Spreaders, igniters, and burning shrubs: plant flammability explains novel fire dynamics in grass-invaded deserts.

Novel fire regimes are an important cause and consequence of global environmental change that involve interactions among biotic, climatic, and human components of ecosystems. Plant flammability is key to these interactions, yet few studies directly measure flammability or consider how multiple species with different flammabilities interact to produce novel fire regimes. Deserts of the southwestern United States are an ideal system for exploring how novel fire regimes can emerge when fire-promoting species invade ecosystems comprised of species that did not evolve with fire. In these deserts, exotic annual grasses provide fuel continuity across landscapes that did not historically burn. These fires often ignite a keystone desert shrub, the fire-intolerant creosote bush, Larrea tridentata (DC.) Coville. Ignition of Larrea is likely catalyzed by fuels produced by native plants that grow beneath the shrubs. We hypothesize that invasive and native species exhibit distinct flammability characteristics that in combination determine spatial patterns of fire spread and intensity. We measured flammability metrics of Larrea, two invasive grasses, Schismus arabicus and Bromus madritensis, and two native plants, the sub-shrub Ambrosia dumosa and the annual herb Amsinckia menziesii. Results of laboratory experiments show that the grasses carry fire quickly (1.32 cm/s), but burn for short duration (0.5 min) at low temperatures. In contrast, native plants spread fire slowly (0.12 cm/s), but burn up to eight times longer (4 min) and produced hotter fires. Additional experiments on the ignition requirements of Larrea suggest that native plants burn with sufficient temperature and duration to ignite dead Larrea branches (time to ignition, 2 min; temperature at ignition 692°C). Once burning, these dead branches ignite living branches in the upper portions of the shrub. Our study provides support for a conceptual model in which exotic grasses are "spreaders" of fire and native plants growing beneath shrubs are "igniters" of dead Larrea branches. Once burning, flames produced by dead branches engulf the entire shrub, resulting in locally intense fires without historical precedent in this system. We suggest that fire models and conservation-focused management could be improved by incorporating the distinct flammability characteristics and spatial distributions of spreaders, igniters, and keystone shrubs.

Assessing the impact of fire on the spatial distribution of Larrea tridentata in the Sonoran Desert, USA.

In southwestern American deserts, fire has been historically uncommon because of insufficient continuity of fuel for spreading. However, deserts have been invaded by exotic species that now connect the empty space between shrubs to carry fire. We hypothesized that fire would change the spatial distribution of surviving Larrea tridentata shrubs. We established two study plots, one each in a burned and unburned area, and recorded location and living status of all shrubs. We performed univariate and bivariate point pattern analyses to characterize the impact of fire on the overall distribution of shrubs. Additionally, we used a simple wildfire model to determine how close we could come to reconstructing the observed spatial pattern of living and dead shrubs. We found a hyper-dispersed pattern of shrubs at finer scales and a random pattern at broader scales for both the unburned plot and for the living and dead shrubs combined in the burned plot, the latter providing an approximation of the pre-burn distribution of shrubs. After fire, living shrubs showed a clustered pattern at scales >2.5 m, whereas dead shrubs were randomly distributed, indicating that fire caused a change in the spatial pattern of the surviving shrubs. The fire model was able to partially reconstruct the spatial pattern of Larrea, but created a more clustered distribution for both living and dead shrubs. Our study reinforces the key role of fire in altering landscapes that had not been habituated to fire, and suggests the existence of potential cascading effects across the entire plant community.

Current models broadly neglect specific needs of biodiversity conservation in protected areas under climate change.

BACKGROUND: Protected areas are the most common and important instrument for the conservation of biological diversity and are called for under the United Nations' Convention on Biological Diversity. Growing human population densities, intensified land-use, invasive species and increasing habitat fragmentation threaten ecosystems worldwide and protected areas are often the only refuge for endangered species. Climate change is posing an additional threat that may also impact ecosystems currently under protection. Therefore, it is of crucial importance to include the potential impact of climate change when designing future nature conservation strategies and implementing protected area management. This approach would go beyond reactive crisis management and, by necessity, would include anticipatory risk assessments. One avenue for doing so is being provided by simulation models that take advantage of the increase in computing capacity and performance that has occurred over the last two decades.Here we review the literature to determine the state-of-the-art in modeling terrestrial protected areas under climate change, with the aim of evaluating and detecting trends and gaps in the current approaches being employed, as well as to provide a useful overview and guidelines for future research. RESULTS: Most studies apply statistical, bioclimatic envelope models and focus primarily on plant species as compared to other taxa. Very few studies utilize a mechanistic, process-based approach and none examine biotic interactions like predation and competition. Important factors like land-use, habitat fragmentation, invasion and dispersal are rarely incorporated, restricting the informative value of the resulting predictions considerably. CONCLUSION: The general impression that emerges is that biodiversity conservation in protected areas could benefit from the application of modern modeling approaches to a greater extent than is currently reflected in the scientific literature. It is particularly true that existing models have been underutilized in testing different management options under climate change. Based on these findings we suggest a strategic framework for more effectively incorporating the impact of climate change in models exploring the effectiveness of protected areas.

