When is connectivity important? A case study of the spatial pattern of sudden oak death

Although connectivity has been examined from many different angles and in many ecological disciplines, few studies have tested in which systems and under what conditions connectivity is important in determining ecological dynamics. Identifying general rules governing when connectivity is important is crucial not only for basic ecology, but also for our ability to manage natural systems, particularly as increasing fragmentation may change the degree to which connectivity influences ecological dynamics. In this study, we used statistical regression, least‐cost path analysis, and model selection techniques to test the relative importance of potential connectivity in determining the spatial pattern of sudden oak death, a tree disease that is killing millions of oak and tanoak trees along coastal forests of California and Oregon. We hypothesized that potential connectivity, in addition to environmental conditions, is important in determining the spatial distribution of sudden oak death, the importance of connectivity is more apparent when measured using biologically meaningful metrics that account for the effects of landscape structure on disease spread, and the relative importance of environmental variables and connectivity is approximately equal. Results demonstrate that potential connectivity was important in determining the spatial pattern of sudden oak death, though it was relatively less important than environmental variables. Moreover, connectivity was important only when using biologically meaningful metrics as opposed to simple distance‐based metrics that ignore landscape structure. These results demonstrate that connectivity can be important in systems not typically considered in connectivity studies – highlighting the importance of examining connectivity in a variety of different systems – and demonstrate that the manner in which connectivity is measured may govern our ability to detect its importance.     

Landscape-scale patterns of shrub-species abundance in California chaparral – The role of topographically mediated resource gradients

We examine the degree to which landscape-scale spatial patterns of shrub-species abundance in California chaparral reflect topographically mediated environmental conditions, and evaluate whether these patterns correspond to known ecophysiological plant processes. Regression tree models are developed to predict spatial patterns in the abundance of 12 chaparral shrub and tree species in three watersheds of the Santa Ynez Mountains, California. The species response models are driven by five variables: average annual soil moisture, seasonal variability in soil moisture, average annual photosynthetically active radiation, maximum air temperature over the dry season (May–October), and substrate rockiness. The energy and moisture variables are derived by integrating high resolution (10 m) digital terrain data and daily climate observations with a process-based hydro-ecological model (RHESSys). Field-sampled data on species abundance are spatially integrated with the distributed environmental variables for developing and evaluating the species response models.The species considered are differentially distributed along topographically-mediated environmental gradients in ways that are consistent with known ecophysiological processes. Spatial patterns in shrub abundance are most strongly associated with annual soil moisture and solar radiation. Substrate rockiness is also closely associated with the establishment of certain species, such as Adenostoma fasciculatum and Arctostaphylos glauca. In general, species that depend on fire for seedling recruitment (e.g., Ceanothous megacarpus) occur at high abundance in xeric environments, whereas species that do not depend on fire (e.g., Heteromeles arbutifolia) occur at higher abundance in mesic environments. Model performance varies between species and is related to life history strategies for regeneration. The scale of our analysis may be less effective at capturing the processes that underlie the establishment of species that do not depend on fire for recruitment. Analysis of predication errors in relation to environmental conditions and the abundance of potentially competing species suggest factors not explicitly considered in the species response models.     

An approach to the biometeorology of decomposer organisms

A search for surrogate variables of weather's control over rate of decay by decomposer organisms has revealed that Actual Evapotranspiration (AE), a water budget term, correlates well (r = 0.976) with measured values of litter decomposition rate. Using data from many biomes of the earth, a curve-fit of AE with measured decomposition rate has been formulated. This curve-fit has been used to prepare a map which displays the geography of predicted decay rate for North America. The physical properties of the litter also controls decomposition rates. Work is in progress to refine the AE to decomposer relationship by considering the lignin content of decomposing litter. Preliminary results suggest that control of decomposition rates by lignin increases with AE so that in high AE environments small changes in lignin concentration result in large changes in litter decay rates. This relationship perhaps explains the great variability in decay rates reported in tropical ecosystems.     

