Quo vadis, smallholder forest landscape? An introduction to the LPB-RAP model.

The impacts of the Anthropocene on climate and biodiversity pose societal and ecological problems that may only be solved by ecosystem restoration. Local to regional actions are required, which need to consider the prevailing present and future conditions of a certain landscape extent. Modeling approaches can be of help to support management efforts and to provide advice to policy making. We present stage one of the LaForeT-PLUC-BE model (Landscape Forestry in the Tropics-PCRaster Land Use Change-Biogeographic & Economic model; in short: LPB) and its thematic expansion module RAP (Restoration Areas Potentials). LPB-RAP is a high-resolution pixel-based scenario tool that relies on a range of explicit land use types (LUTs) to describe various forest types and the environment. It simulates and analyzes future landscape configurations under consideration of climate, population and land use change long-term. Simulated Land Use Land Cover Change (LULCC) builds on dynamic, probabilistic modeling incorporating climatic and anthropogenic determinants as well as restriction parameters to depict a sub-national regional smallholder-dominated forest landscape. The model delivers results for contrasting scenario settings by simulating without and with potential Forest and Landscape Restoration (FLR) measures. FLR potentials are depicted by up to five RAP-LUTs. The model builds on user-defined scenario inputs, such as the Shared Socioeconomic Pathways (SSP) and Representative Concentration Pathways (RCP). Model application is here exemplified for the SSP2-RCP4.5 scenario in the time frame 2018-2100 on the hectare scale in annual resolution using Esmeraldas province, Ecuador, as a case study area. The LPB-RAP model is a novel, heuristic Spatial Decision Support System (SDSS) tool for smallholder-dominated forest landscapes, supporting near-time top-down planning measures with long-term bottom-up modeling. Its application should be followed up by FLR on-site investigations and stakeholder participation across all involved scales.

Climatologies at high resolution for the earth's land surface areas.

High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present the CHELSA (Climatologies at high resolution for the earth's land surface areas) data of downscaled model output temperature and precipitation estimates of the ERA-Interim climatic reanalysis to a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperatures. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height, with a subsequent bias correction. The resulting data consist of a monthly temperature and precipitation climatology for the years 1979-2013. We compare the data derived from the CHELSA algorithm with other standard gridded products and station data from the Global Historical Climate Network. We compare the performance of the new climatologies in species distribution modelling and show that we can increase the accuracy of species range predictions. We further show that CHELSA climatological data has a similar accuracy as other products for temperature, but that its predictions of precipitation patterns are better.

Mass elevation and lee effects markedly lift the elevational distribution of ground beetles in the Himalaya-Tibet orogen.

Mass elevation and lee effects markedly influence snow lines and tree lines in high mountain systems. However, their impact on other phenomena or groups of organisms has not yet been quantified. Here we quantitatively studied their influence in the Himalaya-Tibet orogen on the distribution of ground beetles as model organisms, specifically whether the ground beetle distribution increases from the outer to the inner parts of the orogen, against latitudinal effects. We also tested whether July temperature and solar radiation are predictors of the beetle's elevational distribution ranges. Finally, we discussed the general importance of these effects for the distributional and evolutionary history of the biota of High Asia. We modelled spatially explicit estimates of variables characterizing temperature and solar radiation and correlated the variables with the respective lower elevational range of 118 species of ground beetles from 76 high-alpine locations. Both July temperature and solar radiation significantly positively correlated with the elevational ranges of high-alpine beetles. Against the latitudinal trend, the median elevation of the respective species distributions increased by 800 m from the Himalayan south face north to the Transhimalaya. Our results indicate that an increase in seasonal temperature due to mass elevation and lee effects substantially impact the regional distribution patterns of alpine ground beetles of the Himalaya-Tibet orogen and are likely to affect also other soil biota there and in mountain ranges worldwide. Since these effects must have changed during orogenesis, their potential impact must be considered when biogeographic scenarios based on geological models are derived. As this has not been the practice, we believe that large biases likely exist in many paleoecological and evolutionary studies dealing with the biota from the Himalaya-Tibet orogen and mountain ranges worldwide.

