Spatial Analysis For Conservation and Sustainability
Land Use
Land use change is currently the largest threat to biodiversity, and exacerbates the detrimental effects of climate change. We are interested in novel types of land use change, such as housing growth in the WUI, and widespread land abandonment after socioeconomic shocks, and how such changes affect biodiversity.
Understandingof the vulnerabilityof populationsexposedto wildfires is limited.We usedan index from the U.S.Centersfor DiseaseControl and Preventionto assessthe socialvulnerabilityof populationsexposedto wildfirefrom 2000–2021in California,Oregon,and Washington,whichaccountedfor 90%of exposures in the westernUnitedStates. The numberof peopleexposedto fire from 2000–2010to 2011–2021increasedsubstantially, withthe largest increase,nearly250%,for peoplewithhighsocialvulnerability. In Oregonand Washington,a higherpercentageof exposedpeoplewere highlyvulnerable (>40%)thanin California(~8%).Increasedsocialvulner-abilityof populationsin burnedareas was the primarycontributorto increasedexposure of the highlyvulner-able in California,whereas encroachmentof wildfires on vulnerable populationswas the primarycontributorinOregonand Washington.Our resultsemphasizethe importanceof integrating the vulnerabilityof at-riskpop-ulationsin wildfire mitigation and adaptation plans.
The Wildland-Urban Interface (WUI) is the area where natural vegetation is close to housing and area of concern due to various negative consequences for humans and the environment including fire ignitions, landscape fragmentation and human-wildlife interactions. The WUI is a global phenomenon, and widespread in many countries but long-term WUI dynamics and the main factors causing WUI growth are unknown. Our goal was to assess WUI changes in the Polish Carpathians since the mid-19th century, based on high-resolution spatial data for 1860s, 1970s and 2013. We found that WUI covered already 30% of the study area in the 1860s but grew to cover nearly half by 2013, especially at lower elevations. Detailed analysis of WUI determinants confirmed the areas closer to regional administrative centres or located on steep slopes were more WUI-prone. Tourist trail density also fostered WUI occurrence. We conclude that in Central Europe, with a long history of human settlements and agricultural activities, WUI has been a persistent landscape feature for centuries, but increased in area in recent decades due to widespread abandonment of agricultural land combined with development of new residential areas.
Socioeconomic shocks can cause regime shifts in land use, but even during shocks, and when land use change is widespread, some areas persist in their land use. The question is what makes these areas more resistant. Our research goal was to find out what explains where arable farming persisted despite a major socioeconomic shock of forced post-war displacements. Our study area were 291 villages in the Polish Carpathians where abandonment due to the forced displacement of the Ukrainian population after WWII was widespread. We compared prewar arable land with 1990 CORINE Land Cover data to quantify land-use change throughout the socialist period. We applied logistic regression with economically relevant environmental and access-related variables, and assessed the explanatory power of our models and relative importance of determinants. Forty years after forced displacements, arable farming persisted only in a small portion of what had been farmed in the 1940s (16 %), while the majority of former arable land converted to forests (54 %) or grasslands (22 %). Arable farming persisted mainly in areas with high accessibility that had oak-hornbeam forest as potential natural vegetation, on less steep slopes, and at lower elevations. Our models predicting agricultural abandonment leading to reforestation performed well (R2 = 0.57), but our model of persistent agriculture had low explanatory power (R2 = 0.26) as did models of conversion to grassland (R2 = 0.24). We therefore conclude that agricultural persistence is driven by different factors than agricultural land abandonment. In the long term, after arable farming ceases, areas can either be completely abandoned or convert to less intensive grassland use. These long-term changes have strong effects on biodiversity and ecosystem services, but are not well predicted by environmental and access-related determinants. Our findings can help to develop strategies and policies for areas affected by agricultural land abandonment caused by depopulation, and other socioeconomic shocks, and highlight the need to understand not only why arable land is abandoned, but also what determines its long-term fate.
The wildland – urban interface (WUI) is the zone where human settlements are in or near areas of fire-prone wildland vegetation. The WUI is widespread and expanding, with detrimental consequences to human lives, property, and neighboring ecosystems. While the WUI has been mapped in many regions, Europe does not have a high resolution WUI map to date. Moreover, while most WUI research has been focused on quantifying spatial and temporal patterns, little is known about the relationship between the WUI and the socioeconomic conditions that drive its formation. Here, we present the first high-resolution map of the European WUI and provide the first macro-scale analysis of the relationship between the WUI and some of its potential drivers. We found that the WUI covers about 7.4 % of Europe, but its extent varies considerably both across and within countries, with subnational WUI cover varying from nearly zero to almost 90 %. WUI cover is significantly related to socioeconomic variables such as GDP per capita, the proportion of the population above 65 years old, population density, road density, and the proportion of protected areas, but these effects are complex and interactive. This suggests that WUI drivers are likely to differ across and within countries, and hints about the importance of both top-down and local socioeconomic processes in driving the WUI. Our new WUI map can facilitate local as well as regional-scale wildfire risk and ecological assessments that inform policy and management decisions aimed at reducing the detrimental outcomes of the WUI in Europe.
