Why evolutionary biologists should get seriously involved in ecological monitoring and applied biodiversity assessment programs

While ecological monitoring and biodiversity assessment programs are widely implemented and relatively well developed to survey and monitor the structure and dynamics of populations and communities in many ecosystems, quantitative assessment and monitoring of genetic and phenotypic diversity that is important to understand evolutionary dynamics is only rarely integrated. As a consequence, monitoring programs often fail to detect changes in these key components of biodiversity until after major loss of diversity has occurred. The extensive efforts in ecological monitoring have generated large data sets of unique value to macro-scale and long-term ecological research, but the insights gained from such data sets could be multiplied by the inclusion of evolutionary biological approaches. We argue that the lack of process-based evolutionary thinking in ecological monitoring means a significant loss of opportunity for research and conservation. Assessment of genetic and phenotypic variation within and between species needs to be fully integrated to safeguard biodiversity and the ecological and evolutionary dynamics in natural ecosystems. We illustrate our case with examples from fishes and conclude with examples of ongoing monitoring programs and provide suggestions on how to improve future quantitative diversity surveys.

Assessment of population structure by single nucleotide polymorphisms (SNPs) in goat breeds

Single nucleotide polymorphisms (SNPs) may be used in biodiversity studies and commercial tasks like traceability, paternity testing and selection for suitable genotypes. Twenty-seven SNPs were characterized and genotyped on 250 individuals belonging to eight Italian goat breeds. Multilocus genotype data were used to infer population structure and assign individuals to populations. To estimate the number of groups (K) to test in population structure analysis we used likelihood values and variance of the bootstrap samples, deriving optimal K from a drop in the likelihood and a rise in the variance plots against K.

Ecosystem service trade-offs and stakeholder claims - a meso-scale study from a Madagascar biodiversity hotspot

The north-eastern escarpment of Madagascar has been labelled a global biodiversity hotspot due to its extremely high rates of endemic species which are heavily threatened by accelerated deforestation rates and landscape change. The traditional practice of shifting cultivation or "tavy" used by the majority of land users in this area to produce subsistence rice is commonly blamed for these threats. A wide range of stakeholders ranging from conservation to development agencies, and from the private to the public sector has therefore been involved in trying to find solutions to protect the remaining forest fragments and to increase agricultural production. Consequently, provisioning, regulating and socio-cultural services of this forest-mosaic landscape are fundamentally altered leading to trade-offs between them and consequently new winners and losers amongst the stakeholders at different scales. However, despite a growing amount of evidence from case studies analysing local changes, the regional dynamics of the landscape and their contribution to such trade-offs remain poorely understood. This study therefore aims at using generalised landscape units as a base for the assessment of multi-level stakeholder claims on ecosystem services to inform negotiation, planning and decision making at a meso-scale. The presented study applies a mixed-method approach combining remote sensing, GIS and socio-economic methods to reveal current landscape dynamics, their change over time and the corresponding ecosystem service trade-offs induced by diverse stakeholder claims on the regional level. In a first step a new regional land cover classification for three points in time (1995, 2005 and 2011) was conducted including agricultural classes characteristic for shifting cultivation systems. Secondly, a novel GIS approach, termed “landscape mosaics approach” originally developed to assess dynamics of shifting cultivation landscapes in Laos was applied. Through this approach generalised landscape mosaics were generated allowing for a better understanding of changes in land use intensities instead of land cover. As a next step we will try to use these landscape units as proxies to map provisioning and regulating ecosystem services throughout the region. Through the overlay with other regional background data such as accessibility and population density and information from a region-wide stakeholder analysis, multiscale trade-offs between different services will be highlighted. The trade-offs observed on the regional scale will then be validated through a socio-economic ground-truthing within selected sites at the local scale. We propose that such meso-scale knowledge is required by all stakeholders involved in decision making towards sustainable development of north-eastern Madagascar.

Ecosystem services, biodiversity and environmental change in a tropical mountain ecosystem of south Ecuador

An interdisciplinary research unit consisting of 30 teams in the natural, economic and social sciences analyzed biodiversity and ecosystem services of a mountain rainforest ecosystem in the hotspot of the tropical Andes, with special reference to past, current and future environmental changes. The group assessed ecosystem services using data from ecological field and scenario-driven model experiments, and with the help of comparative field surveys of the natural forest and its anthropogenic replacement system for agriculture. The book offers insights into the impacts of environmental change on various service categories mentioned in the Millennium Ecosystem Assessment (2005): cultural, regulating, supporting and provisioning ecosystem services. Examples focus on biodiversity of plants and animals including trophic networks, and abiotic/biotic parameters such as soils, regional climate, water, nutrient and sediment cycles. The types of threats considered include land use and climate changes, as well as atmospheric fertilization. In terms of regulating and provisioning services, the emphasis is primarily on water regulation and supply as well as climate regulation and carbon sequestration. With regard to provisioning services, the synthesis of the book provides science-based recommendations for a sustainable land use portfolio including several options such as forestry, pasture management and the practices of indigenous peoples. In closing, the authors show how they integrated the local society by pursuing capacity building in compliance with the CBD-ABS (Convention on Biological Diversity - Access and Benefit Sharing), in the form of education and knowledge transfer for application.

Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment

Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.