Impacts of tropical selective logging on carbon storage and tree species richness: A meta-analysis

Abstract

a b s t r a c tOver 400 million hectares of tropical forest are currently designated as logging concessions. This practice is an important source of timber, but there are concerns about its long-term sustainability and impacts on biodiversity and carbon storage. However, logging impacts vary widely, making generalisation and, consequently, policy implementation, difficult. Recent syntheses of animal biodiversity have indicated that differences in logging intensity -the volume of wood removed ha À1 -might help to explain some of these disparities. In addition, it has widely been assumed that reduced impact logging (RIL) might minimise some of the negative effects of logging; though in practice, this has rarely been tested. To test the hypothesis that RIL reduces negative impacts of selective logging once intensity is controlled for, we used meta-analyses of selective logging impact studies, focusing specifically on (1) residual tree damage, (2) aboveground biomass and (3) tree species richness. Our results indicate that RIL appears to reduce residual tree damage when compared to conventional methods. However, changes in aboveground biomass were negatively related to logging intensity. Any effect of RIL, independent of logging intensity, was difficult to discern since it was carried out at relatively low intensities. Tree richness appeared to increase at low intensities but decreased at higher intensities and any effect of RIL was difficult to detect. Our results tentatively support the hypothesis that RIL reduces the negative impacts of logging on tree damage, but do not support suggestions that RIL reduces loss of aboveground biomass or tree species richness. However, this lack of support may be a result of the relative paucity of data on the topic. Based on our results, we suggest that better evidence is needed to assess the differences between the impacts of RIL and conventional logging. Studies that consider plot-level differences in logging intensity are required to fill this knowledge gap. In addition, there must be clarification of whether RIL is an inherently low intensity practice so that this can be factored into management.

Carbon recovery dynamics following disturbance by selective logging in Amazonian forests

“…Maps were obtained with the following steps: (i) spatially-explicit covariates are extracted at the resolution of 30 arc-second from: the pan-tropical carbon map of Avitabile et al for pre-disturbance aboveground carbon stocks (Avitabile et al, 2016); WorldClim (RRID:SCR_010244) (Hijmans et al, 2005) for annual precipitation and seasonality of precipitation, and the Harmonized World Soil database (Nachtergaele et al, 2008) for topsoil bulk density; (ii) disturbance intensity is set to 40% of pre-logging ACS loss, which is a common value for disturbance intensity after conventional logging in Amazonia (West et al, 2014; Blanc et al, 2009; Martin et al, 2015) , and the relative forest maturity $dacs$ is set to zero; (iii) parameters are drawn from their previously calibrated distribution; (iv) to simulate random effects, all five parameters ($\alpha$) are taken from their distribution $𝒩({\alpha }_0,{\sigma }_{\alpha }^2)$; (v) for every pixel, we estimate the five cumulative ACS changes ($cSg$, $cSl$, $cRr$,$cRg$,$cRl$) 10 years after the 40% ACS loss, given the parameters value and the pixel covariates values extracted from global rasters. Steps (iii) to (v) are repeated 200 times and summary statistics are calculated for every pixel.…”

“…We quantify the effect of pre-disturbance ecosystem characteristics [the site’s average pre-logging ACS ($acs0$) and the relative difference between each plot and $acs0$ as a proxy of forest maturity ($dacs$)], disturbance intensity [percentage of pre-logging ACS lost ($loss$)], and interactions with the environment [annual precipitation ($prec$), seasonality of precipitation ($seas$), and soil bulk density ($bd$)] (Figure 2) on the rates at which post-disturbance ACS changes converge to a theoretical steady state (as in Figure 1, see Materials and methods for more details). With global maps of ACS (Avitabile et al, 2016), climatic conditions (Hijmans et al, 2005) and soil bulk density (Nachtergaele et al, 2008), we up-scale our results to Amazonia (sensu lato) and elaborate predictive maps of potential ACS changes over 10 years under the hypothesis of a 40% ACS loss, which is a common disturbance intensity after conventional logging in Amazonia (Blanc et al, 2009; Martin et al, 2015; West et al, 2014). Summing these ACS changes over time gives the net post-disturbance rate of ACS accumulation.…”

The Study of Faustmann Formula Application in Sustainable Natural Forest Management in Indonesia

“…2. Kerusakan tergantung dari intensitas penebangan, namun tingkat kerusakan sama untuk semua jenis dan kelas diameter: = , dimana = (ℎ ) (misalnya da Silva, Piazza, Fantini & Vibrans (2018); Martin, Newton, Pfeifer, Khoo & Bullock (2015)). Seperti halnya model i, kerusakan tegakan tinggal sama untuk semua jenis dan kelas diameter namun proporsi kerusakan dipengaruhi oleh intensitas tebangan ℎ .…”

Perbandingan Model Kerusakan Tegakan Tinggal di Hutan Alam Dipterocarp Untuk Mendukung Mekanisme REDD Plus

“…Pendekatan model kerusakan tegakan tinggal telah dikembangkan di hutan tropis di dunia, antara lain: (1) kerusakan tetap dan independent terhadap jumlah pohon yang ditebang (Mendoza et al, 2000;Sasaki et al, 2012), (2) jumlah pohon yang ditebang akan mempengaruhi jumlah kerusakan yang terjadi (Sist et al, 2003;Martin et al, 2015), dan (3) matriks kerusakan tegakan tinggal (Boscolo and Vincent, 2000;Macpherson et al, 2010). Model kerusakan tegakan tinggal pertama berasumsi bahwa tingkat kerusakan tegakan yang terjadi bersifat tetap tidak tergantung pada jumlah pohon yang ditebang (Bertault and Sist, 1997;.…”