Wildfires and housing development have increased since the 1990s, presenting unique challenges for wildfire management. However, it is unclear how the relative influences of housing growth and changing wildfire occurrence have altered risk to homes, or the potential for wildfire to threaten homes. We used a random forests model to predict burn probability in relation to weather variables at 1-km resolution and monthly intervals from 1990 through 2019 in the Southern Rocky Mountains ecoregion. We quantified risk by combining the predicted burn probabilities with decadal housing density. We then compared the predicted burn probabilities and risk across the study area with observed values and quantified trends. Finally, we evaluated how housing growth and changes in burn probability influenced risk individually and combined. Fires burned 9055 km2and exposed more than 8500 homes from 1990 to 2019.Observed burned area increased 632% from the 1990s to the 2000s, which combined with housing growth, resulted in a 1342% increase in homes exposed.. Increases continued in the 2010s but at lower rates; burned area by 65% and exposure by 32%. The random forests model had excellent fit and high correlation with observations (AUC=0.88 andr=0.9). Observed values were within the 95% uncertainty interval for all years except 2016 (burned area) and 2000(exposure). However, our model overpredicted in years with low observed burned area and underpredicted in years with high observed burned area. Overpredictions in risk resulted in lower rates of change in predicted risk com-pared with change in observed exposure. Increases in risk between the 1990sand 2000s were primarily due to warmer and drier weather conditions and secondarily because of housing growth. However, increases between the 2000sand 2010s were primarily due to housing growth. Our modeling approach identifies spatial and temporal patterns of wildfire potential and risk, which is critical information to guide decision-making. Because the drivers behind risk shift over time, strategies to mitigate risk may need to account for multiple drivers simultaneously.
Accurate maps of gains in tree cover are necessary to quantify carbon storage, wildlife habitat, and land use changes. Satellite-based mapping of emerging smallholder woodlots in heterogeneous landscapes of sub-Saharan Africa is challenging. Our goal was to evaluate the use of time series to detect and map small woodlots (<1 ha) in Tanzania. We distinguished woodlots from other land cover types by woodlots’ distinct multi-year spectral time series. Woodlots exhibit greening from planting to maturity followed by browning at harvest. We compared two time series approaches: 1) a linear model of Tasseled Cap Wetness (TCW) and other indices, and 2) LandTrendr temporal segmentation metrics. The approaches had equivalent woodlot detection accuracy, but LandTrendr segments had lower accuracy for characterizing woodlot age. We tested the effect of the following factors on woodlot detection and mapping accuracy: the length of the time series (2009–2019), frequency of observations (all Landsat vs. only Landsat-8), spatial resolution (30-m Landsat vs. 10-m Sentinel-2), and woodlot age and size. Woodlot mapping accuracies were higher with longer time series (54% at 3-yrs vs 77% at 7-yrs). The accuracies also improved with more observations, especially when the time series was short (3-yrs Landsat-8 only: 54% vs. all-Landsat: 64%, p-value <0.001). Sentinel-2’s higher spatial resolution minimized commission errors even for short time series. Finally, less than half of young and small (<0.4 ha) woodlots were detected, suggesting considerable omission errors in our and other woodlot maps. Our results suggest that the accurate detection of woodlots is possible by analyzing multi-year time series of Landsat and Sentinel-2 data. Given the region’s woodlot boom, accurate maps are needed to better quantify woodlots’ contribution to carbon sequestration, livelihoods enhancement, and landscape management.
Wildfire risks to homes are increasing, especially in the wildland-urban interface (WUI), where wildland vegetation and houses are in close proximity. Notably, we found that more houses are exposed to and destroyed by grassland and shrubland fires than by forest fires in the United States. Destruction was more likely in forest fires, but they burned less WUI. The number of houses within wildfire perimeters has doubled since the 1990s because of both housing growth (47% of additionally exposed houses) and more burned area (53%). Most exposed houses were in the WUI, which grew substantially during the 2010s (2.6million new WUI houses), albeit not as rapidly as before. Any WUI growth increases wildfire risk to houses though, and more fires increase the risk to existing WUI houses.
