Landscape Ecology Applications

What can landscape history tell us about biodiversity? Our new article in Ecology and Evolution led by Nivedita Varma Harisena and with Maarten van Strien demonstrates the importance of historical ecological networks to estimate current beta and gamma diversity. The history of a landscape can help identify spatial patterns in species metacommunity extents that associate better with beta and gamma diversity, which cannot be identified via spatial networks alone. We found this for odonate species in the wetlands of the Swiss plateau based on data of the past 110 years on wetland change (1899-2010). Thus, the history of a landscape contributes significant information, either in terms of habitat ecological similarities or time lagged species dispersal impacts, on the current patterns and processes of species diversity. Such historical habitat networks can be a useful knowledge base for estimating metacommunity spatial extents at a regional scale. Bridging the gap between theory and practice, the method of identifying regional units of similarly interacting habitat patch groups can create a common ground within which collaborations between multiple stakeholders can be fostered to holistically manage landscapes for biodiversity conservation. https://lnkd.in/dGwj7hcC  

Exploring occupancy modelling to understand forest fragmentation 🌿 Inspired by the methodologies outlined in Ramiadantsoa et al. (2015, 10.1371/journal.pone.0132126), I developed a Python-based project 🐍 to examine how forest fragmentation impacts species occupancy and distribution over time. Using stochastic patch occupancy modeling as a foundation, I aimed to adapt and apply similar concepts in a grid-based framework. The model and approach Forest fragmentation, often a result of human activities, divides continuous habitats into smaller patches, creating challenges for species survival 🐾. My model classifies forest cover into three categories: intact, degraded, and non-forest 🌳. By calculating habitat suitability for each grid cell, I simulate how species occupancy changes over time. Key Results 1. Patch dynamics: early fragmentation results in an increase in smaller, isolated patches. However, over time, many of these patches are lost due to local extinctions or integration into unsuitable areas. 2. Occupancy trends: species occupancy probabilities decline significantly, nearing zero as habitat connectivity decreases. 3. Landscape metrics analysis: an analysis of patch number, size, and connectivity over time reveals a shift from fragmented landscapes with many small patches to fewer, larger fragments with reduced habitat suitability. Moving forward While this is an early-stage project, it highlights the importance of habitat connectivity and its role in maintaining biodiversity 🌍. Future improvements will focus on expanding the model to incorporate additional species groups and metrics for better understanding of ecological resilience. Reference: Ramiadantsoa T., Ovaskainen O., Rybicki J., Hanski I. (2015). Large-Scale Habitat Corridors for Biodiversity Conservation: A Forest Corridor in Madagascar. PLOS ONE, 10(7): e0132126. doi:10.1371/journal.pone.0132126 #ForestFragmentation #BiodiversityConservation #OccupancyModeling #PythonForEcology #LandscapeEcology #HabitatConnectivity #MetapopulationDynamics #EcologicalModeling