Comparison of quantitative and molecular genetic variation of native vs. invasive populations of purple loosestrife (Lythrum salicaria L., Lythraceae).

Study of adaptive evolutionary changes in populations of invasive species can be advanced through the joint application of quantitative and population genetic methods. Using purple loosestrife as a model system, we investigated the relative roles of natural selection, genetic drift and gene flow in the invasive process by contrasting phenotypical and neutral genetic differentiation among native European and invasive North American populations (Q(ST) - F(ST) analysis). Our results indicate that invasive and native populations harbour comparable levels of amplified fragment length polymorphism variation, a pattern consistent with multiple independent introductions from a diverse European gene pool. However, it was observed that the genetic variation reduced during subsequent invasion, perhaps by founder effects and genetic drift. Comparison of genetically based quantitative trait differentiation (Q(ST)) with its expectation under neutrality (F(ST)) revealed no evidence of disruptive selection (Q(ST) > F(ST)) or stabilizing selection (Q(ST) < F(ST)). One exception was found for only one trait (the number of stems) showing significant sign of stabilizing selection across all populations. This suggests that there are difficulties in distinguishing the effects of nonadaptive population processes and natural selection. Multiple introductions of purple loosestrife may have created a genetic mixture from diverse source populations and increased population genetic diversity, but its link to the adaptive differentiation of invasive North American populations needs further research.

Phenotypic plasticity of native vs. invasive purple loosestrife: a two-state multivariate approach.

The differences in phenotypic plasticity between invasive (North American) and native (German) provenances of the invasive plant Lythrum salicaria (purple loosestrife) were examined using a multivariate reaction norm approach testing two important attributes of reaction norms described by multivariate vectors of phenotypic change: the magnitude and direction of mean trait differences between environments. Data were collected for six life history traits from native and invasive plants using a split-plot design with experimentally manipulated water and nutrient levels. We found significant differences between native and invasive plants in multivariate phenotypic plasticity for comparisons between low and high water treatments within low nutrient levels, between low and high nutrient levels within high water treatments, and for comparisons that included both a water and nutrient level change. The significant genotype x environment (G x E) effects support the argument that invasiveness of purple loosestrife is closely associated with the interaction of high levels of soil nutrient and flooding water regime. Our results indicate that native and invasive plants take different strategies for growth and reproduction; native plants flowered earlier and allocated more to flower production, while invasive plants exhibited an extended period of vegetative growth before flowering to increase height and allocation to clonal reproduction, which may contribute to increased fitness and invasiveness in subsequent years.

Finding the Missing Link between Landscape Structure and Population Dynamics: A Spatially Explicit Perspective.

We construct and explore a general modeling framework that allows for a systematic investigation of the impact of changes in landscape structure on population dynamics. The essential parts of the framework are a landscape generator with independent control over landscape composition and physiognomy, an individual-based spatially explicit population model that simulates population dynamics within heterogeneous landscapes, and scale-dependent landscape indices that depict the essential aspects of landscape that interact with dispersal and demographic processes. Landscape maps are represented by a grid of [Formula: see text] cells and consist of good-quality, poor-quality, or uninhabitable matrix habitat cells. The population model was shaped in accordance to the biology of European brown bears (Ursus arctos), and demographic parameters were adjusted to yield a source-sink configuration. Results obtained with the spatially explicit model do not confirm results of earlier nonspatial source-sink models where addition of sink habitat resulted in a decrease of total population size because of dilution of high-quality habitat. Our landscape indices, which describe scale-dependent correlation between and within habitat types, were able to explain variations in variables of population dynamics (mean number of females with sink home ranges, mean number of females with source home ranges, and mean dispersal distance) caused by different landscape structure. When landscape structure changed, changes in these variables generally followed the corresponding change of an appropriate landscape index in a linear way. Our general approach incorporates source-sink dynamics as well as metapopulation dynamics, and the population model can easily be modified for other species groups.

A generalized algorithm for determining category size.

A revision and extension of Vandermeer's algorithm for choosing size categories from demographic data is presented along with an example of its use. The extension permits an exact consideration of sample populations which may have different underlying transition probabilities at different census periods and/or within different subpopulations. Once categories are chosen transition matrices may be computed to investigate the dynamics of the population.