Francesco Chianucci

Estimation of canopy attributes in beech forests using true colour digital images from a small fixed-wing UAV

Abstract Accurate estimates of forest canopy are essential for the characterization of forest ecosystems. Remotely-sensed techniques provide a unique way to obtain estimates over spatially extensive areas, but their application is limited by the spectral and temporal resolution available from these systems, which is often not suited to meet regional or local objectives. The use of unmanned aerial vehicles (UAV) as remote sensing platforms has recently gained increasing attention, but their applications in forestry are still at an experimental stage. In this study we described a methodology to obtain rapid and reliable estimates of forest canopy from a small UAV equipped with a commercial RGB camera. The red, green and blue digital numbers were converted to the green leaf algorithm (GLA) and to the CIE L*a*b* colour space to obtain estimates of canopy cover, foliage clumping and leaf area index (L) from aerial images. Canopy attributes were compared with in situ estimates obtained from two digital canopy photographic techniques (cover and fisheye photography). The method was tested in beech forests. UAV images accurately quantified canopy cover even in very dense stand conditions, despite a tendency to not detecting small within-crown gaps in aerial images, leading to a measurement of a quantity much closer to crown cover estimated from in situ cover photography. Estimates of L from UAV images significantly agreed with that obtained from fisheye images, but the accuracy of UAV estimates is influenced by the appropriate assumption of leaf angle distribution. We concluded that true colour UAV images can be effectively used to obtain rapid, cheap and meaningful estimates of forest canopy attributes at medium-large scales. UAV can combine the advantage of high resolution imagery with quick turnaround series, being therefore suitable for routine forest stand monitoring and real-time applications.

Estimation of foliage clumping from the LAI-2000 Plant Canopy Analyzer: effect of view caps

Key messageFoliage clumping can be estimated from logarithm averaging method in LAI-2000. The spatial scaling of clumping effects considered by the instrument is dependent on the sensor’s azimuthal view.AbstractAccurate estimates of foliage clumping index (Ω) are required to improve the retrieval of leaf area index (L) from optical instruments like LAI-2000/2200 Plant Canopy Analyzer (PCA) and digital hemispherical photography (DHP). The logarithm averaging method is often used to approximate L because clumping effects are considered at scales larger than the sensor’s field of view. However, the spatial scaling considered for logarithm averaging typically differs between PCA and DHP, resulting in different estimates of foliage clumping. Based on simulation, we demonstrated that applying restricting azimuth view caps (e.g., 45° or 10°) allows reliable estimation of Ω and more accurate estimation of L from PCA. Simulated Ω and L values were comparable to those measured using the PCA, DHP and litter traps. Linear averaging of the gap fractions across readings at a plot or site yields a concurrent estimate of effective leaf area index (Le), thus enabling the calculation of Le, L, and Ω from a single instrument fitted with view caps. Users need to be aware that the method they use for averaging gap fractions determines whether they are measuring Le or L, and PCA users need to be aware that they are applying increasingly large corrections for foliage clumping as they use more restrictive view caps, a fact that they can use to their advantage to improve estimates of L.

Mast seeding in deciduous forests of the northern Apennines (Italy) and its influence on wild boar population dynamics

ContextPulsed food resources may strongly affect the population dynamics of several consumer species, with consequences on the ecosystem. One of the most common pulsed resources is forest mast seeding.AimsWe analysed mast seeding in deciduous forests in a mountainous area of northern Apennines and its effect on population dynamics of wild boar (Sus scrofa L.).MethodsWe performed a quantitative, 20-year analysis on annual seed production in Turkey oak (Quercus cerris L.), beech (Fagus sylvatica L.) and chestnut (Castanea sativa Mill.) forest stands using litter traps. The wild boar population density was estimated by means of drive censuses and hunting bag records. The role of other biotic (density of predators) and abiotic (climate) factors potentially affecting wild boar mortality was also investigated.ResultsTurkey oak and chestnut showed high levels of seed production, whereas lower levels were found in beech. The pulsed resources of chestnut and Turkey oak positively affected piglet density. Analyses also highlighted the influence of snow cover and wolves on wild boar population dynamics.ConclusionWild boar can be considered a pulse rate species, the management of which can be improved by annual monitoring of seed production.

