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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.
Long-term changes of the Wildland-Urban Interface in the Polish Carpathians
The Wildland–Urban Interface (WUI) is the area where houses and wildland vegetation
meet or intermingle, which causes many environmental problems. The current WUI is widespread in
many regions, but it is unclear how the WUI evolved, especially in regions where both houses and
forest cover have increased. Here we compared WUI change in the Polish Carpathians for 1860 and
2013 in two study areas with different land use history. Our western study area experienced gradual
forest increase and housing growth over time, while the eastern study area was subject to a shock
due to post-war resettlements, which triggered rapid reforestation. We found that in both study
areas WUI extent increased from 1860 to 2013 (41.3 to 54.6%, and 12.2 to 33.3%, in the west and east,
respectively). However the causes of WUI growth were very different. In the western study area new
houses were the main cause for new WUI, while in the eastern study area forest cover increase was
more important. Our results highlight that regions with similar current WUI cover have evolved very
differently, and that the WUI has grown rapidly and is widespread in the Polish Carpathians.
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Recognizing the “sparsely settled forest”: multi-decade socioecological change dynamics and community exemplars
Sparsely settled forests (SSF) are poorly studied, coupled natural and human systems involving rural communities
in forest ecosystems that are neither largely uninhabited wildland nor forests on the edges of urban areas.
We developed and applied a multidisciplinary approach to define, map, and examine changes in the spatial
extent and structure of both the landscapes and human populations of SSF in the United States. We estimated
that the SSF in the contiguous United States, which are home to only 6–7% of the population, account for over
60% of all forested land and over 30% of all land. From 1990 to 2010 SSF declined in area by 16%, changing
little overall but declining markedly in proximity to urban perimeters. A PCA ordination and cluster analysis of
the human and landscape characteristics of SSF areas revealed complex and regionally variable patterns. Very
broadly, SSF in the far northern and western states are less densely settled and more amenity driven, while the
southeastern states north through Pennsylvania and Ohio are more densely settled and more agricultural. The
socioeconomic characteristics of SSF are often quite variable at fine scales, especially in proximity to urban
areas. Our improved multidisciplinary understanding of SSF raises important questions about regional differences
in the dynamics, structure and future socioeconomic trajectories of these forests. To best manage these
landscapes for the sake of both human and natural systems, SSF need to be considered a distinct land classification
in their own right, not merely perceived as fuzzy boundaries around wild lands or urban areas.
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Widespread forest cutting in the aftermath of World War II captured by broad-scale historical Corona spy satellite photography
Wars have major economic, political and human implications, and they can strongly affect environment and land
use, not only during the conflicts, but also afterwards. However, data on the land use effects of wars is sparse,
especially for World War II, the largest war in history. Our goal was to quantify and understand the time-lagged
land use effects of WWII in Romania, by applying Structure from Motion technology to 1960s Corona spy satellite
photography. We quantified forest cutting across Romania from 1955 to 1965. This was a period when
Romania's economy recovered from the war and when Romania established close economic ties to the Soviet
Union, and when the Romanian government made reparation payments to the Soviet Union. To understand the
effects of war, we developed an accurate and fast method to orthorectify high-resolution Corona photography in
mountain areas, and rectified scanned Corona photography based on Structure from Motion technology. Our
study area of 212,000 km2 was covered by 208 Corona film strips, which we rectified with an overall average
accuracy of 14.3 m. We identified 530,000 ha of forest cuts over this time period, the rate of which is three times
higher than contemporary cutting rates. Our results highlight that the environmental and land use effects of
WWII were substantial in Romania, due to reparation payments, post-war policies regarding resource exploitation,
and technological and infrastructural development. Our research provides quantitative evidence of
how wars can cause time-lagged and long-term effects on the environment. Methodologically, we advance remote
sensing science by pioneering a new approach to orthorectify Corona photography for large areas effectively.
Corona data are available globally. Our approach facilitates the extension of the data record of space
borne observation of the earth by one to two decades earlier than what is possible with satellite datasets.
