Spatial differentiation of marine eutrophication damage indicators based on species density

Marine eutrophication refers to an ecosystem response to the loading of nutrients, typically nitrogen (N), to coastal waters where several impacts may occur. The increase of planktonic growth due to N-enrichment fuels the organic carbon cycles and may lead to excessive oxygen depletion in benthic waters. Such hypoxic conditions may cause severe effects on exposed ecological communities. The biologic processes that determine production, sink, and aerobic respiration of organic material, as a function of available N, are coupled with the sensitivity of demersal species to hypoxia to derive an indicator of the Ecosystem Response (ER) to N-uptake. The loss of species richness expressed by the ER is further modelled to a marine eutrophication Ecosystem Damage (meED) indicator, as an absolute metric of time integrated number of species disappeared (species yr), by applying a newly-proposed and spatially-explicit factor based on species density (SD). The meED indicator is calculated for 66 Large Marine Ecosystems and ranges from 1.6 × 10⁻¹² species kgN⁻¹ in the Central Arctic Ocean, to 4.8 × 10⁻⁸ species kgN⁻¹ in the Northeast U.S. Continental Shelf. The spatially explicit SDs contribute to the environmental relevance of meED scores and to the harmonisation of marine eutrophication impacts with other ecosystem-damage Life Cycle Impact Assessment (LCIA) indicators. The novel features improve current methodologies and support the adoption of the meED indicator in LCIA for the characterization of anthropogenic-N emissions and thus contributing to the sustainability assessment of human activities.     

Assessing high conservation value areas for rare,endemic and threatened (RET) species: A study in high altitude Changthang landscape of India

The Forest Stewardship Council developed the concept of High Conservation Values (HCVs) as a criteria in the forest certification process in order to promote sustainable forest management. It has six major components or values and component one and two of HCVs deal with the habitat for viable populations of “rare, endemic and threatened (RET) species” using the IUCN Red List category and other national / regional / local lists. But a consistent robust methodology for identification of these areas, does not exist. The present study tried to develop for the first time, a straight forward inclusive methodology for identification of HCVAs for the RET species on a spatio-temporal scale. A total of 50 RET and other significant species (32 flora, 10 fauna and 8 avifauna) were identified after a thorough literature review, field surveys and consultations with experts. Occurrence data of the selected species was collected from different secondary sources, field surveys, institutes and scientists who have worked on them. A 10 km grid-based approach and stratified random sampling was used for the primary GPS field surveys conducted during 2018–2019. MaxEnt species distribution model (SDM) software was used based on the occurrence data and environmental variables for identification of potential suitable habitats for the selected species. Linear support vector machine (LSVM) model was used for assessing the performance of the SDMs. The performance of each SDM has been validated through Cohen's Kappa (KAPPA), true skill statistic (TSS) and receiver operating characteristics (ROC) models. The proposed methodology addresses the urgent need for a holistic and robust set of techniques to apply the HCV toolkit. This is key to identify and map HCVAs for RET species at the landscape level and can be easily adapted to and adopted at the national, regional, state or local level in India. The methods offer an efficient, reliable approach for the application of the HCV concept, elsewhere in the world.