Photographic assessment of overstory and understory leaf area index in beech forests under different management regimes in Central Italy

Abstract. Forest understory may be strongly affected by silvicultural practices such as thinning, which simultaneously modulates the overstory canopy cover and influences the availability of light. However, the understory layer is rarely considered in management decisions, partly because methods to estimate understory leaf area index are poorly developed. In this study we used two different restricted view angle photographic methods to estimate overstory plant area index LO (zenith cover photography), understory leaf area index LU (nadir cover photography) and their related canopy attributes (foliage clumping, foliage cover, crown cover, crown porosity). These measurements were performed in beech stands under different management regime. Results from photography indicated that not only overstory but also understory canopy attributes were significantly influenced by forest management. In addition, a significant negative correlation was found between LO and LU. We conclude that the photographic methods are effective for monitoring (overstory and understory) canopy status in managed stands, on account of their rapid and not destructive procedures, which allows large scale implementation of the methods.

A Multidimensional statistical framework to explore seasonal profile, severity and land-use preferences of wildfires in a Mediterranean country

SUMMARY This study analyses spatio-temporal patterns of wildfires in Greece using a multidimensional statistical framework based on non-parametric correlations, principal component analysis, clustering and stepwise discriminant analysis. Specifically, we assess the frequency, seasonal profile, severity and land-use type of 135 178 wildfires which occurred between 2000–2012 in Greece, one of the countries most affected by fire in Europe. Our results show that both the number of fires and the average size of the area covered by fire show a specific seasonal pattern with a marked increase during the dry season. Principal component analysis identifies three dimensions linked with the main type of land-use affected by the fires: (i) medium and large fires primarily affected landscapes composed of forests, mixed woodlands/shrublands and croplands; (ii) small fires mainly affected fragmented landscapes, i.e. those with mosaics of different crops, market gardens and non-vegetated, abandoned or marginal areas; (iii) fires affecting wetlands and pastures occurred particularly in late summer and showing medium-low severity. Hierarchical clustering highlights similarities in spatio-temporal patterns between fire indicators (ignition date, burnt land cover classes, fire size, fire density). K-means clustering allows us to distinguish between low-severity fires occurring in the wet season from intense and frequent fires occurring in the dry season but with distinct land-use selectivity. The research reported here contributes insight into the complexity of wild fires in the Mediterranean region and supports the design of more effective fire prevention measures including sustainable forest management practices and careful regional planning to minimise risk factors.

An objective image analysis method for estimation of canopy attributes from digital cover photography

Key messageA method was proposed to remove the subjectivity of gap size analyses approaches implemented by default in cover photography. The method yielded robust and replicable measurements of forest canopy attributes.AbstractDigital cover photography (DCP) is an increasingly popular method to estimate canopy attributes of forest canopies. Compared with other canopy photographic methods, DCP is fast, simple, and less sensitive to image acquisition and processing. However, the image processing steps used by default in DCP have a large substantial subjective component, particularly regarding the separation of canopy gaps into large gaps and small gaps. In this study, we proposed an objective procedure to analyse DCP based on the statistical distribution of gaps occurring in any image. The new method was tested in 11 deciduous forest stands in central Italy, with different tree composition, stand density, and structure, which is representative of the natural variation of these forest types. Results indicated that the new method removed the subjectivity of manual and semi-automated gap size classifications performed so far in cover photography. A comparison with direct LAI measurements demonstrated that the new method outperformed the previous approaches and increased the precision of LAI estimates. Results have important implications in forestry, because the simplicity of the method allowed objective, reliable, and highly reproducible estimates of canopy attributes, which are largely suitable in forest monitoring, where measures are routinely repeated. In addition, the use of a restricted field of view enables implementation of this photographic method in many devices, including smartphones, downward-looking cameras, and unmanned aerial vehicles.

