Integrating ongoing biodiversity monitoring: potential benefits and methods

Abstract

Halting the loss of biodiversity comes along with the need to quantify biodiversity composition and dynamics at large spatial and temporal scales. Highly standardized, international monitoring networks would be ideal, but they do not exist yet. If we are to assess changes in biodiversity now, combining output available from ongoing monitoring initiatives is the only option. However, integration of biodiversity information across schemes is still very poorly developed. In this paper, we outline practical issues to be considered when planning to combine existing monitoring information. First, we provide an overview of avenues for integration along the four dimensions that characterize a monitoring design: sample size, biological coverage, spatial coverage and temporal coverage. We also emphasize that complementarity in monitoring targets across schemes enables to describe complex processes of biodiversity dynamics, e.g. through relating species traits to the impacts of environmental changes. Second, we review some methods to overcome differences in designs among monitoring schemes, such as site selection, poststratification and measurement error. Finally, we point out some commonly used statistical methods that are at hand for combining data or parameter estimates. We especially emphasize the possible levels of data integration (raw data, parameter estimates, or effect size estimates), and the largely under-exploited potential of meta-analysis methods and weighted analyses. This contribution aims to bolster the practice and use of integration of ongoing monitoring initiatives for biodiversity assessment.

Why Include Impacts on Biodiversity from Land Use in LCIA and How to Select Useful Indicators?

“…[30][31][32]). Not surprising is also that most of the proposed frameworks for biodiversity assessments are a mix of indicators, often a combination of structural indicators and selected indicator species or taxonomic groups [9,25,33]. Due to the lack of correlation between, in particular, species diversity and ecosystem services, it must also be expected that conflicting results will be found in LCA if such aspects are included, just like conflicting results between any other impact categories frequently found in comparative LCA studies [138].…”

“…Changes in land use are often the most important driver for loss of biodiversity [7][8][9][10][11], but climate change, pollution, invasive species and overexploitation are also of importance [3,9,[12][13][14]. Barnes [15] and Haines-Young [10] point out that not only changes where one land use activity is replaced by another are of importance; small modifications in land use, such as changes in intensity, changes in use of fertilizers and watering, changes in crop, etc., might be equally important as transformations, even if such modifications are not identified when land use changes are in focus.…”

“…Due to the complexity of biodiversity, it is argued that a universal indicator for biodiversity is not likely to be found [9,[23][24][25], and using the structure from Noss [23], Curran et al [6] show that biodiversity indicators can be divided into 12 categories based on hierarchical components and biological attributes. Still, most proposals for including impacts on biodiversity from LULUC in LCIA try to capture the impact in a single indicator.…”

“…The increase or decrease of species within one taxonomic group gives in itself little information about changes in the pressure on the present state of the ecosystem [9,111]. Gottfried et al [112] have documented that an early response to a long-term negative impact might in fact be a short-term increase in species richness.…”

Surveillance of habitats and plant diversity indicators across a regional gradient in the Iberian Peninsula

“…; e.g. Henry et al, 2008), this integration of systems and the harmonization of processes and tools could represent a landmark for environmental monitoring efforts in the Peninsula and elsewhere.…”