The impact of livestock grazing on plant diversity: an analysis across dryland ecosystems and scales in southern Africa.

A general understanding of grazing effects on plant diversity in drylands is still missing, despite an extensive theoretical background. Cross-biome syntheses are hindered by the fact that the outcomes of disturbance studies are strongly affected by the choice of diversity measures, and the spatial and temporal scales of measurements. The aim of this study is to overcome these weaknesses by applying a wide range of diversity measures to a data set derived from identical sampling in three distinct ecosystems. We analyzed three fence-line contrasts (heavier vs. lighter grazing intensity), representing different degrees of aridity (from arid to semiarid) and precipitation regimes (summer rain vs. winter rain) in southern Africa. We tested the impact of grazing intensity on multiple aspects of plant diversity (species and functional group level, richness and evenness components, alpha and beta diversity, and composition) at two spatial scales, and for both 5-yr means and interannual variability. Heavier grazing reduced total plant cover and substantially altered the species and functional composition at all sites. However, a significant decrease in species alpha diversity was detected at only one of the three sites. By contrast, alpha diversity of plant functional groups responded consistently across ecosystems and scales, with a significant decrease at heavier grazing intensity. The cover-based measures of functional group diversity responded more sensitively and more consistently than functional group richness. Beta diversity of species and functional types increased under heavier grazing, showing that at larger scales, the heterogeneity of the community composition and the functional structure were increased. Heavier grazing mostly increased interannual variability of alpha diversity, while effects on beta diversity and cover were inconsistent. Our results suggest that species diversity alone may not adequately reflect the shifts in vegetation structure that occur in response to increased grazing intensity in the dryland biomes of southern Africa. Compositional and structural changes of the vegetation are better reflected by trait-based diversity measures. In particular, measures of plant functional diversity that include evenness represent a promising tool to detect and quantify disturbance effects on ecosystems.

Long-term citalopram administration reduces responsiveness of HPA axis in patients with major depression: relationship with S-citalopram concentrations in plasma and cerebrospinal fluid (CSF) and clinical response.

RATIONALE: A dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis is a well-documented neurobiological finding in major depression. Moreover, clinically effective therapy with antidepressant drugs may normalize the HPA axis activity. OBJECTIVE: The aim of this study was to test whether citalopram (R/S-CIT) affects the function of the HPA axis in patients with major depression (DSM IV). METHODS: Twenty depressed patients (11 women and 9 men) were challenged with a combined dexamethasone (DEX) suppression and corticotropin-releasing hormone (CRH) stimulation test (DEX/CRH test) following a placebo week and after 2, 4, and 16 weeks of 40 mg/day R/S-CIT treatment. RESULTS: The results show a time-dependent reduction of adrenocorticotrophic hormone (ACTH) and cortisol response during the DEX/CRH test both in treatment responders and nonresponders within 16 weeks. There was a significant relationship between post-DEX baseline cortisol levels (measured before administration of CRH) and severity of depression at pretreatment baseline. Multiple linear regression analyses were performed to identify the impact of psychopathology and hormonal stress responsiveness and R/S-CIT concentrations in plasma and cerebrospinal fluid (CSF). The magnitude of decrease in cortisol responsivity from pretreatment baseline to week 4 on drug [delta-area under the curve (AUC) cortisol] was a significant predictor (p<0.0001) of the degree of symptom improvement following 16 weeks on drug (i.e., decrease in HAM-D21 total score). The model demonstrated that the interaction of CSF S-CIT concentrations and clinical improvement was the most powerful predictor of AUC cortisol responsiveness. CONCLUSION: The present study shows that decreased AUC cortisol was highly associated with S-CIT concentrations in plasma and CSF. Therefore, our data suggest that the CSF or plasma S-CIT concentrations rather than the R/S-CIT dose should be considered as an indicator of the selective serotonergic reuptake inhibitors (SSRIs) effect on HPA axis responsiveness as measured by AUC cortisol response.