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Wildlife population changes across Eastern Europe after the collapse of socialism
When political regimes fall, economic conditions change and wildlife protection can be undermined. Eastern
European countries experienced turmoil following the collapse of socialism in the early 1990s, raising the
question of how wildlife was affected. We show that the aftermath of the collapse changed the population
growth rates of various wildlife taxa. We analyzed populations of moose (Alces alces), wild boar (Sus scrofa),
red deer (Cervus elaphus), roe deer (Capreolus capreolus), brown bear (Ursus arctos), Eurasian lynx (Lynx
lynx), and gray wolf (Canis lupus) in nine countries. Population growth rates changed in 32 out of 49 time
series. In the countries that reformed slowly, many species exhibited rapid population declines, and
population
growth rates changed in 83% of the time series. In contrast, in countries with fast post-socialism
reforms, many populations increased rapidly, and growth rates changed in only 48% of time series. Our
results suggest that the direction and frequency of the changes were associated with socioeconomic
conditions,
and that wildlife populations can be greatly affected by socioeconomic upheavals.
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Improving the mapping of crop types in the Midwestern U.S. by fusing Landsat and MODIS satellite data.
Mapping crop types is of great importance for assessing agricultural production, land-use patterns, an the environmental effects of agriculture. Indeed, both radiometric and spatial resolution of Landsat’s sensor images are optimized for cropland monitoring. However, accurate mapping of crop types require frequent cloud-free images during the growing season, which are often not available, and this raises th question of whether Landsat data can be combined with data from other satellites. Here, our goal is t evaluate to what degree fusing Landsat with MODIS Nadir Bidirectional Reflectance Distribution Functio (BRDF)-Adjusted Reflectance (NBAR) data can improve crop-type classification. Choosing either one o two images from all cloud-free Landsat observations available for the Arlington Agricultural Researc Station area in Wisconsin from 2010 to 2014, we generated 87 combinations of images, and used eac combination as input into the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorith to predict Landsat-like images at the nominal dates of each 8-day MODIS NBAR product. Bot the original Landsat and STARFM-predicted images were then classified with a support vector machin (SVM), and we compared the classification errors of three scenarios: 1) classifying the one or two origina Landsat images of each combination only, 2) classifying the one or two original Landsat image plus all STARFM-predicted images, and 3) classifying the one or two original Landsat images togethe with STARFM-predicted images for key dates. Our results indicated that using two Landsat images as th input of STARFM did not significantly improve the STARFM predictions compared to using only one, an predictions using Landsat images between July and August as input were most accurate. Including al STARFM-predicted images together with the Landsat images significantly increased average classificatio error by 4% points (from 21% to 25%) compared to using only Landsat images. However, incorporatin only STARFM-predicted images for key dates decreased average classification error by 2% points (fro 21% to 19%) compared to using only Landsat images. In particular, if only a single Landsat image was available adding STARFM predictions for key dates significantly decreased the average classification error b 4 percentage points from 30% to 26% (p < 0.05). We conclude that adding STARFM-predicted images ca be effective for improving crop-type classification when only limited Landsat observations are available but carefully selecting images from a full set of STARFM predictions is crucial. We developed an approac to identify the optimal subsets of all STARFM predictions, which gives an alternative method of featur selection for future research.
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Nineteenth century land-use legecies affect contemporary land abandonment in the Carpathians
Historical land use may shape landscapes for
centuries into the future, but it remains unclear how much
land-use legacies affect contemporary land use. Knowing
for how long and how strongly land-use legacies affect
agricultural systems is important for contemporary landuse
planning and conservation. We assessed the effect of
nineteenth-century agricultural legacies for contemporary
agricultural abandonment by integrating historic maps and
satellite imagery in the Carpathian region. We modeled the
choice of agricultural land, and the legacies of Habsburg
and Socialist regimes, while controlling for agroecological,
accessibility and sociopolitical variation.
Farming during the Habsburg era was concentrated in agroecologically
suitable areas, but socialist agricultural
expansion occurred mostly in less suitable areas, leading to
subsequent abandonment. In addition, our results showed
that historic land use affected abandonment even 100 years
later. Although legacies diminished over time, their effects
were amplified when political transformations occurred,
likely due to land tenure systems, land owner attitudes,
cultural values and differences in land improvement over
time. Taken together, land-use legacies and shifts in
political systems can constrain current land management
and possible future land-use options, suggesting that contemporary
land-use decisions
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Quasi-experimental methods enable stronger inferences from observational data in ecology
Many systems and processes in ecology cannot be experimentally controlled, either because the temporal and spatial scales are
too broad, or because it would be unethical. Examples include large wildfires, alternative conservation strategies, removal of top
predators, or the introduction of invasive species. Unfortunately, many of these phenomena also do not occur randomly in time or
space, and this can lead to different biases (selection bias, unobserved variable bias) in statistical analyses. Economics has evolved
largely without experiments, and developed statistical approaches to study “quasi-experiments”, i.e., situations were changes
in time or space reveal relationships even in the absence of a controlled experiment. The goal of our paper was to compare and
evaluate four quasi-experimental statistical approaches commonly used in economics, (1) matching, (2) regression discontinuity
design, (3) difference-in-differences models, and (4) instrumental variables, in terms of their relevance for ecological research.