Litter quality in a north European transect versus carbon storage potential

Newly shed foliar plant litter often has a decomposition rate of ca 0.1–0.2% day^–1, which decreases greatly with time and may reach 0.0001 to 0.00001% day^–1 or lower in litter material in the last stages of decay. The decrease in decomposability (substrate quality) varies among species and is complex, involving both direct chemical changes in the substrate itself and the succession in microorganisms able to compete for substrate with a given chemical composition. In late stages, the decomposition appears very little affected by climate, suggesting that climate change will have little effect on late-stages decomposition rates. Here, we apply a model for the late stages of litter decomposition to address the question of climate-change effects on soil-C storage. Decomposition of litter turning into soil organic matter (SOM) is determined by the degradation rate of lignin. In the last phases of decay, raised N concentrations have a rate-retarding effect on lignin degradation and thus on the decomposition of far-decomposed litter and litter in near-humus stages. The retardation of the decomposition rate in late stages may be so strong that decomposition reaches a limit value at which total mass losses virtually stop. At such a stage the remaining litter would be close to that of stabilized SOM. The estimated limit values for different species range from about 45 to 100% decomposition indicating that between 0 and 55% should either be stabilized or decompose extremely slowly. For no less than 106 long-term studies on litter decomposition, encompassing 21 litter types, limit values were significantly and negatively related to N concentration, meaning that the higher the N concentration in the newly shed litter (the lower the C/N ratio) the more litter was left when it reached its limit value. Trees growing under warmer and wetter climates (higher actual evapotranspiration, AET) tend to shed foliar litter more rich in N than those growing under colder and drier climates. A change in climate resulting in higher AET would thus mean that within species, e.g., Scots pine, a higher N level in the foliar litter may result. Further, within the boreal system deciduous species appear to have foliar litter richer in N than have conifers and within the conifers group, Norway spruce has needle litter more rich in N than, e.g., Scots pine. Thus, a change of species (e.g., by planting) from pine to spruce or from spruce to a deciduous species such as birch may result in a higher N level in the litter fall at a given site. In both cases the result would be a lower limit value for decomposition. The paper presents an hypothesis, largely based on available data that a change in climate of 4° higher annual average temperature and 40% higher precipitation in the Baltic basin would result in higher N levels in litter, lower decomposition and thus a considerable increase in humus accumulation.     

Maximum vehicle cabin temperatures under different meteorological conditions

A variety of studies have documented the dangerously high temperatures that may occur within the passenger compartment (cabin) of cars under clear sky conditions, even at relatively low ambient air temperatures. Our study, however, is the first to examine cabin temperatures under variable weather conditions. It uses a unique maximum vehicle cabin temperature dataset in conjunction with directly comparable ambient air temperature, solar radiation, and cloud cover data collected from April through August 2007 in Athens, GA. Maximum cabin temperatures, ranging from 41–76°C, varied considerably depending on the weather conditions and the time of year. Clear days had the highest cabin temperatures, with average values of 68°C in the summer and 61°C in the spring. Cloudy days in both the spring and summer were on average approximately 10°C cooler. Our findings indicate that even on cloudy days with lower ambient air temperatures, vehicle cabin temperatures may reach deadly levels. Additionally, two predictive models of maximum daily vehicle cabin temperatures were developed using commonly available meteorological data. One model uses maximum ambient air temperature and average daily solar radiation while the other uses cloud cover percentage as a surrogate for solar radiation. From these models, two maximum vehicle cabin temperature indices were developed to assess the level of danger. The models and indices may be useful for forecasting hazardous conditions, promoting public awareness, and to estimate past cabin temperatures for use in forensic analyses.     

Carbon sequestration rates in organic layers of boreal and temperate forest soils — Sweden as a case study

Aim The aim of this work was to estimate C sequestration rates in the organic matter layer in Swedish forests. Location The region encompassed the forested area (23 × 10⁶ ha) of Sweden ranging from about 55° N to 69° N. Methods We used the concept of limit values to estimate recalcitrant litter remains, and combined it with amount of litter fall. Four groups of tree species were identified (pine, spruce, birch and ‘other deciduous species’). Annual actual evapotranspiration (AET) was estimated for 5 × 5 km grids covering Sweden. For each grid, data of forested area and main species composition were available. The annual input of foliar litter into each grid was calculated using empirical relationships between AET and foliar litter fall in the four groups. Litter input was combined with average limit values for decomposition for the four groups of litter, based on empirical data. Finally, C sequestration rate was calculated using a constant factor of the C concentration in the litter decomposed to the limit value, thus forming soil organic matter (SOM). Results We obtained a value of 4.8 × 10⁶ metric tons of C annually sequestered in SOM in soils of mature forests in Sweden, with an average of 180 kg ha^?1 and a range from 40 to 410 kg ha^?1. Norway spruce forests accumulated annually an average of 200 kg C ha^?1. The pine and birch groups had an average of 150 kg ha^?1 and for the group of other deciduous trees, which is limited to south Sweden, the C sequestration was around 400 kg ha^?1. Conclusions There is a clear C sequestration gradient over Sweden with the highest C sequestration in the south‐west, mainly corresponding to the gradient in litter fall. The limit‐value method appears useful for scaling up to a regional level to describe the C sequestration in SOM. A development of the limit value approach in combination with process‐orientated dynamic models may have a predictive value.     

