Managing sun bears in a changing tropical landscape

Aim

Across the tropics, large‐bodied mammal species are threatened by rapid and widespread forest habitat conversion by either commercial logging or agricultural expansion. How such species use these habitats is an important area of research for guiding their future management. The tropical forest‐dwelling sun bear, Helarctos malayanus, is the least known of the eight bear species. Consequently, the IUCN/SSC Bear Specialist Group ranks research on this species as a top priority. This study aims to investigate landscape variables that influence sun bear habitat use in forests under varying levels of degradation and protection.

Location

A 20,998 km² Sumatra forest landscape covering Kerinci Seblat National Park (KSNP), Batang Hari Protection Forest (BHPF) and neighbouring logging and agricultural concessions.

Methods

An occupancy‐based sampling technique using detection/non‐detection data with 10 landscape covariates was applied in six study areas that operated a total of 125 camera traps. The potential differences between habitat use (ψ) of sun bears were first modelled with broad‐scale covariates of study area, land‐use types and forest type. Sun bear habitat use was then investigated with the finer‐scale landscape features associated within these areas.

Results

From 10,935 trap nights, sun bears were recorded at altitudes ranging from 365 to 1791 m. At a broad‐scale, habitat use increased with protection status, being highest in KSNP (0.688 ± 0.092, ± SE) and BHPF (0.621 ± 0.110) compared to production (0.418 ± 0.121) and convertible (0.286 ± 0.122) forests. Within these areas, sun bears showed a preference for forest that was further from public roads and villages and at a lower elevation.

Main conclusions

The habitat suitability model identified several high‐quality habitat patches outside of the priority conservation areas for immediate protection. Consequently, conservation management strategies should emphasize the importance of high conservation value forests and prohibit further conversion of threatened lowland forests.

     

Satellite microwave detection of boreal forest recovery from the extreme 2004 wildfires in Alaska and Canada

The rate of vegetation recovery from boreal wildfire influences terrestrial carbon cycle processes and climate feedbacks by affecting the surface energy budget and land‐atmosphere carbon exchange. Previous forest recovery assessments using satellite optical‐infrared normalized difference vegetation index (NDVI) and tower CO₂ eddy covariance techniques indicate rapid vegetation recovery within 5–10 years, but these techniques are not directly sensitive to changes in vegetation biomass. Alternatively, the vegetation optical depth (VOD) parameter from satellite passive microwave remote sensing can detect changes in canopy biomass structure and may provide a useful metric of post‐fire vegetation response to inform regional recovery assessments. We analyzed a multi‐year (2003–2010) satellite VOD record from the NASA AMSR‐E (Advanced Microwave Scanning Radiometer for EOS) sensor to estimate forest recovery trajectories for 14 large boreal fires from 2004 in Alaska and Canada. The VOD record indicated initial post‐fire canopy biomass recovery within 3–7 years, lagging NDVI recovery by 1–5 years. The VOD lag was attributed to slower non‐photosynthetic (woody) and photosynthetic (foliar) canopy biomass recovery, relative to the faster canopy greenness response indicated from the NDVI. The duration of VOD recovery to pre‐burn conditions was also directly proportional (P < 0.01) to satellite (moderate resolution imaging spectroradiometer) estimated tree cover loss used as a metric of fire severity. Our results indicate that vegetation biomass recovery from boreal fire disturbance is generally slower than reported from previous assessments based solely on satellite optical‐infrared remote sensing, while the VOD parameter enables more comprehensive assessments of boreal forest recovery.     

The response of soil organic carbon of a rich fen peatland in interior Alaska to projected climate change

