Implications of climate variability for the detection of multiple equilibria and for rapid transitions in the atmosphere-vegetation system

Paleoclimatic records indicate a decline of vegetation cover in the Western Sahara at the end of the African Humid Period (about 5,500 years before present). Modelling studies have shown that this phenomenon may be interpreted as a critical transition that results from a bifurcation in the atmosphere-vegetation system. However, the stability properties of this system are closely linked to climate variability and depend on the climate model and the methods of analysis. By coupling the Planet Simulator (PlaSim), an atmosphere model of intermediate complexity, with the simple dynamic vegetation model VECODE, we assess previous methods for the detection of multiple equilibria, and demonstrate their limitations. In particular, a stability diagram can yield misleading results because of spatial interactions, and the system's steady state and its dependency on initial conditions are affected by atmospheric variability and nonlinearities. In addition, we analyse the implications of climate variability for the abruptness of a vegetation decline. We find that a vegetation collapse can happen at different locations at different times. These collapses are possible despite large and uncorrelated climate variability. Because of the nonlinear relation between vegetation dynamics and precipitation the green state is initially stabilised by the high variability. When precipitation falls below a critical threshold, the desert state is stabilised as variability is then also decreased. © 2011 The Author(s)

Spatio-temporal stochastic resonance induces patterns in wetland vegetation dynamics

Water availability is a major environmental driver affecting riparian and wetland vegetation. The interaction between water table fluctuations and vegetation in a stochastic environment contributes to the complexity of the dynamics of these ecosystems. We investigate the possible emergence of spatial patterns induced by spatio-temporal stochastic resonance in a simple model of groundwater-dependent ecosystems. These spatio-temporal dynamics are driven by the combined effect of three components: (i) an additive white Gaussian noise, accounting for external random disturbances such as fires or fluctuations in rain water availability, (ii) a weak periodic modulation in time, describing hydrological drivers such as seasonal fluctuations of water table depth, and (iii) a spatial coupling term, which takes into account the ability of vegetation to spread and colonize other parts of the landscape. A suitable cooperation between these three terms is able to give rise to ordered structures which show spatial and temporal coherence, and are statistically steady in time.Comment: 9 pages, 7 figure

The importance of canopy complexity in shaping seasonal spider and beetle assemblages in saltmarsh habitats

1. Habitat structure, including vegetation structural complexity, largely determines invertebrate assemblages in semi-natural grasslands. The importance of structural complexity to the saltmarsh invertebrate community, where the interplay between vegetation characteristics and tidal inundation is key, is less well known. 2. It was hypothesised that canopy complexity would be a more important predictor of spider and beetle assemblages than simple vegetation attributes (e.g. height, community type) and environmental variables (e.g. elevation) alone, measured in two saltmarsh regions, south-east (Essex) and north-west (Morecambe Bay) U.K. Canopy complexity (number of non-vegetated ‘gaps’ in canopy ≥ 1 mm wide) was assessed using side-on photography. Over 1500 spiders and beetles were sampled via suction sampling, winter and summer combined. 3. In summer, saltmarshes with abundant spider and beetle populations were characterised by high scores for canopy complexity often associated with tussocky grass or shrub cover. Simple vegetation attributes (plant cover, height) accounted for 26% of variation in spider abundance and 14% in spider diversity, rising to 46% and 41%, respectively, with the addition of canopy complexity score. Overwintering spider assemblages were associated with elevation and vegetation biomass. Summer beetle abundance, in particular the predatory and zoophagous group, and diversity were best explained by elevation and plant species richness. 4. Summer canopy complexity was identified as a positive habitat feature for saltmarsh spider communities (ground-running hunters and sheet weavers) with significant ‘added value’ over more commonly measured attributes of vegetation structure

Application of AIS Technology to Forest Mapping

Concerns about environmental effects of large scale deforestation have prompted efforts to map forests over large areas using various remote sensing data and image processing techniques. Basic research on the spectral characteristics of forest vegetation are required to form a basis for development of new techniques, and for image interpretation. Examination of LANDSAT data and image processing algorithms over a portion of boreal forest have demonstrated the complexity of relations between the various expressions of forest canopies, environmental variability, and the relative capacities of different image processing algorithms to achieve high classification accuracies under these conditions. Airborne Imaging Spectrometer (AIS) data may in part provide the means to interpret the responses of standard data and techniques to the vegetation based on its relatively high spectral resolution

Extended patchy ecosystems may increase their total biomass through self-replication

Patches of vegetation consist of dense clusters of shrubs, grass, or trees, often found to be circular characteristic size, defined by the properties of the vegetation and terrain. Therefore, vegetation patches can be interpreted as localized structures. Previous findings have shown that such localized structures can self-replicate in a binary fashion, where a single vegetation patch elongates and divides into two new patches. Here, we extend these previous results by considering the more general case, where the plants interact non-locally, this extension adds an extra level of complexity and shrinks the gap between the model and real ecosystems, where it is known that the plant-to-plant competition through roots and above-ground facilitating interactions have non-local effects, i.e. they extend further away than the nearest neighbor distance. Through numerical simulations, we show that for a moderate level of aridity, a transition from a single patch to periodic pattern occurs. Moreover, for large values of the hydric stress, we predict an opposing route to the formation of periodic patterns, where a homogeneous cover of vegetation may decay to spot-like patterns. The evolution of the biomass of vegetation patches can be used as an indicator of the state of an ecosystem, this allows to distinguish if a system is in a self-replicating or decaying dynamics. In an attempt to relate the theoretical predictions to real ecosystems, we analyze landscapes in Zambia and Mozambique, where vegetation forms patches of tens of meters in diameter. We show that the properties of the patches together with their spatial distributions are consistent with the self-organization hypothesis. We argue that the characteristics of the observed landscapes may be a consequence of patch self-replication, however, detailed field and temporal data is fundamental to assess the real state of the ecosystems.Comment: 38 pages, 12 figures, 1 tabl