Closing the research-implementation gap is key for advancing biodiversity conservation. One approach is to generate ecologically relevant spatial datasets that integrate easily with existing management plans. Our goal was to identify priority forest conservation areas in Argentina by combining species distributions, human footprint data, and existing forest zoning. We: (i) mapped potential habitat distributions of 70 plant and animal species associated with forests, and of recognized social and ecological importance, (ii) combined the species distributions with human footprint data to identify priority conservation areas, and (iii) evaluated the juxtaposition of our priority conservation areas with current forest management zones. We found that priority conservation areas (i.e., high number of species and low human footprint) are poorly protected by the current zoning scheme. While the Andean-Patagonian region had a substantial portion (57 %) of priority conservation areas in high protection zones, in four other forest regions we evaluated, only 16–37 % of priority areas had high protection levels. Of great concern are the Chaco and Espinal regions, where 36 % and 39 %, respectively, of priority conservation areas are in low protection zones, where conversion to other uses (row crops, livestock) is allowed. Our results provide new spatial information to managers and conservationists highlighting where current forest zoning performs well, and where it may warrant re-evaluation. Overall, our study highlights the value of integrating species distributions and human footprint maps into existing land use plans to guide conservation efforts in data-poor countries, and is an example of a strategy for closing the research-implementation gap.
Human activity is recognized as a major driver of changes in land cover, land use, and fire regimes that influence and disrupt ecosystems. The Wildland-Urban Interface (WUI) defines areas where low-density settlements overlap with high amounts of wildland vegetation cover and are a focal point for wildfire hazard risks. WUI land uses are expanding and cause many biotic and abiotic implications for the environment and ecosystem functionality, such as declining biodiversity, loss, and fragmentation of habitat. Therefore, we require spatial and temporal information to investigate the rate and extent of the WUI growth and assess its structure and composition for preventing wildfire hazard risk and monitoring its impacts on ecosystems.
Especially in the Mediterranean-climate biome, fire has an important ecological role, which put humans living within the Wildland-Urban Interface at high risk, and fire hazards in these regions have achieved media attention in recent years. Mapping the WUI is essential to quantify the extent of this increasing settlement in wildland vegetation-dominated areas. Standard land cover maps often do not include this widespread settlement type, while differentiating only either into high-density urban land uses or vegetation cover.
So far, the extent of the Wildland-Urban Interface and its growth has only been mapped for a few countries or regions based on national land cover products and census or build-location datasets. However, these datasets are only limited available, and therefore, limit our ability to consistently capture WUI area growth, its structures, and drivers.
Kira Pfoch is conducting a study aiming at filling this gap in data availability. Kira’s main objective is to map WUI growth within the Mediterranean-climate biome with the Landsat Archive. She investigates reasons for WUI growth that is likely to be associated with expanding human activities that lead to increasing settlements in natural landscapes. Kira further investigates the relation between WUI growth and changes in wildfire activities and characteristics, to assess whether increasing human influences affect fire activity within these landscapes. Finally, the impact and interaction of human activity, climate change, and wildfires affect the natural vegetation, and therefore, Kira studies vegetation type conversion concerning WUI growth across different regions within the Mediterranean climate biome.
In conclusion, Kira’s research will help determine to identify growing human-environment conflict and its impacts on fire and vegetation.
Landscapes are undergoing continuous transformation, with both natural and human factors causing the destruction of some habitats and the formation of others. While wildlife can adapt to natural changes, the current scale of human-made landscape alterations is much greater than nature’s ability to adapt. Some species can thrive in human-made landscapes, but others are at risk of extinction due to habitat loss.
Azerbaijan, a country in the Caucasus region with rich biodiversity and a long history of human-driven land cover changes. For conservation and sustainable management there, it is critical to understand the impacts of landscape changes on wildlife habitats. The changes in the Caucasus eco-region have accelerated in the 20th century due to population growth and Soviet nature-transformation efforts. A new study by Afag Rizayeva aims to understand the impact of these changes on the habitats of eight ungulate species, including common animals like wild boar and roe deer, as well as a rare species of gazelle. With landscapes constantly changing due to natural and human causes, it is increasingly important to understand how these changes are affecting wildlife populations.
Afag has developed the Caucasus land cover maps for the 1960s using former spy satellite images (Corona) and has analyzed the long-term changes in these landscapes using recent land cover maps derived from Landsat images. Her research begins by using the presence data of eight ungulate species, conducting species distribution modeling to evaluate their current ranges and the landscape features that are most important to each species.
Next, Afag will analyze the changes in land cover within each species’ range, determining stable areas, habitat gains and losses, and assessing the positive or negative effects of these changes on the species’ habitats. This will enable her to determine if the species can continue to use the same areas despite human activities, or if they require urgent land management solutions to protect them. The results of Afag’s study will help guide wildlife conservation planning and will be used by local NGOs and government agencies. As human impact on nature is a global issue, the methodological approach she develops in her research will have applications in other regions facing similar issues.
In conclusion, understanding the impact of long-term land cover changes on wildlife habitats is crucial for conservation and sustainable management. The research being conducted by Afag Rizayeva will provide valuable insights into this issue and help guide efforts to protect the wild species in Azerbaijan and beyond. Stay tuned!