Impact of sudden oak death on tree mortality in the Big Sur ecoregion of California

The Big Sur ecoregion in coastal California is a botanically and ecologically diverse area that has recently experienced substantial mortality of oak (Quercus spp.) and tanoak (Lithocarpus densiflorus) trees due to the emerging forest disease sudden oak death, caused by the invasive pathogen Phytophthora ramorum. In response to the urgent need to examine environmental impacts and create management response strategies, we quantified the impact of P. ramorum invasion on tree mortality across the Big Sur ecoregion using high-resolution aircraft imagery and field data. Using the imagery, we mapped all detectable oak and tanoak trees possibly killed by P. ramorum infection within redwood-tanoak forests and mixed oak woodlands. To validate and improve our remote assessment, we quantified the number, size, and infection status of host trees in 77 field plots (0.25 ha). The field data showed that our remote assessment underestimated mortality due to the occurrence of dead trees in the forest understory. For each forest type, we developed regression models that adjusted our remote assessments of tree mortality in relation to field observations of mortality and local habitat variables. The models significantly improved remote assessment of oak mortality, but relationships were stronger for mixed oak woodlands (r ² = 0.77) than redwood-tanoak forests (r ² = 0.66). Using the field data, we also modeled the amount of dead tree basal area (m²) in relation to the density of mapped dead trees in mixed oak woodlands (r ² = 0.73) and redwood-tanoak forests (r ² = 0.54). Application of the regression models in a GIS estimated 235,678 standing dead trees in 2005 and 12,650 m² of tree basal area removed from the ecoregion, with 63% of mortality occurring in redwood-tanoak forests and 37% in mixed oak woodlands. Integration of the remote assessment with population estimates of host abundance, obtained from an independent network of 175 field plots (0.05 ha each), indicated similar prevalence of mortality in redwood-tanoak forests (20.0%) and mixed oak woodlands (20.5%) at this time. This is the first study to quantify a realistic number of dead trees impacted by P. ramorum over a defined ecological region. Ecosystem impacts of such widespread mortality will likely be significant.

Predicting Forest Microclimate in Heterogeneous Landscapes

Forest microclimate plays an integral role in ecosystem processes, yet a predictive understanding of its spatial and temporal variability in heterogeneous landscapes is largely lacking. In this study, we used regression kriging (RK) to analyze the degree to which physiographic versus ecological variables influence spatio-temporal variation in understory microclimate conditions. We monitored understory temperature in 200 forest plots within a 274 km² environmentally heterogeneous region in northern California (0.55 obs/km²). For each plot location, we measured four physiographic influences (elevation, coastal proximity, potential solar radiation, topographic wetness index) and three ecological drivers (forest patch size, proximity to forest edge, tree abundance). Temperature observations were aggregated to three time scales (hourly, daily, and monthly) to examine temporal variability in microclimate dynamics and its effect on spatial prediction. The obtained prediction models included both physiographic and vegetative effects, although the relative importance of individual effects varied greatly between the different models. Across time scales, elevation and coastal proximity had the most consistent physiographic effects on temperature, followed by the vegetative effects of forest patch size and distance to forest edge. RK captured significantly more landscape-scale variability in understory temperature than a regression-only approach with considerably better model performance at hourly and daily time scales than at a monthly scale. Using varied sampling density scenarios our results also suggest that predictive accuracy drops considerably at densities less than 0.34 obs/km². This research illustrates how geospatial and statistical modeling can be used to distinguish physiographic versus ecological effects on microclimate dynamics and elucidates the spatial and temporal scales that these processes operate.