Spatial heterogeneity and irreversible vegetation change in semi-arid grazing systems

Recent theoretical studies have shown that spatial redistribution of surface water may explain the occurrence of patterns of alternating vegetated and degraded patches in semiarid grasslands. These results implied, however, that spatial redistribution processes cannot explain the collapse of production on coarser scales observed in these systems. We present a spatially explicit vegetation model to investigate possible mechanisms explaining irreversible vegetation collapse on coarse spatial scales. The model results indicate that the dynamics of vegetation on coarse scales are determined by the interaction of two spatial feedback processes. Loss of plant cover in a certain area results in increased availability of water in remaining vegetated patches through run-on of surface water, promoting within-patch plant production. Hence, spatial redistribution of surface water creates negative feedback between reduced plant cover and increased plant growth in remaining vegetation. Reduced plant cover, however, results in focusing of herbivore grazing in the remaining vegetation. Hence, redistribution of herbivores creates positive feedback between reduced plant cover and increased losses due to grazing in remaining vegetated patches, leading to collapse of the entire vegetation. This may explain irreversible vegetation shifts in semiarid grasslands on coarse spatial scales

A morphometric analysis of vegetation patterns in dryland ecosystems

Vegetation in dryland ecosystems often forms remarkable spatial patterns. These range from regular bands of vegetation alternating with bare ground, to vegetated spots and labyrinths, to regular gaps of bare ground within an otherwise continuous expanse of vegetation. It has been suggested that spotted vegetation patterns could indicate that collapse into a bare ground state is imminent, and the morphology of spatial vegetation patterns, therefore, represents a potentially valuable source of information on the proximity of regime shifts in dryland ecosystems. In this paper, we have developed quantitative methods to characterize the morphology of spatial patterns in dryland vegetation. Our approach is based on algorithmic techniques that have been used to classify pollen grains on the basis of textural patterning, and involves constructing feature vectors to quantify the shapes formed by vegetation patterns. We have analysed images of patterned vegetation produced by a computational model and a small set of satellite images from South Kordofan (South Sudan), which illustrates that our methods are applicable to both simulated and real-world data. Our approach provides a means of quantifying patterns that are frequently described using qualitative terminology, and could be used to classify vegetation patterns in large-scale satellite surveys of dryland ecosystems

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)

Challenging the Scientific Foundations for an IUCN Red List of Ecosystems

The International Union for Conservation of Nature (IUCN) is currently discussing the development of a Red List of Ecosystems (RLE) that would mirror the categories and criteria used to assess the conservation status of species. The suggested scientific foundations for the RLE are being considered by IUCN for adoption as the backbone of the RLE. We identify conceptual and operational weaknesses in the draft RLE approach, the categories, and criteria.While species are relatively well-described units, there is no consistent means to classify ecosystems for assessing conservation status. The proposed RLE is framed mostly around certain features of ecosystems such as broad vegetation or habitat types, and do not consider major global change drivers such as climate change. We discuss technical difficulties with the proposed concept of ecosystem collapse and suggest it is not analogous to species extinction. We highlight the lack of scientific basis for the criteria and thresholds proposed by the RLE, and question the need to adopt the structure of the Red List of Species for an RLE. We suggest that the proposed RLE is open to ambiguous interpretations and uncertain outcomes, and that its practicality and benefit for conservation should be carefully evaluated before final approval

Effect of permafrost thaw on CO2 and CH4 exchange in a western Alaska peatland chronosequence

Permafrost soils store over half of global soil carbon (C), and northern frozen peatlands store about 10% of global permafrost C. With thaw, inundation of high latitude lowland peatlands typically increases the surface-atmosphere flux of methane (CH4), a potent greenhouse gas. To examine the effects of lowland permafrost thaw over millennial timescales, we measured carbon dioxide (CO2) and CH4 exchange along sites that constitute a ~1000 yr thaw chronosequence of thermokarst collapse bogs and adjacent fen locations at Innoko Flats Wildlife Refuge in western Alaska. Peak CH4 exchange in July (123 ± 71 mg CH4–C m−2 d−1) was observed in features that have been thawed for 30 to 70 (\u3c100) yr, where soils were warmer than at more recently thawed sites (14 to 21 yr; emitting 1.37 ± 0.67 mg CH4–C m−2 d−1 in July) and had shallower water tables than at older sites (200 to 1400 yr; emitting 6.55 ± 2.23 mg CH4–C m−2 d−1 in July). Carbon lost via CH4 efflux during the growing season at these intermediate age sites was 8% of uptake by net ecosystem exchange. Our results provide evidence that CH4 emissions following lowland permafrost thaw are enhanced over decadal time scales, but limited over millennia. Over larger spatial scales, adjacent fen systems may contribute sustained CH4 emission, CO2 uptake, and DOC export. We argue that over timescales of decades to centuries, thaw features in high-latitude lowland peatlands, particularly those developed on poorly drained mineral substrates, are a key locus of elevated CH4 emission to the atmosphere that must be considered for a complete understanding of high latitude CH4 dynamics