Reflectance Modeling

The overall goal of this work has been to develop a set of computational tools and media abstractions for the terrain bidirectional reflectance problem. The modeling of soil and vegetation surfaces has been emphasized with a gradual increase in the complexity of the media geometries treated. Pragmatic problems involved in the combined modeling of soil, vegetation, and atmospheric effects have been of interest and one of the objectives has been to describe the canopy reflectance problem in a classical radiative transfer sense permitting easier inclusion of our work by other workers in the radiative transfer field

Complex network statistics to the design of fire breaks for the control of fire spreading

A computational approach for identifying efficient fuel breaks partitions for the containment of fire incidents in forests is proposed. The approach is based on the complex networks statistics, namely the centrality measures and cellular automata modeling. The efficiency of various centrality statistics, such as betweenness, closeness, Bonacich and eigenvalue centrality to select fuel breaks partitions vs. the random-based distribution is demonstrated. Two examples of increasing complexity are considered: (a) an artificial forest of randomly distributed density of vegetation, and (b) a patch from the area of Vesuvio, National Park of Campania, Italy. Both cases assume flat terrain and single type of vegetation. Simulation results over an ensemble of lattice realizations and runs show that the proposed approach appears very promising as it produces statistically significant better outcomes when compared to the random distribution approach

Parameter sensitivity analysis for different complexity land surface models using multicriteria methods

A multicriteria algorithm, the MultiObjective Generalized Sensitivity Analysis (MOGSA), was used to investigate the parameter sensitivity of five different land surface models with increasing levels of complexity in the physical representation of the vegetation (BUCKET, CHASM, BATS 1, Noah, and BATS 2) at five different sites representing crop land/ pasture, grassland, rain forest, cropland, and semidesert areas. The methodology allows for the inclusion of parameter interaction and does not require assumptions of independence between parameters, while at the same time allowing for the ranking of several single-criterion and a global multicriteria sensitivity indices. The analysis required on the order of 50 thousand model runs. The results confirm that parameters with similar "physical meaning" across different model structures behave in different ways depending on the model and the locations. It is also shown that after a certain level an increase in model structure complexity does not necessarily lead to better parameter identifiability, i.e., higher sensitivity, and that a certain level of overparameterization is observed. For the case of the BATS 1 and BATS 2 models, with essentially the same model structure but a more sophisticated vegetation model, paradoxically, the effect on parameter sensitivity is mainly reflected in the sensitivity of the soil-related parameter. Copyright 2006 by the American Geophysical Union

Influence of tree species complexity on discrimination performance of vegetation indices

Performance of different vegetation indices (VIs) in combination with single- and multipleendmember (SEM and MEM) for discriminating Corsican and Scots pines with different ages and Broadleaves tree species is demonstrated by using an airborne hyperspectral data. The analysis is performed in three different complexity levels. The results show by increasing tree species complexity, overall accuracy significantly reduced. An overall accuracy up to 90% is obtained from the first category with the least complexity; however, it is reduced to 55% in the third category with the highest complexity. By employing MEM, performance of normalized difference vegetation index (NDVI) is increased by 10%

Simplifying understory complexity in oil palm plantations is associated with a reduction in the density of a cleptoparasitic spider, Argyrodes miniaceus (Araneae: Theridiidae), in host (Araneae: Nephilinae) webs.

Expansion of oil palm agriculture is currently one of the main drivers of habitat modification in Southeast Asia. Habitat modification can have significant effects on biodiversity, ecosystem function, and interactions between species by altering species abundances or the available resources in an ecosystem. Increasing complexity within modified habitats has the potential to maintain biodiversity and preserve species interactions. We investigated trophic interactions between Argyrodes miniaceus, a cleptoparasitic spider, and its Nephila spp. spider hosts in mature oil palm plantations in Sumatra, Indonesia. A. miniaceus co-occupy the webs of Nephila spp. females and survive by stealing prey items caught in the web. We examined the effects of experimentally manipulated understory vegetation complexity on the density and abundance of A. miniaceus in Nephila spp. webs. Experimental understory treatments included enhanced complexity, standard complexity, and reduced complexity understory vegetation, which had been established as part of the ongoing Biodiversity and Ecosystem Function in Tropical Agriculture (BEFTA) Project. A. miniaceus density ranged from 14.4 to 31.4 spiders per square meter of web, with significantly lower densities found in reduced vegetation complexity treatments compared with both enhanced and standard treatment plots. A. miniaceus abundance per plot was also significantly lower in reduced complexity than in standard and enhanced complexity plots. Synthesis and applications: Maintenance of understory vegetation complexity contributes to the preservation of spider host-cleptoparasite relationships in oil palm plantations. Understory structural complexity in these simplified agroecosystems therefore helps to support abundant spider populations, a functionally important taxon in agricultural landscapes. In addition, management for more structurally complex agricultural habitats can support more complex trophic interactions in tropical agroecosystems