A spatio-temporal dataset of forest mensuration for the analysis of tree species structure and diversity in semi-natural mixed floodplain forests

Analyses of tree structure and diversity have traditionally employed non-spatial measures, due to the simplicity of such approach (e.g. Neumann and Starlinger 2001). However, over the last few decades, a large number of studies have been performed to quantify tree structure and diversity in a spatially explicit way (e.g. Aguirre et al. 2003; Pommerening 2002; Pommerening 2006; Hui and Pommerening 2014). Results from these studies have led to the safe conclusion that spatially explicit measures provide more information on biodiversity patterns in forests compared with non-spatial measures. At another level, functional diversity approach allows integrating ecosystem processes and diversity analyses (Laliberté and Legendre 2010). Recently, the functional diversity approach has been included in forestry studies (e.g. Hui and Pommerening 2014). Mixed forests are particularly interesting for diversity analyses, as high diversity can be expected in this forest type (BravoOviedo et al. 2014). Repeated spatio-temporal analysis in these forests may provide insight on natural stand development processes over time. However, because of cost and time constraints, very few studies have performed spatial-temporal analysis of forest stands dynamics (e.g. LeMay et al. 2009). In addition, most studies employed chronosequences rather than true time series (repeated measures on permanent plots), which may introduce some uncertainties in interpreting trends over time. Further, the majority of previous studies on spatial diversity has analysed tropical and sub-tropical forests (Wright 2002; Wiegand et al. 2007), while studies on temperate forests have been scarce (e.g. Hui and Pommerening 2014). Semi-natural Reserve of Bosco Fontana is one of the last remaining floodplain forests in the Northern Italy (Zapponi et al. 2014) and one of the most endangered ecosystems in Europe (Schlaghamersky 2000). The forest has been managed as coppice with standards until the 80s and then it was left to develop naturally. The high level of diversity and naturalness of the stands makes this forest an ideal site for studying structure and dynamics in mixed floodplain forests. The dataset presented here provide replicated, repeated measurements at single-tree level conducted in three ~ 1-ha permanent plots; all standing trees in these plots were mapped and inventoried in 1995, 2005, and 2016. These data can be used to perform temporal analysis of tree structure and diversity in this forest type enabling both non-spatial and spatially explicit measures to be employed. Most Jannatul Fardusi, Cristiano Castaldi, Francesco Chianucci, Piermaria Corona, Franco Mason, Emma Minari and Nicola Puletti contributed equally to this work.

Climate, tree masting and spatial behaviour in wild boar (Sus scrofa L.): insight from a long-term study

Key messageClimate factors affect seed biomass production which in turn influences autumn wild boar spatial behaviour. Adaptive management strategies require an understanding of both masting and its influence on the behaviour of pulsed resource consumers like wild boar.ContextPulsed resources ecosystem could be strongly affected by climate. Disantangling the role of climate on mast seeding allow to understand a seed consumer spatial behaviour to design proper wildlife and forest management strategies.AimsWe investigated the relationship between mast seeding and climatic variables and we evaluated the influence of mast seeding on wild boar home range dynamics.MethodsWe analysed mast seeding as seed biomass production of three broadleaf tree species (Fagus sylvatica L., Quercus cerris L., Castanea sativa Mill.) in the northern Apennines. Next, we explored which climatic variables affected tree masting patterns and finally we tested the effect of both climate and seed biomass production on wild boar home range size.ResultsSeed biomass production is partially regulated by climate; high precipitation in spring of the current year positively affects seed biomass production while summer precipitation of previous year has an opposite effect. Wild boar home range size is negatively correlated to seed biomass production, and the climate only partially contributes to determine wild boar spatial behaviour.ConclusionClimate factors influence mast seeding, and the negative correlation between wild boar home range and mast seeding should be taken into account for designing integrated, proactive hunting management.

Tree-oriented silviculture for growing valuable broadleaved tree species in Turkey oak coppices

Valuable broadleaved tree species can play an important role in mixed-forest management; in these forests, silviculture may play an important role in getting high value timber. This paper illustrates a tree-oriented silviculture approach with an application in a Turkey oak coppice stand in Central Italy. This silvicultural approach has been developed in the last decades in France, Germany, Switzerland. The rationale behind the tree-oriented approach is to select a number of target sporadic tree species with valuable timber and to support their growth through repeated thinning from above. We tested the effectiveness of this silviculture approach as an alternative to customary coppice management in Italy, which is traditionally focused on the dominant tree species and does not consider valuable broadleaved tree species. The two silviculture approaches (tree-oriented and customary coppicing) were compared through a financial evaluation of the economic convenience of the two alternatives in a Turkey oak coppice stand in Central Italy