Assessing the human impacts on biodiversity is important for conserving biodiversity. Life cycle assessment (LCA) is a tool to assess the impact product service systems have on the environment. To critically asses the human impact of land use on biodiversity in LCA, characterisation factors (CF) are needed to translate area and type of land use into loss of biodiversity. Most CFs are based on species richness but another biodiversity indicator, functional diversity (FD), better represents ecosystem functioning compared to taxonomic measures such as species richness. This study proposes a new method for calculating CFs, based on FD, for assessing impact of land use on plant biodiversity. To demonstrate the applicability of the method that is proposed, CFs were calculated based on data from Germany. The data was divided into four types, being land use, plant abundance, trait data and environmental data. The CFs developed show trends in impact on biodiversity in accordance with other studies. The proposed method in this study can guide in the development of more precise and geographically diverse CFs for assessing the impact of land use in biodiversity in LCA.

Food forests are gaining attention in the Netherlands as a concept that holds the promise of delivering a variety of ecosystem services our society depends upon. However, there are no insights available what a food forest could look like on peat soils nor what its environmental benefits could be. At the same time the Dutch peat area represents 12% of the total agricultural area and is subjected to soil subsidence releasing carbon dioxide, accounting for 2.5% of the national greenhouse gas (GHG) emissions. This thesis designed a food forest for the Dutch peat area and assessed it on three ecosystem services being: food provisioning, climate regulation and wildlife habitat provisioning. The results were put into perspective by comparing them to the currently predominant land-use for organic milk production. The plant species were selected based on selection criteria which took into account the environmental conditions and marketing potential. Yield estimates were made based on documented yields and proxies. GHG emissions and carbon sequestration potentials were determined by both available comparative literature and calculations. For the indications of wildlife habitat provisioning birds were taken as indicator species group and the attractiveness was determined by available literature. The proposed peatland food forest (PFF) consists of 21 different plant species that were estimated to produce a mean dry weight yield of 863 kg/ha/a over the first 20 years with a maximum of 1569 kg/ha/a. Furthermore, the PFF is expected to store between 0.37 and 0.52 Mg CO2 eq./ha/a compared to the current emissions of 15.8 Mg CO2 eq./ha/a. Finally, the PFF provides a habitat that is likely to attract more but different bird species than the current landscape, including a greater number of endangered species. The results are in range with existing literature on either food forests or swamp forests and highlight the potential of food forest on peat soil to contribute to sustainable food provisioning, reduction of GHG-emissions, and preservation of wildlife habitats. This study promotes to conduct a field experiment to validate the promising initial results.

The food sector plays a crucial role in exceeding several planetary boundaries. Currently, humanity has the challenge to stay between these boundaries. Food forests are an approach for improving ecosystems in soil quality, sequestering carbon and enhancing biodiversity while providing food. However, this concept is yet nearly unstudied in temperate regions. Accordingly, this study attempted to investigate aboveground and belowground storage, carbon fluxes, and the build-up rate in the transition from grassland to a food forest through an in-depth case study in a temperate region. In order to analyse all key carbon pools, a plotless method was applied for the coppice, hedgerows, fruit and nut-bearing trees, and a plot-based method for the grass, herbs, litter and soil organic carbon (SOC). Overall, the results showed exponential growth in aboveground carbon in the living biomass, though remarkably different patterns for SOC over the first 5.5 years. The ground layer (e.g. grass, herbs, and litter) is a significant source of aboveground carbon in young food forests (95% in year 3.5 to 36% in year 5.5). The trees compartments showed an exponential increase, and the total stored carbon biomass in the food forests at the age of 5.5 is 6.0 t C ha-1 yr-1. The SOC differed over the years, which is 115 t C ha-1 in the grassland and depicts 78 to 136 t C ha-1in year 5.5. Finally, the food forest has the potential to sequester around 4.4 t C ha-1 yr-1 in above and belowground biomass, functioning as active carbon sinks already within the first five years of the case study. Coppice and hedgerows have proven to be vital in sequestering carbon in living biomass. Further research should investigate older food forests in temperate regions while bearing in mind the potential of coppices and hedgerows. In addition, a better understanding of belowground carbon is essential for assessing the net carbon impact of carbon farming initiatives, as the soil stores most of the carbon.

