Per-Pixel Forest Attribute Mapping and Error Estimation: The Google Earth Engine and R dataDriven Tool.

Remote sensing products are typically assessed using a single accuracy estimate for the entire map, despite significant variations in accuracy across different map areas or classes. Estimating per-pixel uncertainty is a major challenge for enhancing the usability and potential of remote sensing products. This paper introduces the dataDriven open access tool, a novel statistical design-based approach that specifically addresses this issue by estimating per-pixel uncertainty through a bootstrap resampling procedure. Leveraging Sentinel-2 remote sensing data as auxiliary information, the capabilities of the Google Earth Engine cloud computing platform, and the R programming language, dataDriven can be applied in any world region and variables of interest. In this study, the dataDriven tool was tested in the Rincine forest estate study area-eastern Tuscany, Italy-focusing on volume density as the variable of interest. The average volume density was 0.042, corresponding to 420 m3 per hectare. The estimated pixel errors ranged between 93 m3 and 979 m3 per hectare and were 285 m3 per hectare on average. The ability to produce error estimates for each pixel in the map is a novel aspect in the context of the current advances in remote sensing and forest monitoring and assessment. It constitutes a significant support in forest management applications and also a powerful communication tool since it informs users about areas where map estimates are unreliable, at the same time highlighting the areas where the information provided via the map is more trustworthy. In light of this, the dataDriven tool aims to support researchers and practitioners in the spatially exhaustive use of remote sensing-derived products and map validation.

Design-based properties of the nearest neighbor spatial interpolator and its bootstrap mean squared error estimator.

Nearest neighbor spatial interpolation for mapping continuous populations and finite populations of areas or units is approached from a design-based perspective, that is, populations are fixed, and uncertainty stems from the sampling scheme adopted to select locations. We derive conditions for design-based pointwise and uniform consistency of the nearest neighbor interpolators. We prove that consistency holds under certain schemes that are widely applied in environmental and forest surveys. Furthermore, we propose a pseudopopulation bootstrap estimator of the root mean squared errors of the interpolated values. Finally, a simulation study is performed to assess the theoretical results.

Design-based mapping of tree attributes by 3P sampling.

The estimation of individual values (marks) in a finite population of units (e.g., trees) scattered onto a survey region is considered under 3P sampling. For each unit, the mark is estimated by means of an inverse distance weighting interpolator. Conditions ensuring the design-based consistency of maps are considered under 3P sampling. A computationally simple mean squared error estimator is adopted. Because 3P sampling involves the prediction of marks for each unit in the population, prediction errors rather than marks can be interpolated. Then, marks are estimated by the predictions plus the interpolated errors. If predictions are good, prediction errors are more smoothed than raw marks so that the procedure is likely to better meet consistency requirements. The purpose of this paper is to provide theoretical and empirical evidence on the effectiveness of the interpolation based on prediction errors to prove that the proposed strategy is a tool of general validity for mapping forest stands.

Assessment of seasonal variation of diet composition in rodents using DNA barcoding and Real-Time PCR.

The study of animal diet and feeding behaviour is a fundamental tool for the illustration of the ecological role of species in the ecosystem. However, size and quality of food intake samples make it hard for researchers to describe the diet composition of many small species. In our study, we exploited genomic tools for the analysis of the diet composition of the Savi's pine vole (Microtus savii) using DNA barcoding and qPCR techniques for the identification of ingested plant species retrieved from stomach contents. In contrast with previous studies, we found that, despite being a fossorial species, the Savi's pine vole is a selective feeder that undergoes intense superficial activity in search for food. In addition, our study shows that with a a priori knowledge of the candidate plant species included in animal diet, qPCR is a powerful tool to assess presence/absence, frequency of occurrence and electivity of ingested species. We conclude that this approach offers new opportunities to implement the analysis of food selection in small animals, thereby revealing a detailed picture of plant-animal interactions.

Integration of land use and land cover inventories for landscape management and planning in Italy.

