The 2007 crisis and Greek wildfires: a multivariate analysis of suppression times.

Shifts in government priorities in response to the 2007 global recession have affected wildfire management and natural disaster funding arrangements, leading to a reduced effectiveness of fire suppression actions and increasing fire vulnerability. Our study investigates the role of local socioeconomic contexts on fire suppression effectiveness under economic expansion and recession in a Mediterranean region (Attica, Greece) strongly affected by 2007 crisis and displaying a persistently high density of peri-urban wildfires. Basic characteristics of wildfires (spatial distribution, intensity, and land use preferences) were investigated in the study area over two consecutive 8-year time intervals characterized by economic expansion (2000-2007) and recession (2008-2015). An integrated approach based on multivariate statistics and artificial neural networks was implemented to evaluate latent relationships between fire suppression time, wildfire characteristics, and socioeconomic dynamics. Controlling for wildfires' characteristics over the two time intervals, fire time length increased under crisis-mainly for small and medium-sized fires-possibly as an indirect response to reduced effectiveness of forest land management. Local contexts and political decisions influenced by economic downturns are relevant factors shaping wildfires' severity in the Mediterranean region. With recession, local contexts vulnerable to wildfires require more effective fire prevention measures, sustainable forest management, and regional planning.

Paths to Change: Bio-Economic Factors, Geographical Gradients and the Land-Use Structure of Italy.

This study introduces a bio-economic approach to evaluate the influence of local socioeconomic contexts on complex processes of landscape transformation (urbanization, withdrawal of farming with woodland creation and loss in crop mosaics) in a sustainable development perspective. Land-use and socioeconomic indicators (including shares of agriculture, industry and services in total product, per-worker value added, productivity by economic sector, distance from central cities, latitude and elevation) at the local district scale in Italy have been considered together in an exploratory approach based on multivariate statistics. The combined use of land-use and socioeconomic indicators was preferred to more traditional approaches based on single-variable analysis and allows identifying latent factors of landscape transformation at the local scale. Our approach sheds light in the intimate relationship between regional economic structures and land-use change in districts with varying socio-environmental attributes across Italy. Urban-rural divides, coastal-inland dichotomy and the elevation gradient were relevant factors shaping urbanization-driven landscape transformations at the country scale. Indicators of economic structure (and especially industrial production and per-worker productivity of industry and services) were also documented to influence greatly entity and direction of change in the use of land. Discontinuous and dispersed urbanization has been demonstrated to be spatially-decoupled from consolidated (continuous and compact) urbanization, expanding into undeveloped rural areas progressively far away from central cities and being spatially associated with forest land.

Consolidating new paradigms in large-scale monitoring and assessment of forest ecosystems.

Forests provide a wide range of ecosystem services from which people benefit, and upon which all life depends. However, any rational decision related to the maintenance and enhancement of the multiple functions provided by the forests needs to be based on objective, reliable information. As such, forest monitoring and assessment are rapidly evolving as new information needs arise or new techniques and tools become available. Global change issues and utilities from ecosystem management are distinctively to be considered, so that forest inventory and mapping are broadening their scope towards multipurpose resources surveys. Recent changes in forest management perspective have promoted the consideration of forests as complex adaptive systems, thereby highlighting the need to account that such approaches actually work: forest monitoring and assessment are then expected to address and fully incorporate this perspective at global scale, seeking to support planning and management decisions that are evidence-based. This contribution provides selected considerations on the above mentioned issues, in the form of a commented discussion with examples from the literature produced in the last decade.

Towards a sampling strategy for the assessment of forest condition at European level: combining country estimates.

A correct characterization of the status and trend of forest condition is essential to support reporting processes at national and international level. An international forest condition monitoring has been implemented in Europe since 1987 under the auspices of the International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests). The monitoring is based on harmonized methodologies, with individual countries being responsible for its implementation. Due to inconsistencies and problems in sampling design, however, the ICP Forests network is not able to produce reliable quantitative estimates of forest condition at European and sometimes at country level. This paper proposes (1) a set of requirements for status and change assessment and (2) a harmonized sampling strategy able to provide unbiased and consistent estimators of forest condition parameters and of their changes at both country and European level. Under the assumption that a common definition of forest holds among European countries, monitoring objectives, parameters of concern and accuracy indexes are stated. On the basis of fixed-area plot sampling performed independently in each country, an unbiased and consistent estimator of forest defoliation indexes is obtained at both country and European level, together with conservative estimators of their sampling variance and power in the detection of changes. The strategy adopts a probabilistic sampling scheme based on fixed-area plots selected by means of systematic or stratified schemes. Operative guidelines for its application are provided.

Assessment of forest net primary production through the elaboration of multisource ground and remote sensing data.

This paper builds on previous work by our research group which demonstrated the applicability of a parametric model, Modified C-Fix, for the monitoring of Mediterranean forests. Specifically, the model is capable of combining ground and remote sensing data to estimate forest gross primary production (GPP) on various spatial and temporal scales. Modified C-Fix is currently applied to all Italian forest areas using a previously produced data set of meteorological data and NDVI imagery descriptive of a ten-year period (1999-2008). The obtained GPP estimates are further elaborated to derive forest net primary production (NPP) averages for 20 Italian Regions. Such estimates, converted into current annual increment of standing volume (CAI) through the use of specific coefficients, are compared to the data of a recent national forest inventory (INFC). The results obtained indicate that the modelling approach tends to overestimate the ground CAI values for all forest types. The correction of a drawback in the current model implementation leads to reduce this overestimation to about 9% of the INFC increments. The possible origins of this overestimation are investigated by examining the results of previous studies and of older forest inventories. The implications of using different NPP estimation methods are finally discussed in view of assessing the forest carbon budget on a national basis.