We contrast the strengths and weaknesses of each approach and provide a detailed tutorial to demonstrate these approaches. We
suggest that quasi-experimental methods offer great potential for investigating many phenomena and processes in ecological
and coupled human-natural systems. Furthermore, quasi-experimental methods are common in environmental policy research
and policy recommendations by ecologists may be more valuable when based on these methods.
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The effect of protected areas on forest disturbance in the Carpathian Mountains 1985-2010
Protected areas are a cornerstone for forest protection, but they are not always effective during
times of socioeconomic and institutional crises. The Carpathian Mountains in Eastern Europe are an ecologically
outstanding region, with widespread seminatural and old-growth forest. Since 1990, Carpathian
countries (Czech Republic, Hungary, Poland, Romania, Slovakia, and Ukraine) have experienced economic
hardship and institutional changes, including the breakdown of socialism, European Union accession, and a
rapid expansion of protected areas. The question is how protected-area effectiveness has varied during these
times across the Carpathians given these changes. We analyzed a satellite-based data set of forest disturbance
(i.e., forest loss due to harvesting or natural disturbances) from 1985 to 2010 and used matching statistics
and a fixed-effects estimator to quantify the effect of protection on forest disturbance. Protected areas in the
Czech Republic, Slovakia, and the Ukraine had significantly less deforestation inside protected areas than
outside in some periods; the likelihood of disturbance was reduced by 1–5%. The effectiveness of protection
increased over time in these countries, whereas the opposite was true in Romania. Older protected areas were
most effective in Romania and Hungary, but newer protected areas were more effective in Czech Republic,
and Poland. Strict protection (International Union for Conservation of Nature [IUCN] protection category
Ia-II) was not more effective than landscape-level protection (IUCN III-VI). We suggest that the strength of
institutions, the differences in forest privatization, forest management, prior distribution of protected areas,
and when countries joined the European Union may provide explanations for the strikingly heterogeneous
effectiveness patterns among countries. Our results highlight how different the effects of protected areas can
be at broad scales, indicating that the effectiveness of protected areas is transitory over time and space and
suggesting that generalizations about the effectiveness of protected areas can be misleading.
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The signature of human pressure history on the biogeography of body mass in tetrapods
Aim: Examining the biogeography of body size is crucial for understanding how animal communities
are assembled and maintained. In tetrapods, body size varies predictably with temperature,
moisture, productivity seasonality and topographical complexity. Although millennial-scale human
pressures are known to have led to the extinction of primarily large-bodied tetrapods, human pressure
history is often ignored in studies of body size that focus on extant species. Here, we analyse
11,377 tetrapod species of the Western Hemisphere to test whether millennial-scale human pressures
have left an imprint on contemporary body mass distributions throughout the tetrapod
clade.
Location: Western Hemisphere.
Time period: Contemporary.
Major taxa studied: Tetrapods (birds, mammals, amphibians and reptiles).
Methods: We mapped the distribution of assemblage-level median tetrapod body mass at a resolution
of 110 km across the Western Hemisphere. We then generated multivariate models of
median body mass as a function of temperature, moisture, productivity seasonality and topographical
complexity, as well as two variables capturing the history of human population density and
human-induced land conversion over the past 12,000 years. We controlled for both spatial and
phylogenetic autocorrelation effects on body mass–environment relationships.
Results: Human pressures explain a small but significant portion of geographical variation in
median body mass that cannot be explained by ecological constraints alone. Overall, the median
body mass of tetrapod assemblages is lower than expected in areas with a longer history of high
human population density and land conversion, but there are important differences among tetrapod
classes.
Main conclusions: At this broad scale, the effect of human pressure history on tetrapod body
mass is low relative to that of ecology. However, ignoring spatial variation in the history of human
pressure is likely to lead to bias in studies of the present-day functional composition of tetrapod
assemblages, at least in areas that have long been influenced by humans.
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