It is important to understand the fate of carbon in boreal peatland soils in response to climate change because a substantial change in release of this carbon as CO₂ and CH₄ could influence the climate system. The goal of this research was to synthesize the results of a field water table manipulation experiment conducted in a boreal rich fen into a process‐based model to understand how soil organic carbon (SOC) of the rich fen might respond to projected climate change. This model, the peatland version of the dynamic organic soil Terrestrial Ecosystem Model (peatland DOS‐TEM), was calibrated with data collected during 2005–2011 from the control treatment of a boreal rich fen in the Alaska Peatland Experiment (APEX). The performance of the model was validated with the experimental data measured from the raised and lowered water‐table treatments of APEX during the same period. The model was then applied to simulate future SOC dynamics of the rich fen control site under various CO₂ emission scenarios. The results across these emissions scenarios suggest that the rate of SOC sequestration in the rich fen will increase between year 2012 and 2061 because the effects of warming increase heterotrophic respiration less than they increase carbon inputs via production. However, after 2061, the rate of SOC sequestration will be weakened and, as a result, the rich fen will likely become a carbon source to the atmosphere between 2062 and 2099. During this period, the effects of projected warming increase respiration so that it is greater than carbon inputs via production. Although changes in precipitation alone had relatively little effect on the dynamics of SOC, changes in precipitation did interact with warming to influence SOC dynamics for some climate scenarios.     

Comparison of complex modeling strategies for prediction of a binary outcome based on a few,highly correlated predictors

Motivated by a clinical prediction problem, a simulation study was performed to compare different approaches for building risk prediction models. Robust prediction models for hospital survival in patients with acute heart failure were to be derived from three highly correlated blood parameters measured up to four times, with predictive ability having explicit priority over interpretability. Methods that relied only on the original predictors were compared with methods using an expanded predictor space including transformations and interactions. Predictors were simulated as transformations and combinations of multivariate normal variables which were fitted to the partly skewed and bimodally distributed original data in such a way that the simulated data mimicked the original covariate structure. Different penalized versions of logistic regression as well as random forests and generalized additive models were investigated using classical logistic regression as a benchmark. Their performance was assessed based on measures of predictive accuracy, model discrimination, and model calibration. Three different scenarios using different subsets of the original data with different numbers of observations and events per variable were investigated. In the investigated setting, where a risk prediction model should be based on a small set of highly correlated and interconnected predictors, Elastic Net and also Ridge logistic regression showed good performance compared to their competitors, while other methods did not lead to substantial improvements or even performed worse than standard logistic regression. Our work demonstrates how simulation studies that mimic relevant features of a specific data set can support the choice of a good modeling strategy.     

Alternative pathways of liana communities in the forests of northwestern Argentina

Liana dynamics in secondary and mature forests are well known in tropical areas dominated by native tree species. Outside the tropics and in secondary forests invaded by exotic species, knowledge is scarce. In this study, we compare liana communities between secondary and mature forests dominated by native species in a subtropical montane area of Sierra de San Javier, Tucuman, Argentina. Additionally, we evaluate changes of liana communities in secondary forests with increasing densities of Ligustrum lucidum and Morus alba, two of the most invasive exotic trees of the area. We surveyed liana species richness and density in three 30-year secondary patches, four 60-year secondary patches, and four mature patches dominated by native tree species, to analyze changes in liana communities with forest age. Within each patch, we sampled 10–25 20 × 20 m quadrats. Additionally, we surveyed liana density and species richness in secondary forest patches with different densities of L. lucidum and M. alba. In native-dominated forests, liana species richness increased and showed a tendency of increasing basal area from 30-year secondary forests to mature forests. Liana density was highly variable, and most of the species were shared between native-dominated secondary and mature forests. Liana density and species richness decreased with L. lucidum density, whereas in secondary forests highly dominated by M. alba, lianas increased in density. Overall, lianas followed different pathways influenced by native forest succession and exotic tree invasions.     

Continental estimates of forest cover and forest cover changes in the dry ecosystems of Africa between 1990 and 2000

Aim

This study provides regional estimates of forest cover in dry African ecoregions and the changes in forest cover that occurred there between 1990 and 2000, using a systematic sample of medium‐resolution satellite imagery which was processed consistently across the continent.

Location

The study area corresponds to the dry forests and woodlands of Africa between the humid forests and the semi‐arid regions. This area covers the Sudanian and Zambezian ecoregions.

Methods

A systematic sample of 1600 Landsat satellite imagery subsets, each 20 km × 20 km in size, were analysed for two reference years: 1990 and 2000. At each sample site and for both years, dense tree cover, open tree cover, other wooded land and other vegetation cover were identified from the analysis of satellite imagery, which comprised multidate segmentation and automatic classification steps followed by visual control by national forestry experts.

