Fence Removal Research Articles

Predicting the impact of targeted fence removal on connectivity in a migratory ecosystem.

Fencing is one of the most widely utilized tools for reducing human-wildlife conflict in agricultural landscapes. However, the increasing global footprint of fencing exceeds millions of kilometers and has unintended consequences for wildlife, including habitat fragmentation, movement restriction, entanglement, and mortality. Here, we present a novel and quantitative approach to prioritize fence removal within historic migratory pathways of white-bearded wildebeest (Connochaetes taurinus) across Kenya's Greater Masai Mara Ecosystem. Our approach first assesses historic and contemporary landscape connectivity of wildebeest between seasonal ranges by incorporating two sets of GPS tracking data and fine-scale fencing data. We then predict connectivity gains from simulated fence removal and evaluate the impact of different corridor widths and locations on connectivity and removal costs derived from locally implemented interventions. Within the study system, we found that modest levels of fence removal resulted in substantial connectivity gains (39%-54% improvement in connectivity for 15-140 km of fence line removed). By identifying the most suitable corridor site, we show that strategically placed narrow corridors outperform larger, more expensive interventions. Our results demonstrate how and where targeted fence removal can enhance connectivity for wildlife. Our framework can aid in identifying suitable and cost-effective corridor restoration sites to guide decision-makers on the removal of fences and other linear barriers. Our approach is transferable to other landscapes where the removal or modification of fences or similar barriers is a feasible mitigation strategy to restore habitat and migratory connectivity.

Successful forest restoration using plantation at high deer density: How neighboring vegetation drives browsing pressure and tree growth

Browsing can be an environmental stress to forest ecosystems, where the composition and structure of plant communities depend on the balance between ungulate browsing and the ability of plants to tolerate and acclimate to this stressor. Tree planting is a management tool for restoring forest whose integrity has been compromised by the intensity and repetition of browsing. This tool may be insufficient when the stress leading to forest degradation is ongoing. Balsam fir (Abies balsamea (L.) Mill.) plantations are used on Anticosti Island (Quebec, Canada) to restore winter habitat for white-tailed deer (Odocoileus virginianus Zimmermann, 1780). To promote natural regeneration and growth of planted firs that are the staple winter forage of deer, enclosures were temporarily erected and deer densities reduced to decrease browsing pressure. The stress induced by heavy browsing at the time of fence removal and the density of competitors in regenerating cutblocks, however, could compromise fir growth and forest recruitment. Our objective was to identify factors influencing browsing intensity and balsam fir’s growth following fence removal. We aimed to identify factors influencing lateral browsing intensity and number of trunk reiterations on fir at the landscape scale, including distance and size of the surrounding forests, and at the local scale through intraspecific density-dependence and interspecific associative effects. We then sought to identify the stressors most influencing balsam fir growth among browsing variables and a neighborhood crowding index (NCI). We measured browsing intensity and growth of 114 balsam firs 8 years following planting and again 2 and 4 years after dismantling two management enclosures. At the landscape scale, our results showed that when balsam fir was more than 150 m from a forest edge, the probability of browsing was close to zero and consistently a low percentage of shelter area surrounding a focal fir led to a decrease in browsing pressure. At the local scale, intensity of lateral browsing increased with the NCI of white spruce (Picea glauca (Moench) Voss). Fir growth was negatively influenced by the additive effects of browsing and NCI. Finally, our results showed that 19.7% (95 %CI: 4.5%, 42.6%) of the effect of the surrounding vegetation on growth was mediated by browsing. The success of forest ecosystem restoration through planting depends on density of neighboring tree species that can generate environmental stress by influencing growth indirectly through browsing as well as directly through competition for resources.

Estimating capercaillie Tetrao urogallus population size in Scotland from annual leks and counts of broods over the period 2010–2020

The population size of capercaille Tetrao urogallus in Scotland was estimated from annual counts of males at 151 known spring lek sites and 45 counts of males, females and their broods in August during the period 2010–2020, combined with published survival estimates. Population size declined from an estimated 580 birds (95% CL: 462–698) in 2011 to 304 (239–369) in 2020 and the extinction probability was 23% after 25 years, 95% after 50 years and 100% after 100 years. Removing mortality associated with collisions against fences lowered extinction probabilities to 0, 3 and 40% respectively, emphasizing fence removal as a management priority. Greatest declines occurred in Deeside and Donside, Morayshire and Ross‐shire and Perthshire and Trossachs. In the Badenoch and Strathspey stronghold, where an estimated 83% of males remain, numbers of occupied leks and lekking males have decreased in the last five years and are associated with reduced breeding success over the last 10 years. Our estimates of population size are only half that derived from the last official national survey in winter 2015/2016. We discuss possible reasons for this difference including underestimates from lek‐based surveys linked to male detection probabilities. Finally, we recommend improvements to the current annual monitoring scheme, including repeat counts at leks and use of novel remote acoustic devices and restoration of annual brood counts in remaining key forests.

