Remote sensing tracks daily radial wood growth of evergreen needleleaf trees

Abstract

Relationships between gross primary productivity (GPP) and the remotely sensed photochemical reflectance index (PRI) suggest that time series of foliar PRI may provide insight into climate change effects on carbon cycling. However, because a large fraction of carbon assimilated via GPP is quickly returned to the atmosphere via respiration, we ask a critical question—can PRI time series provide information about longer term gains in aboveground carbon stocks? Here we study the suitability of PRI time series to understand intra‐annual stem‐growth dynamics at one of the world's largest terrestrial carbon pools—the boreal forest. We hypothesized that PRI time series can be used to determine the onset (hypothesis 1) and cessation (hypothesis 2) of radial growth and enable tracking of intra‐annual tree growth dynamics (hypothesis 3). Tree‐level measurements were collected in 2018 and 2019 to link highly temporally resolved PRI observations unambiguously with information on daily radial tree growth collected via point dendrometers. We show that the seasonal onset of photosynthetic activity as determined by PRI time series was significantly earlier (p < .05) than the onset of radial tree growth determined from the point dendrometer time series which does not support our first hypothesis. In contrast, seasonal decline of photosynthetic activity and cessation of radial tree growth was not significantly different (p > .05) when derived from PRI and dendrometer time series, respectively, supporting our second hypothesis. Mixed‐effects modeling results supported our third hypothesis by showing that the PRI was a statistically significant (p < .0001) predictor of intra‐annual radial tree growth dynamics, and tracked these daily radial tree‐growth dynamics in remarkable detail with conditional and marginal coefficients of determination of 0.48 and 0.96 (for 2018) and 0.43 and 0.98 (for 2019), respectively. Our findings suggest that PRI could provide novel insights into nuances of carbon cycling dynamics by alleviating important uncertainties associated with intra‐annual vegetation response to climate change.

Why trees grow at night

“…Meanwhile, the zero‐growth approach has become widely accepted and applied (Dietrich & Kahmen, 2019 ; Schafer et␣al ., 2019 ; Eitel et␣al ., 2020 ; Güney et␣al ., 2020 ; Lamacque et␣al ., 2020 ; Pappas et␣al ., 2020 ; Sellier & Segura, 2020 ). Accordingly, growth is defined as the radial stem increase above a previously reached stem radial maximum (Fig.…”

High Leaf Respiration Rates May Limit the Success of White Spruce Saplings growing in The Kampfzone at the Arctic Treeline

“…Considered to be one of the hardiest coniferous species, white spruce has a suite of structural and functional traits that may help explain its persistence in the harsh FTE environment where tree growth can be limited by low winter temperatures, short growing seasons, extreme light environments and often limiting rooting volumes due to the occurrence of permafrost. These potentially adaptive traits include strong apical dominance (Nienstaedt & Zasada, 1990), prolific seed production beginning at an early age (Sutton, 1969), xylem morphology capable of desiccation tolerance (Pampuch et al, 2020), strong photoperiodicity of growth (Eitel et al, 2019), early rehydration and initiation of growth despite experiencing extremely cold winters (Eitel et al, 2020) and rapid photoprotection mechanisms (Maguire et al, 2020), among many others. The physiology of white spruce is less well characterized, but studies of both photosynthesis and respiration (e.g., Weger & Guy, 1991a;Man & Lieffers, 1997;McNown & Sullivan, 2013;Stinziano & Way, 2017;Benomar et al, 2018;Prud'homme et al, 2018) indicate the physiology of leaf carbon balance in white spruce is under strong environmental control that could contribute to the establishment and persistence of the FTE.…”

Modelling the productivity of Siberian larch forests from Landsat NDVI time series in fragmented forest stands of the Mongolian forest-steppe

“…By contrast, remote sensing data are able to monitor and quantify ecological parameters that affect plant productivity over large areas. The basic concept relies on the establishment of relations between the absorbed and reflected solar radiation in the visible and near infrared (VNIR) spectrum and the specific index of plant productivity in question, such as tree ring increment (Eitel et al, 2020). The vast majority of such studies use regression analyses to parameterize the relationship between the target variable and the remote sensing observations (Lu et al, 2015;Powell et al, 2010;Rodríguez-Veiga et al, 2019).…”