS might provide more accurate crop type assessment and also might give a better estimate on the crop growth stage

Stand Density and Age Affect Tree-level Structural and Functional Characteristics of Young, Postfire Lodgepole Pine in Yellowstone National Park

More frequent fire activity associated with climate warming is expected to increase the extent of young forest stands in fire-prone landscapes, yet growth rates and biomass allocation patterns in young forests that regenerated naturally following stand-replacing fire have not been well studied. We assessed the structural and functional characteristics of young, postfire lodgepole pine (Pinus contorta var. latifolia) trees across the Yellowstone subalpine plateaus to understand the influence of postfire stand density and age on tree-level aboveground biomass (AB), component biomass (bole, branch, foliage), partitioning to components, tree-level aboveground net primary productivity (ANPP) and leaf area (LA). Sixty 24- year-old lodgepole pine trees were harvested from 21 sites ranging from 500 to 74,667 stems-ha-1 for development of allometric equations to predict biomass, ANPP and LA. All traits increased nonlinearly with increasing tree basal diameter. Tree-level total AB and component biomass decreased with increasing stand density and increased with age when compared with measurements from 11-year-old trees. Bole partitioning increased with stand density, while foliage and branch wood partitioning declined. Tree-level ANPP and LA decreased significantly with stand density and age. Overall, our results indicate that stand density and age explain much of the variation in tree characteristics and that 24 years after fire, the initial postfire regeneration density is still exerting significant influence on the structure and function of individual trees