Learning to See Through Obstructions With Layered Decomposition

We present a learning-based approach for removing unwanted obstructions, such as window reflections, fence occlusions, or adherent raindrops, from a short sequence of images captured by a moving camera. Our method leverages motion differences between the background and obstructing elements to recover both layers. Specifically, we alternate between estimating dense optical flow fields of the two layers and reconstructing each layer from the flow-warped images via a deep convolutional neural network. This learning-based layer reconstruction module facilitates accommodating potential errors in the flow estimation and brittle assumptions, such as brightness consistency. We show that the proposed approach learned from synthetically generated data performs well to real images. Experimental results on numerous challenging scenarios of reflection and fence removal demonstrate the effectiveness of the proposed method.

Vegetation Changes Following Large-scale Fence Removal Across a Protected Area Network Within the Kruger to Canyons Biosphere Reserve, South Africa

In the early 1990’s, reserves adjacent to Kruger National Park (KNP) removed their fences to create a continuous landscape within the Kruger to Canyons Biosphere Reserve. Understanding how these interconnected multi-management systems responded to changes in environmental factors and management regimes can help to maintain natural large-scale landscape heterogeneity and ecological resilience. Our objective was to analyze remote sensing-derived vegetation metric changes between the different management types pre- and post-fence removal. The study area included fourteen reserves and the central section of KNP. We calculated the residuals between TIMESAT-derived metrics (from AVHRR NDVI time series) and rainfall to analyze changes in vegetation from 1985 to 2006. We then compared vegetation-rainfall residuals between different management types pre- and post-fence removal using mean–variance plots, nonmetric multidimensional scaling plots, and permutational multivariate analysis of variance to statistically identify and analyze changes. All management types experienced increased greenness. Reserves that removed their fences had greater changes in vegetation post-fence removal compared to reserves that remained fenced and KNP. Our findings suggest managers may need to address landscape changes by implementing management regimes such as reducing artificial surface water to counterbalance increased grazing pressure as a result of increased animal mobility across artificially created resource gradients. Habitat connectivity within and between protected area networks can be achieved by removing fences across adjacent conservation areas thus potentially increasing ecological resilience, which is vital to effective long-term conservation.

De-Fencing and Multi-Focus Fusion Using Markov Random Field and Image Inpainting

Multi-focus image fusion aims at combining source information from differently focused images. Fusion of multi-focus images has great applications in machine vision. The paper focuses on removal of fence occlusions in multi-focus images. The proposed model extracts fence occlusion map using salient image features, and refined by morphological operators. Binary operators, and inpainting methods are used for fence removal and restoration. The proposed model estimates the fence area using statistical characteristics in focused regions. Similarly, binary filtering is used to perform thinning of enlarged areas for optimised restoration. The proposed model employs guided filtering for consistency verification. Fusion and restoration results are compared using several (reference and no-reference based) image quality metrics. Simulations show that proposed scheme achieves better results (visually and quantitatively) as compared to existing state-of-the-art techniques.

A robust and efficient image de-fencing approach using conditional generative adversarial networks

Image de-fencing is one of the most important aspects of recreational photography in which the objective is to remove the fence texture present in an image and generate an aesthetically pleasing version of the same image without the fence texture. In this paper, we present an automated and effective technique for fence removal and image reconstruction using conditional generative adversarial networks (cGANs). These networks have been successfully applied in several other domains of computer vision, focusing on image generation and rendering. Our approach is based on a two-stage architecture involving two cGANs in succession, in which the first cGAN generates the fence mask from an input fenced image, and the next one generates the final de-fenced image from the given input and the corresponding fence mask obtained from the previous cGAN. Training of these networks is carried out independently using suitable loss functions, and during the deployment phase, the above two networks are stacked together in an end-to-end manner to generate the de-fenced image from an unknown test image. Extensive qualitative and quantitative evaluations using challenging data sets emphasize the effectiveness of our approach over state-of-the-art de-fencing techniques. The data sets used in the experiments have also been made available for further comparison.