There are both semantic and technical differences between land use (LU) and land cover (LC) measurements. In cartographic approaches, these differences are often neglected, giving rise to a hybrid classification. The aim of this paper is to provide a better understanding and characterization of the two classification schemes using a comparison that allows maximization of the informative power of both. The analysis was carried out in the Molise region (Central Italy) using sample information from the Italian Land Use Inventory (IUTI). The sampling points were classified with a visual interpretation of aerial photographs for both LU and LC in order to estimate surfaces and assess the changes that occurred between 2000 and 2012. The results underscore the polarization of land use and land cover changes resulting from the following: (a) recolonization of natural surfaces, (b) strong dynamisms between the LC classes in the natural and semi-natural domain and (c) urban sprawl on the lower hills and plains. Most of the observed transitions are attributable to decreases in croplands, natural grasslands and pastures, owing to agricultural abandonment. The results demonstrate that a comparison between LU and LC estimates and their changes provides an understanding of the causes of misalignment between the two criteria. Such information may be useful for planning policies in both natural and semi-natural contexts as well as in urban areas.

Patterns of spatial overlap in a monogamous large rodent, the crested porcupine.

The crested porcupine Hystrix cristata is a large rodent which pairs for life. We studied the space use of 17 female and 9 male radio-tracked porcupines in an evergreen coastal woodland ("macchia", EW) and in an agricultural estate (AE), with special reference to the use of cultivations. Home range sizes of male porcupines (4.72-323.40) ranged around 114ha (median) during the warm period (April-September) and 162ha during the cold one (October-March). Home ranges of females (2.48-323.40) were c. 91ha during the warm period and c. 143ha during the cold one. Habitat composition and selection changed from the cold to the warm months, with porcupines being present in agricultural areas especially in the latter. Home range overlap between members of the same pair varied from 57% to 97% (median, 75%). Habitat selection was analyzed at the second (within study area) and at the third (within home range) order of selection. Within study areas, porcupines avoided cultivations and selected habitats with dense vegetation, providing cover and food. Within home ranges, in the warm period, porcupines selected agricultural areas in EW, where this habitat represented a minor portion of the study site. In that season, the Mediterranean "macchia" is a poor source of food, forcing porcupines to travel long distances to reach feeding sites. No significant difference of habitat selection within home ranges was detected between members of the same pair. Cultivations may play a key-role for porcupine survival, especially in poor habitats, as they provide abundant food resources in the warm period.

Design-based treatment of unit nonresponse in environmental surveys using calibration weighting.

Unit nonresponse is often a problem in sample surveys. It arises when the values of the survey variable cannot be recorded for some sampled units. In this paper, the use of nonresponse calibration weighting to treat nonresponse is considered in a complete design-based framework. Nonresponse is viewed as a fixed characteristic of the units. The approach is suitable in environmental and forest surveys when sampled sites cannot be reached by field crews. Approximate expressions of design-based bias and variance of the calibration estimator are derived and design-based consistency is investigated. Choice of auxiliary variables to perform calibration is discussed. Sen-Yates-Grundy, Horvitz-Thompson, and jackknife estimators of the sampling variance are proposed. Analytical and Monte Carlo results demonstrate the validity of the procedure when the relationship between survey and auxiliary variables is similar in respondent and nonrespondent strata. An application to a forest survey performed in Northeastern Italy is considered.

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.

Extending large-scale forest inventories to assess urban forests.

Urban areas are continuously expanding today, extending their influence on an increasingly large proportion of woods and trees located in or nearby urban and urbanizing areas, the so-called urban forests. Although these forests have the potential for significantly improving the quality the urban environment and the well-being of the urban population, data to quantify the extent and characteristics of urban forests are still lacking or fragmentary on a large scale. In this regard, an expansion of the domain of multipurpose forest inventories like National Forest Inventories (NFIs) towards urban forests would be required. To this end, it would be convenient to exploit the same sampling scheme applied in NFIs to assess the basic features of urban forests. This paper considers approximately unbiased estimators of abundance and coverage of urban forests, together with estimators of the corresponding variances, which can be achieved from the first phase of most large-scale forest inventories. A simulation study is carried out in order to check the performance of the considered estimators under various situations involving the spatial distribution of the urban forests over the study area. An application is worked out on the data from the Italian NFI.