Intermediate coupling between aboveground and belowground biomass maximises the persistence of grasslands

Aboveground and belowground biomass compartments of vegetation fulfil different functions and they are coupled by complex interactions. These compartments exchange water, carbon and nutrients and the belowground biomass compartment has the capacity to buffer vegetation dynamics when aboveground biomass is removed by disturbances such as herbivory or fire. However, despite their importance, root-shoot interactions are often ignored in more heuristic vegetation models. Here, we present a simple two-compartment grassland model that couples aboveground and belowground biomass. In this model, the growth of belowground biomass is influenced by aboveground biomass and the growth of aboveground biomass is influenced by belowground biomass. We used the model to explore how the dynamics of a grassland ecosystem are influenced by fire and grazing. We show that the grassland system is most persistent at intermediate levels of aboveground-belowground coupling. In this situation, the system can sustain more extreme fire or grazing regimes than in the case of strong coupling. In contrast, the productivity of the system is maximised at high levels of coupling. Our analysis suggests that the yield of a grassland ecosystem is maximised when coupling is strong, however, the intensity of disturbance that can be sustained increases dramatically when coupling is intermediate. Hence, the model predicts that intermediate coupling should be selected for as it maximises the chances of persistence in disturbance driven ecosystems

FOUR YEARS OF UNMANNED AERIAL SYSTEM IMAGERY REVEALS VEGETATION CHANGE IN A SUB-ARCTIC MIRE DUE TO PERMAFROST THAW

Warming trends in sub-arctic regions have resulted in thawing of permafrost which in turn induces change in vegetation across peatlands both in areal extent and composition. Collapse of palsas (i.e. permafrost plateaus) has also been correlated with increases in methane (CH4) emission to the atmosphere. Vegetation change provides new microenvironments that promote CH4 production and emission, specifically through plant interactions and structure. By quantifying the changes in vegetation at the landscape scale, we will be able to scale the impact of thaw on CH4 emissions in these complex climate-sensitive northern ecosystems. We combine field-based measurements of vegetation composition and Unmanned Aerial Systems (UAS) high resolution (3 cm) imagery to characterize vegetation change in a sub-arctic mire. The objective of this study is to analyze how vegetation from Stordalen Mire, Abisko, Sweden, has changed over time in response to permafrost thaw. At Stordalen Mire, we flew a fixed-wing UAS in July of each of four years, 2014 through 2017, over a 1 km x 0.5 km area. High precision GPS ground control points were used to georeference the imagery. Randomized square-meter plots were measured for vegetation composition and individually classified into one of five vegetation cover types, each representing a different stage of permafrost degradation. Using these training data, each year of imagery was classified by cover type in Google Earth Engine using a Random Forest Classifier. Textural information was extracted from the imagery, which provided additional spatial context information and improved classification accuracy. Twenty five percent of the training data were held back from the classification and used for validation, while the remaining seventy five percent of the training data were used to classify the imagery. The overall classification accuracy for 2014-2017 was 80.6%, 79.1%, 82.0%, and 82.9%, respectively. Percent cover across the landscape was calculated from each classification map and compared between years. Hummock sites, representing intact permafrost, decreased coverage by 9% from 2014-2017, while semi-wet sites increased coverage by 18%. This four-year comparison of vegetation cover indicated a rapid response to permafrost thaw. The use of a UAS allowed us to effectively capture the spatial heterogeneity of a northern peatland ecosystem. Estimation of vegetation cover types is vital in our understanding of the evolution of northern peatlands and their future role in the global carbon cycle