In forest ecosystems, tree individuals modify the abundance and allocation of ecological resources such as water and light due to their spatial and seasonal biomass distribution [1
]. This is reflected by substantial small-scale variation in resource patterns and ecological functioning of forests [4
]. Thus, forests as parts of the biosphere interact on multiple scales with the hydro- and atmosphere. The partitioning of rainfall into interception loss, stemflow, free throughfall, and canopy throughfall depends on tree species, tree metrics, and vegetation patterns caused by clumping of leaves and the creation of canopy gaps [6
]. Transmission, absorption, and reflection of light radiation are largely modified by tree species-specific phenological rhythmic (e.g., foliated vs. leafless periods), as well as the morphologies of leaves and crowns, the angles of leaves and twigs, and by effects on the spatial arrangement of leaves [4
]. For both, the abundance and distribution of water and light, the biomass and area of leaves play pivotal roles and can be expressed for example as leaf area index (LAI), as relevant property of the biosphere.
The LAI is defined as the cumulative one-sided area of leaves per unit stand area and is expressed in m2
]. The same applies for the surface area of woody plant compartments, the woody area index (WAI) and the sum of LAI and WAI, the plant area index (PAI). The LAI affects the distribution and consumption of ecological resources in forest ecosystems and therefore is closely linked to hydrological and atmospherical processes related to the cycles of water-, energy-, and carbon, as well as gas fluxes at higher spatial scales. A variety of ecological processes in the forest and on the forest floor are linked to the resource input at a particular location, among them germination and germinant growth of trees [11
], water uptake by plants [5
], and organic matter decomposition with subsequent nutrient release by soil microorganisms [15
]. Despite ecological modelling today resolves to the tree or at least cohort (groups of similar trees) level, the small-scale variability of LAI and WAI are not explicitly considered. Research results were commonly reported at the spatial scale of groups of trees or forest stands [18
]. However, some studies indicated horizontal variability of LAI within the crown of single trees in orchards, olive- and nut plantations, as well as in forest ecosystems for juvenile alder and beech [9
] and strong spatial autocorrelations in point-scale LAI measurements with a range between ten and 15 m, which equals average crown dimensions [25
The application of indirect ground based optical methods such as LAI-2000-series (plant canopy analyzer), TRAC (Tracing Radiation and Architecture of Canopies), digital hemispherical photography, line quantum sensors, imaging instruments, and terrestrial laser scanning that aims to generate estimates of LAI for particular measurement points is partly restricted by the variability and complexity of canopy and stand structures in forests [8
]. In particular, in spatially heterogeneous stands with mixed tree species and variable age composition, currently applied methodologies for LAI determination do not provide reliable quantitative estimates on small-scale variability of leaf distribution and subsequent effects on distribution of throughfall water and light radiation.
In contrast to the complex physics of light and subsequent restrictions on applicability of ground-based light radiation measurements [14
], we hypothesize that small-scale (<1 m) measurements of water movement via throughfall in forests provide a reliable, causal and mathematical sound attempt to quantify LAI and WAI at the spatial scale of the respective crown section above the measurement point. In detail, we believe this is in particular the case for the causal relationship between interception loss, as expressed by the respective canopy storage capacity: SCcanopy
, and the respective intercepting crown biomass [31
]. In this context it is important to note that the specific wetting capacity (SWC
) of the single canopy compartment (e.g., leaves, bud, twig) is linearly related to the respective wetted surface area [34
]. The sum of all compartments at a given area results in the cumulative storage capacity (SC
As an alternative method for small-scale horizontal LAI quantification, we propose an attempt that is based on exact perpendicular measurements of throughfall below the canopy and the subsequent calculation of SCcanopy,
leaf storage capacity (SCleaf
), and twig storage capacity (SCtwig
). The general idea is based on previous work [31
], however, no attempts still exist for the specific application of fine-scale LAI quantification. The reasons for that are diverse and partly relate to the spatial scale of interest of the studies and the considered hydrological factors:
(1) At the level of the forest stand, the commonly applied calculation approach for the estimation of SCcanopy
is based on water balance approaches that integrate over larger spatial scales [6
] than required for small-scale LAI estimation.
(2) The tree species specific occurrence of stemflow or relative throughfall accumulation at dripping points affect throughfall patterns. Depending on tree species, bark properties, and branch angel; the amount and spatial patterns of lateral flow must be determined using direct or indirect measurement methods (e.g., stemflow or LIDAR observations). In such cases, the additional mathematical consideration of lateral flow is mandatory, but was not included in previous studies [35
(3) Many datasets suffer from the occurrence of strong wind, time dependent evaporation, and spatially variable rainfall events in the course of explicit measurement campaigns. These factors affect applicability of the LAI estimation approach in an unwanted manner.
The proposed approach relies on the methodological differentiation between SCleaf
obtained from throughfall data during foliated and leafless periods in order to separate interception of leaves and twigs. Based on the investigation and quantification of beech leaf mass and area [8
] the relationship between leaf area and SCleaf
can be established. Single tree leaf amount can be derived by inverse modelling [44
]. This method was established in seed dispersal research [46
] and can be used for spatially explicit modelling of single tree LAI based on SCleaf
This study presents an approach to (i) detect and (ii) quantify the variability of leaf distribution within single tree crowns of European beech (Fagus sylvatica L.). Both goals will be achieved by the investigation of the redistribution of gross precipitation by measurements of net precipitation at specific locations underneath beech tree crowns. The observations consider several rainfall events (n = 33) and include foliated and leafless phenological phases. As field-data originate from a mixed stand of European beech and Norway spruce (Picea abies (L.) Karst.), the approach was tested in a highly structured case situation. For European beech, (iii) single tree leaf masses, leaf amounts and leaf areas were predicted by using inverse modelling of litter dispersal based on spatially highly resoluted litter fall measurements. Leaf predictions were compared to associated measurements of SCleaf at the single-tree level (iv).
LAI is an essential structural property of plant canopies and is functionally related to fluxes of energy, water, carbon, and light in ecosystems [14
] and thus interacting with geo-, hydro-, and atmosphere. LAI is a key parameter of these interactions and is used in plant growth and radiative transfer models, coupling vegetation to the climate system. There is an increasing need for more accurate and traceable measurements among several spatial scales of investigation and modelling [107
]. Our results corroborate the approach of [38
] who determined SC
related to canopy biomass at forest stand and catchment level. With our approach we demonstrated that it is possible to detect small-scale LAI and SC
distribution within the canopy of a common European tree species in a complex, mixed forest based on throughfall measurements. Our approach is simple. It might be possible to use already existing datasets of throughfall in foliated and leafless periods to derive small-scale SCleaf
’s and LAI’s based on the presented approach. The prerequisite for this is a thorough throughfall data inspection and selection.
Forest canopies are generally heterogeneous as a consequence of natural (windfall, diseases, and site characteristics) and artificial factors caused e.g., by planting density and selective thinning during stand development. In order to account for this inherent heterogeneity, currently applied indirect methods for LAI estimation increase sample sizes accompanied with the proportional increase in expense [24
]. LAI estimations based on small-scale throughfall dynamics may offer an alternative and more flexible approach to better understand and detect sources of variability and to link it with ecosystem functioning.