Assessing Retrospective Fragility in Grasslands An Italian Case Study

Grasslands around the world have been and still are extensively studied as brittle but dynamic ecosystems hosting many uniquely adapted animals and plants. The Russian steppes, the American prairies, or the African savannas are examples of the results of and are threatened by the interactions at multiple spatial and temporal scales of climatic and pedological constraints, natural disturbance regimes (e.g., grazing and browsing by wild animals or frequent fires), and anthropogenic pressures like agricultural field's conversion or livestock overgrazing. In Central and Southern Europe, many mountain grasslands, both pastures and hay meadows, have been abandoned or left without management, mainly due to economic reasons and demographic changes in local human communities, triggering a phase transition toward shrublands and impairing the multipurpose management of agropastoral systems.

Fragility and resilience as retrospective properties of grassland-based systems have been investigated within a framework implementing the integration of fractal analysis together with procedures of satellite change detection in the northern part of the Italian Apennine mountain chain. Shifts in the boundary fractal dimension of real mapped grassland patches were used to reveal hierarchical size organization and to define boundaries for scale domains of spatial and shape patterns. Scale thresholds separate these domains, and represent relatively sharp transitions or critical locations where a shift occurs in the relative importance of slow or fast variables influencing processes and structures. All habitat patches pertaining to a particular scale domain can be deemed as multiple configurations of the same ecological phase, according to dominating processes which generate and maintain habitats. A time series of LANDSAT TM5 imageries from 1990 to 2000 helped to estimate grasslands fragility measured as the mean level of change occurred within each patch for each time step (four steps of approximately 3 years) as measured by the differences in values of the NDVI, a commonly used remote-sensed index for quantifying photosynthetic rates, vegetation status, and land-cover changes. Habitat resilience was operationally defined as the inverse of fragility and was expected to be lower for scale domains where change is most likely. Two types of different grasslands were evaluated, corresponding, roughly, to increasing elevation gradients and to decreasing human influence and control. The so-called 'lowland hay meadows' are rich mesophile grasslands in the lowland, hill-land and submontane ranges, regularly irrigated and manured, well-drained under direct human control. They often begin from seeding of leguminous grasses or mixed fodder, and later are regularly cut in time for cattle breeding in farms. Brachypodium grasslands are subalpine thermophile siliceous habitats, often on skeleton soils, not under direct human influence except sporadic grazing by cows and sheep at lower altitudes, with hard-to-browse carpet communities typical of higher elevations and of the summits.

Different fragility and resilience levels were found associated with diverse-scale domains of the two grassland habitats and could be related to different processes acting at different spatial scales, according to human management activities and land manipulation (Figure 2). Brachypodium grasslands showed two different scale domains (i.e., two well different groups of class patches separated by distinct complex patch geometry) with a higher short-term retrospective resilience at the upper- than at the lower-scale domain, which had smaller areas and more regular shapes. The higher-scale domain collects patches with higher mean elevation or of the summits, mainly influenced by broad-scale climatic processes, with certain internal regulation (mainly to drought), highly adaptive responses to opportunity, and with the highest retrospective resilience. The second domain groups patches at lower altitudes, influenced by occasional grazing and manuring or by episodic inputs such as rainfall, more sensitive to local geomorphological conditions, and prone to variability induced by successional processes, thus leading to a higher degree of fragility and lower levels of resilience. 'Lowland hay meadows', instead, in spite of three scale domains, presented much lower short-term retrospective resilience levels across scales with respect to other grasslands (Figure 3). This is a managed ecosystem under direct human control and change is most likely due to management practices; thereby, resilience is expected to be lowest

Arable lands

Beech forests

Natural grasslands

Arable lands

Beech forests

Natural grasslands

Figure 2 Example of a retrospective analysis of cross-scale interactions between climatic constraints and three different ecosystem types in Apulia region (southern Italy) as arable lands, beech forests, and natural dry grasslands. Monthly mean normalized difference vegetation index (NDVI) values derived by a moderate resolution imaging spectroradiometer (MODIS) images time series from 2001 to 2006 for each ecosystem type are showed (upper panel). NDVI is here applied as a remotely sensed index of photosynthetic activity, biomass production, and ecosystem dynamics. Monthly mean temperature and monthly total precipitation describe the higher-level slow variables' constraints on lower-level systems and partially determine the three ecosystems' dynamics (lower panel).

Figure 2 Example of a retrospective analysis of cross-scale interactions between climatic constraints and three different ecosystem types in Apulia region (southern Italy) as arable lands, beech forests, and natural dry grasslands. Monthly mean normalized difference vegetation index (NDVI) values derived by a moderate resolution imaging spectroradiometer (MODIS) images time series from 2001 to 2006 for each ecosystem type are showed (upper panel). NDVI is here applied as a remotely sensed index of photosynthetic activity, biomass production, and ecosystem dynamics. Monthly mean temperature and monthly total precipitation describe the higher-level slow variables' constraints on lower-level systems and partially determine the three ecosystems' dynamics (lower panel).

and fragility highest. As a productive system, they are characterized by predictable inputs and present some internal regulation mechanisms for external variability over certain scale ranges. Constraints were provided by cutting and manuring practices, forcing the system always through the same trajectory. Natural variability of structuring variables such as grazing has been reduced to stabilize hay production so that they tend to become more spatially uniform and less functionally diverse; thus they tend to be more sensitive to disturbances that otherwise could have been absorbed.

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