Selective logging is a major driver of rainforest degradation across the tropics. Two competing logging strategies are proposed to meet timber demands with the least impact on biodiversity: land sharing, which combines timber extraction with biodiversity protection across the concession; and land sparing, in which higher intensity logging is combined with the protection of intact primary forest reserves. We evaluate these strategies by comparing the abundances and species richness of birds, dung beetles and ants in Borneo, using a protocol that allows us to control for both timber yield and net profit across strategies. Within each taxonomic group, more species had higher abundances with land-sparing than land-sharing logging, and this translated into significantly higher species richness within land-sparing concessions. Our results are similar when focusing only on species found in primary forest and restricted in range to Sundaland, and they are independent of the scale of sampling. For each taxonomic group, land-sparing logging was the most promising strategy for maximizing the biological value of logging operations.
Abstract:We investigated the capabilities of a canopy height model (CHM) derived from aerial photographs using the Structure from Motion (SfM) approach to estimate aboveground biomass (AGB) in a tropical forest. Aerial photographs and airborne Light Detection and Ranging (LiDAR) data were simultaneously acquired under leaf-on canopy conditions. A 3D point cloud was generated from aerial photographs using the SfM approach and converted to a digital surface model (DSMP). We also created a DSM from airborne LiDAR data (DSML). From each of DSMP and DSML, we constructed digital terrain models (DTM), which are DTMP and DTML, respectively. We created four CHMs, which were calculated from (1) DSMP and DTMP (CHMPP); (2) DSMP and DTML (CHMPL); (3) DSML and DTMP (CHMLP); and (4) DSML and DTML (CHMLL). Then, we estimated AGB using these CHMs. The model using CHMLL yielded the highest accuracy in four CHMs (R 2 = 0.94) and was comparable to the model using CHMPL (R 2 = 0.93). The model using CHMPP yielded the lowest accuracy (R 2 = 0.79). In conclusion, AGB can be estimated from CHM derived from aerial photographs using the SfM approach in the tropics. However, to accurately estimate AGB, we need a more accurate DTM than the DTM derived from aerial photographs using the SfM approach.
Effects of logging on species composition in tropical rainforests are well known but may fail to reveal key changes in species interactions. We used nitrogen stable-isotope analysis of 73 species of understory birds to quantify trophic responses to repeated intensive logging of rainforest in northern Borneo and to test 4 hypotheses: logging has significant effects on trophic positions and trophic-niche widths of species, and the persistence of species in degraded forest is related to their trophic positions and trophic-niche widths in primary forest. Species fed from higher up the food chain and had narrower trophic-niche widths in degraded forest. Species with narrow trophic-niche widths in primary forest were less likely to persist after logging, a result that indicates a higher vulnerability of dietary specialists to local extinction following habitat disturbance. Persistence of species in degraded forest was not related to a species' trophic position. These results indicate changes in trophic organization that were not apparent from changes in species composition and highlight the importance of focusing on trophic flexibility over the prevailing emphasis on membership of static feeding guilds. Our results thus support the notion that alterations to trophic organization and interactions within tropical forests may be a pervasive and functionally important hidden effect of forest degradation.
Context Daily growth hormone (GH) injections can be burdensome for patients and carers. Somapacitan is a long-acting, reversible albumin-binding GH derivative in development for once-weekly administration in patients with growth hormone deficiency (GHD). Objective The objective of this study is to evaluate the efficacy, safety, and tolerability of once-weekly somapacitan vs once-daily GH. Design REAL 3 is a multicenter, randomized, controlled, double-blind (somapacitan doses), phase 2 study with a 26-week main and 26-week extension phase (NCT02616562). Setting This study took place at 29 sites in 11 countries. Patients Fifty-nine GH treatment-naive prepubertal children with GHD were randomly assigned; 58 completed the trial. Interventions Interventions comprised 3 somapacitan doses (0.04 [n = 16], 0.08 [n = 15], or 0.16 mg/kg/wk [n = 14]) and daily GH (0.034 mg/kg/d [n = 14]), administered subcutaneously. Main Outcome Measures The primary end point was height velocity (HV) at week 26. Secondary efficacy end points included HV SD score (SDS) and insulin-like growth factor-I (IGF-I) SDS. Results At week 26, mean (SD) annualized HV for the somapacitan groups was 8.0 (2.0), 10.9 (1.9), and 12.9 (3.5) cm/year, respectively, vs 11.4 (3.3) cm/year for daily GH; estimated treatment difference (somapacitan 0.16 mg/kg/week—daily GH): 1.7 [95% CI –0.2 to 3.6] cm/year. HV was sustained at week 52, and significantly greater with somapacitan 0.16 mg/kg/week vs daily GH. Mean (SD) change from baseline in HV SDS at week 52 was 4.72 (2.79), 6.14 (3.36), and 8.60 (3.15) for the somapacitan groups, respectively, vs 7.41 (4.08) for daily GH. Model-derived mean (SD) IGF-I SDS for the somapacitan groups was −1.62 (0.86), −1.09 (0.78), and 0.31 (1.06), respectively, vs −0.40 (1.50) observed for daily GH. Safety and tolerability were consistent with the profile of daily GH. Conclusions In children with GHD, once-weekly somapacitan 0.16 mg/kg/week provided the closest efficacy match with similar safety and tolerability to daily GH after 26 and 52 weeks of treatment. A short visual summary of our work is available (1).
Abstract:Here, we investigated the capabilities of a lightweight unmanned aerial vehicle (UAV) photogrammetric point cloud for estimating forest biophysical properties in managed temperate coniferous forests in Japan, and the importance of spectral information for the estimation. We estimated four biophysical properties: stand volume (V), Lorey's mean height (H L ), mean height (H A ), and max height (H M ). We developed three independent variable sets, which included a height variable, a spectral variable, and a combined height and spectral variable. The addition of a dominant tree type to the above data sets was also tested. The model including a height variable and dominant tree type was the best for all biophysical property estimations. The root-mean-square errors (RMSEs) for the best model for V, H L , H A , and H M , were 118.30, 1.13, 1.24, and 1.24, respectively. The model including a height variable alone yielded the second highest accuracy. The respective RMSEs were 131.74, 1.21, 1.31, and 1.32. The model including a spectral variable alone yielded much lower estimation accuracy than that including a height variable. Thus, a lightweight UAV photogrammetric point cloud could accurately estimate forest biophysical properties, and a spectral variable was not necessarily required for the estimation. The dominant tree type improved estimation accuracy.
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