Soft sediment benthic ecosystems are highly productive habitats which provide humans with a variety of valued resources and ecosystem services globally. However, coastal environments are subject to ongoing and increasing levels of anthropogenic stress which urgently needs to be quantified and strategically managed to balance socioeconomic resource interests. To support a more holistic approach to Marine Spatial Planning and better inform management decisions, spatial assessment approaches are needed which quantify the accumulating impact of multiple stressors on coastal species and habitats. This thesis investigates stressor-induced change in the density and distribution of subtidal benthic invertebrates from two globally pervasive stressors (sedimentation and bottom fishing), to develop spatial assessment tools useful to inform marine spatial management decisions. For many benthic species, their functional capacity is inherently density-dependent, and environmental stressors can impact population density, hence limiting the functional capacity of species and their ability to contribute to ecosystem processes and overall ecosystem health. A holistic approach to MSP needs to address the ways in which humans can cumulatively use, and also impact the environment, but it is difficult to measure the impact an environmental stressor can cause without first quantifying the current density and distribution of key species that they effect. Furthermore, it can often be challenging to obtain species records measuring abundance, density, or species richness within certain geographical locations, due to data scarcity, even if more data is available over a broader spatial scale. Probability of occurrence, abundance, and density was predicted using Species Distribution Models (SDMs) for seven functionally distinct benthic invertebrates, over two different spatial scales to compare the difference in model performance and usefulness of predictions made using data-rich national scale models compared to data limited regional scale models. Results indicated that neither occurrence nor abundance SDMs performed consistently better at either scale across all taxa models, demonstrating the challenge of working in-data limited environments. Models which achieved the more optimal predictive performance across spatial scales were selected to be combined into a regionally useful density model (i.e., regional data-derived occurrence model * national data-derived abundance model) highlighting the utility of a multi-scalar approach. Knowledge of how multiple stressors impact marine species and modify habitats over time is critical, to support management and mitigation of anthropogenic stressors. Bottom fishing and sedimentation stress are two globally pervasive coastal stressors. The transportation of terrestrially sourced silt, mud, and clay into the coastal environment from inadequate land management can alter sediment biogeochemistry, and alter macrofaunal community composition, which can lead to the smothering of seafloor communities. Bottom fishing can directly damage and disturb seabed habitats, reducing the abundance of macrofaunal communities, and can lead to homogenisation of the seascape. A spatially explicit model including correlative stressor-response relationships were applied to simulate single and multi-stressor impact scenarios over a temporal period of four-years to predict the change in density, distribution, and recovery for different stressor combinations and magnitudes. Models focussed on three functionally distinct coastal seafloor invertebrates that varied in stressor response and recovery time. All taxa exhibited different stressor responses in terms of density change, and the spatial distribution pattern of density values was affected, informed through empirically derived stressor-receptor response curves. The greatest modification to taxa density occurred across the shallow coastal environment, near shore, for habitats that were predicted to have high density to begin with. Fishing was the more dominant stressor and overlapping fishing impact year on year resulted in little to no recovery. For sensitive emergent epifauna (Callyspongia), sedimentation stress was almost as impactful as fishing, highlighting that greater management consideration should be given to the compound effect of slow-acting, accumulating stressors, even in scenarios where a single stressor is more dominant. Failure to adequately identify and mitigate the effects of multiple stressors increases the risk of focussing conservation efforts on areas that could become ecologically diminished in the future. To ensure that global biodiversity conservation targets are upheld under ongoing anthropogenic conditions, practitioners must identify robust and ecologically resilient habitats that will persist over time as part of a systematic prioritization approach. A comparative spatial prioritization assessment was performed to test the utility of using density SDMs that had been modified by stressor impacts (stressor-impacted predictions) to drive a spatial prioritization using Zonation, as opposed to using unimpacted density SDMs (the conventional method). Utilising stressor-impacted predictions within the prioritisation assessment increased conservation efficiency, and thus spatial accuracy, to help prioritise high-density areas that showed resilience to stressor impacts over time (from 4 years of successive stress). This analysis highlighted that conventional prioritization approaches may no longer be sufficient and may prioritise habitats that experience density loss under stressed conditions, undermining conservation effectiveness. Incorporating multiple stressor effects that have accrued over time can help identify areas that are likely to retain a higher total density into the future, to support long-term conservation objectives. Incorporation of spatially explicit stressor effects using taxa stressor impacted density predictions helps identify ecologically rich and resilient habitat areas that persist within the broad footprints of stressors, instead of avoidance, which is often promoted by conventional approaches to minimise conservation cost. Collectively, this thesis demonstrated the utility of novel modelling approaches which integrate the combined and accumulating effects of anthropogenic stressors on coastal species and habitats to help inform MSP decision-making. It also highlighted the range of possible implications to benthic species and coastal ecosystems if anthropogenic stressors are not adequately identified and managed.