Community mean traits as additional indicators to monitor effects of land-use intensity on grassland plant diversity

Semi-natural grasslands, biodiversity hotspots in Central-Europe, suffer from the cessation of traditional land-use. Amount and intensity of these changes challenge current monitoring frameworks typically based on classic indicators such as selected target species or diversity indices. Indicators based on plant functional traits provide an interesting extension since they reflect ecological strategies at individual and ecological processes at community levels. They typically show convergent responses to gradients of land-use intensity over scales and regions, are more directly related to environmental drivers than diversity components themselves and enable detecting directional changes in whole community dynamics. However, probably due to their labor- and cost intensive assessment in the field, they have been rarely applied as indicators so far. Here we suggest overcoming these limitations by calculating indicators with plant traits derived from online accessible databases. Aiming to provide a minimal trait set to monitor effects of land-use intensification on plant diversity we investigated relationships between 12 community mean traits, 2 diversity indices and 6 predictors of land-use intensity within grassland communities of 3 different regions in Germany (part of the German ‘Biodiversity Exploratory’ research network). By standardization of traits and diversity measures, use of null models and linear mixed models we confirmed (i) strong links between functional community composition and plant diversity, (ii) that traits are closely related to land-use intensity, and (iii) that functional indicators are equally, or even more sensitive to land-use intensity than traditional diversity indices. The deduced trait set consisted of 5 traits, i.e., specific leaf area (SLA), leaf dry matter content (LDMC), seed release height, leaf distribution, and onset of flowering. These database derived traits enable the early detection of changes in community structure indicative for future diversity loss. As an addition to current monitoring measures they allow to better link environmental drivers to processes controlling community dynamics.

Role of Urbanization, Land-Use Diversity, and Livestock Intensification in Zoonotic Emerging Infectious Diseases

Emerging infectious diseases (EIDs) continue to significantly threaten human and animal health. While there has been some progress in identifying underlying proximal driving forces and causal mechanisms of disease emergence, the role of distal factors is most poorly understood. This article focuses on analyzing the statistical association between highly pathogenic avian influenza (HPAI) H5N1 and urbanization, land-use diversity and poultry intensification. A special form of the urban transition—peri-urbanization—was hypothesized as being associated with ‘hot-spots’ of disease emergence. Novel metrics were used to characterize these distal risk factors. Our models, which combined these newly proposed risk factors with previously known natural and human risk factors, had a far higher predictive performance compared to published models for the first two epidemiological waves in Viet Nam. We found that when relevant risk factors are taken into account, urbanization is generally not a significant independent risk factor. However, urbanization spatially combines other risk factors leading to peri-urban places being the most likely ‘hot-spots’. The work highlights that peri-urban areas have highest levels of chicken density, duck and geese flock size diversity, fraction of land under rice, fraction of land under aquaculture compared to rural and urban areas. Land-use diversity, which has previously never been studied in the context of HPAI H5N1, was found to be a significant risk factor. Places where intensive and extensive forms of poultry production are collocated were found to be at greater risk.

Quantifying differences in land use emission estimates implied by definition discrepancies

The quantification of CO2 emissions from anthropogenic land use and land use change (eLUC) is essential to understand the drivers of the atmospheric CO2 increase and to inform climate change mitigation policy. Reported values in synthesis reports are commonly derived from different approaches (observation-driven bookkeeping and process-modelling) but recent work has emphasized that inconsistencies between methods may imply substantial differences in eLUC estimates. However, a consistent quantification is lacking and no concise modelling protocol for the separation of primary and secondary components of eLUC has been established. Here, we review differences of eLUC quantification methods and apply an Earth System Model (ESM) of Intermediate Complexity to quantify them. We find that the magnitude of effects due to merely conceptual differences between ESM and offline vegetation model-based quantifications is ~ 20 % for today. Under a future business-as-usual scenario, differences tend to increase further due to slowing land conversion rates and an increasing impact of altered environmental conditions on land-atmosphere fluxes. We establish how coupled Earth System Models may be applied to separate secondary component fluxes of eLUC arising from the replacement of potential C sinks/sources and the land use feedback and show that secondary fluxes derived from offline vegetation models are conceptually and quantitatively not identical to either, nor their sum. Therefore, we argue that synthesis studies should resort to the "least common denominator" of different methods, following the bookkeeping approach where only primary land use emissions are quantified under the assumption of constant environmental boundary conditions.

Land use policies and practices for reducing vulnerability in rural Tajikistan

Tajikistan, with 93% of its surface area taken up by mountains and 65% of its labor force employed in agriculture, is judged to be highly vulnerable to risks, including climate change risks and food insecurity risks. The article examines a set of land use policies and practices that can be used to mitigate the vulnerability of Tajikistan’s large rural population, primarily by increasing family incomes. Empirical evidence from Tajikistan and other CIS countries suggests that families with more land and higher commercialization earn higher incomes and achieve higher well-being. The recommended policy measures that are likely to increase rural family incomes accordingly advocate expansion of smallholder farms, improvement of livestock productivity, increase of farm commercialization through improvement of farm services, and greater diversification of both income sources and the product mix. The analysis relies for supporting evidence on official statistics and recent farm surveys. Examples from local initiatives promoting sustainable land management practices and demonstrating the implementation of the proposed policy measures are presented.