With the current trend in emissions, the pH levels of the oceans are expected to decrease from 8.1 to 7.8 by the end of the century. In combination with the other stressors, it is projected that OA will have a wide range of impacts on marine life and its services to humanity. The representation of these implications is limited in environmental assessment tools such as Life Cycle Assessment. This research explores the relationship between the changing acidity of the oceans and marine biodiversity loss. This relation is quantified through utilising the ecotoxicology impact assessment approach for LCA. Following this approach, an endpoint characterization model is developed for ocean acidification. 3 different categorisations (climate zones, calcification, exposure duration) were made to assess their effects on species responses. The results revealed that there is no significant difference in responses based on different exposure durations or climate zones. Calcifying species on the other hand is found to have a higher sensitivity to ocean acidification as the change in carbonate chemistry directly influences the shell and skeleton formation of these organisms. Lastly, these models were integrated into an endpoint characterization model for ocean acidification. From the 3 GHG emissions included within the scope of this research (CO2, CO, CH4), CO2 has the highest (CFCO2 = 4.883 × 104 (𝑃𝐷𝐹)𝑚3/𝑘𝑔𝐺𝐻𝐺) and CH4 has the lowest (CFCH4 = 4.072 × 104 𝑃𝐷𝐹)𝑚3/𝑘𝑔𝐺𝐻𝐺) impact on marine biodiversity loss due to OA. These ecosystem damage indicators can be utilised in the impact assessment phase of the Life Cycle Assessment to translate the inventory results into impact on marine biodiversity. Through the quantification of the impacts of ocean acidification, the effects of this major stressor on marine life can be better understood and targeted strategies can be developed. However, more research is required to increase the robustness of these models through expanding the species scope and incorporating temporal and geographical aspects into the models. Furthermore, the cascading effects of the changing ocean pH are still unknown and its consequences on ecosystems and socio-economic structures are unprecedented. To establish science-based targets and strategies to conserve the species richness in marine life, the extent of our understanding of the damage caused by anthropogenic actions needs to be further explored and estimated.

The CONE-LCA framework is a promising framework that can be used to assess the impact of food items on human health and the environment. However, the nutrition-health assessment in the CONE-LCA framework quantifies the health impacts of food at the level of food items with the use of an indicator that is based on only few nutrients and otherwise broad food groups. Given that food items within food groups can have different impacts on health, disaggregating health impacts can be of added value and was explored here. An extended version of the Nutrients Rich Food index is used for both downscaling and cluster analysis. The correlation coefficient at the aggregated levels with the NRF index (-0.93) was substantially higher than the original health impact indicator of food items with the NRF index (0.36). These results illustrate that the use of a downscaled indicator improves the health impact assessment of food items. The downscaling analysis showed that downscaled health impacts can differ substantially between food items within food groups. Furthermore, the cluster analysis showed that some food groups (e.g. fruits, vegetables and red meat) are highly variable in nutrient density and therefore prioritizing these food groups for clustering can be of added value in future epidemiological studies. The improved nutrition health assessment model is not only relevant within the CONE-LCA framework but can be used on its own to assess health impacts of food items. The model may be very useful in policy applications as it enables comparison of food items on impact on human health and the environment, which can be the basis for sustainable dietary guidelines. Future research can focus on further development and validation of the model.

The cultivation of palm oil has many adverse social and environmental impacts. The high level of biodiversity that is native to areas where palm oil plantations occur is at risk. Various measures are taken, such as the Roundtable of Sustainable Palm Oil (RSPO). The RSPO certification is a sector governance measure that indicates which management and operations interventions have to be implemented to protect the public interest – countering negative social and environmental impacts. No research has been done on the impact of RSPO certification and the plantation size on biodiversity. The research question of this thesis is “do RSPO certification and plantation size influence the level of biodiversity of palm oil plantations in Indonesia and Malaysia?” Three open source online data sets from Global Forest Watch containing information on plantations were used. These spatial data sets were combined with Global Biodiversity Information Facility (GBIF) species observations data. From GBIF, four taxa were selected to be used in this study, known to be impacted by palm oil cultivation: birds, lizards, primates and small mammals. The majority of the GBIF observations that laid within the studied plantation data set, however, were bird observations (93.0%). Only 1.8% of the GBIF observations laid within the palm oil plantations. Data analysis indicated that there is no significant difference between RSPO and non-RSPO-certified plantations in terms of biodiversity. The obtained results imply that the measures that are taken by plantations to obtain the RSPO certificate do not affect the level of biodiversity and therefore certification does not protect the species living on plantations better when compared to plantations that are not RSPO-certified. Results also indicate that biodiversity is not influenced by the size of a plantation – small, medium or large. The proposed research was the first attempt in getting insight into the effectiveness of certification and small-scaled plantations – in other words plantation size – on biodiversity levels. It can be concluded that the effectiveness of the two measures has not been proven yet. Suggestions for further research are done, in which higher quality data sets and larger numbers of observations are of importance.