Results

Land cover and land‐cover changes were estimated at continental and ecoregion scales and compared with existing pan‐continental, regional and local studies. The overall accuracy of our land‐cover maps was estimated at 87%. Between 1990 and 2000, 3.3 million hectares (Mha) of dense tree cover, 5.8 Mha of open tree cover and 8.9 Mha of other wooded land were lost, with a further 3.9 Mha degraded from dense to open tree cover. These results are substantially lower than the 34 Mha of forest loss reported in the FAO's 2010 Global Forest Resources Assessment for the same period and area.

Main conclusions

Our method generates the first consistent and robust estimates of forest cover and change in dry Africa with known statistical precision at continental and ecoregion scales. These results reduce the uncertainty regarding vegetation cover and its dynamics in these previously poorly studied ecosystems and provide crucial information for both science and environmental policies.     

Structure and content of pollutants in temporal surface sediments in small watersheds

ABSTRACT

Formation of gel-like surface sediments has been observed during spring and autumn in small watersheds in boreal areas with pH <5.7 and concentrations of humic substances above 3 mg L^?1. This structure efficiently accumulates dissolved, colloidal and particulate constituents. The gel consists of ferric (hydr)oxides and fulvic acid and has high viable counts of bacteria (notably Gallionella spp.) as well as fungal hyphae. The solid/solution distribution (log K_d; l kg^?1) for trace metals (Cd, Cu, Pb, V, Zn) ranges from 4 to 6.5 which indicate an efficient accumulation during periods with gel. The concentrations of adsorbable organic halogens in the gel were not different from forest soils in general.     

Neogene origins and implied warmth tolerance of Amazon tree species

Tropical rain forest has been a persistent feature in South America for at least 55 million years. The future of the contemporary Amazon forest is uncertain, however, as the region is entering conditions with no past analogue, combining rapidly increasing air temperatures, high atmospheric carbon dioxide concentrations, possible extreme droughts, and extensive removal and modification by humans. Given the long‐term Cenozoic cooling trend, it is unknown whether Amazon forests can tolerate air temperature increases, with suggestions that lowland forests lack warm‐adapted taxa, leading to inevitable species losses. In response to this uncertainty, we posit a simple hypothesis: the older the age of a species prior to the Pleistocene, the warmer the climate it has previously survived, with Pliocene (2.6–5 Ma) and late‐Miocene (8–10 Ma) air temperature across Amazonia being similar to 2100 temperature projections under low and high carbon emission scenarios, respectively. Using comparative phylogeographic analyses, we show that 9 of 12 widespread Amazon tree species have Pliocene or earlier lineages (>2.6 Ma), with seven dating from the Miocene (>5.6 Ma) and three >8 Ma. The remarkably old age of these species suggest that Amazon forests passed through warmth similar to 2100 levels and that, in the absence of other major environmental changes, near‐term high temperature‐induced mass species extinction is unlikely.     

Fungal disease incidence along tree diversity gradients depends on latitude in European forests

European forests host a diversity of tree species that are increasingly threatened by fungal pathogens, which may have cascading consequences for forest ecosystems and their functioning. Previous experimental studies suggest that foliar and root pathogen abundance and disease severity decrease with increasing tree species diversity, but evidences from natural forests are rare. Here, we tested whether foliar fungal disease incidence was negatively affected by tree species diversity in different forest types across Europe. We measured the foliar fungal disease incidence on 16 different tree species in 209 plots in six European countries, representing a forest‐type gradient from the Mediterranean to boreal forests. Forest plots of single species (monoculture plots) and those with different combinations of two to five tree species (mixed species plots) were compared. Specifically, we analyzed the influence of tree species richness, functional type (conifer vs. broadleaved) and phylogenetic diversity on overall fungal disease incidence. The effect of tree species richness on disease incidence varied with latitude and functional type. Disease incidence tended to increase with tree diversity, in particular in northern latitudes. Disease incidence decreased with tree species richness in conifers, but not in broadleaved trees. However, for specific damage symptoms, no tree species richness effects were observed. Although the patterns were weak, susceptibility of forests to disease appears to depend on the forest site and tree type.