Factors driving the discovery and utilization of a newly available area by African elephants

AbstractFor large mammals, area expansion is a key conservation measure to prevent species’ decline and extinction. Yet, its success depends on whether animals discover and later use these areas. Here, using GPS data, we investigated how herds of elephants detected and used an area made available to them after the removal of a fence. We studied the elephants’ behaviour before and after the fence removal, accounting for seasonal changes in movement patterns. In contrast to previous studies, herds visited the newly available area within a month of the fence removal, and the maximum distance they moved into the new area was reached between 5 and 9 months after the fence removal. Yet, elephants did not preferentially visit the new area at night. By the second year, all herds had shifted their seasonal home ranges and incorporated the new area, in contrast to a previous range expansion event. Our analyses show that the regular proximity of elephants to the original fence, and the fact that the new area was generally composed of preferred habitats of the elephants, probably explained the rapid discovery and use of the area. Our study improves our understanding of animal exploration and the role of habitat quality, and thus may improve range expansion and corridor programmes.

Evaluating the impacts of white-tailed deer (Odocoileus virginianus) browsing on vegetation in fenced and unfenced timber harvests

Ensuring the recruitment of desired tree species is a primary goal when considering successful regeneration of timber harvests. Deer populations that are overabundant relative to forage availability within their local landscapes pose a considerable challenge to successful forest regeneration. We evaluated the short-term (<10 years) impact of white-tailed deer browsing on woody structure and composition in northcentral Pennsylvania. Specifically, we compared woody plant species density, height, and cover within 10 pairs of fenced and unfenced regenerating timber harvests. Percent of browsed stems was higher in unfenced harvests for red maple (Acer rubrum), oaks (Quercus spp.), Rubus spp., sassafras (Sassafras albidum), and witch hazel (Hamamelis virginiana). Stem density did not differ between fenced and unfenced harvests for any species except Rubus spp., which was greater in the former. However, height of serviceberry (Amalanchier spp.), sassafras, northern red oak (Quercus rubra), Rubus spp., and red maple was taller in fenced harvests. Both vertical and horizontal vegetation density were greater in fenced harvests, suggesting a more structurally complex understory in fenced harvests. Rubus spp. and tall (>1.5 m) sapling cover were greater in fenced harvests, while unfenced harvests had greater forb, fern, and blueberry/huckleberry (Vaccinium spp./Gaylussacia spp.) cover. Our results suggest that browsing by deer in the years initially (<10 years) following timber harvest may not immediately impact woody species density, but can considerably reduce seedling height, overall horizontal and vertical structure, and composition of vegetation strata. Reduced sapling height and greater prevalence of blueberry/huckleberry, forbs, and ferns in unfenced harvests threaten the successful recruitment of desired species into the future overstory. Our results from large, operational-scale timber harvests combined with those from previous small-scale studies stress the potential value of deer exclusion fencing to achieve successful forest regeneration. Future research should examine the timing of fence removal to achieve forest regeneration success, while also providing deer access to available foraging opportunities during the later portion of stand initiation.

Real-world fence removal from a single-image via deep neural network

At public space such as a zoo and sports facilities, the presence of fence often annoys tourists and professional photographers. There is a demand for a post-processing tool to produce a non-occluded view from an image or video. This “de-fencing” task is divided into two stages: one is to detect fence regions and the other is to fill the missing part. For a decade or more, various methods have been proposed for video-based de-fencing. However, only a few single-image-based methods are proposed. In this paper, we mainly focus on single-image fence removal. Conventional approaches suffer from inaccurate and non-robust fence detection and inpainting due to less content information. To solve these problems, we combine novel methods based on a deep convolutional neural network (CNN) and classical domain knowledge in image processing. In the training process, we are required to obtain both fence images and corresponding non-fence ground truth images. Therefore, we synthesize natural fence image from real images. Moreover, spacial filtering processing (e.g. a Laplacian filter and a Gaussian filter) improves the performance of the CNN for detecting and inpainting. Our proposed method can automatically detect a fence and generate a clean image without any user input. Experimental results demonstrate that our method is effective for a broad range of fence images.

Single-Image Fence Removal Using Deep Convolutional Neural Network

In public spaces such as zoos and sports facilities, the presence of fences often annoys tourists and professional photographers. There is a demand for a post-processing tool to produce a non-occluded view from an image or video. This “de-fencing” task is divided into two stages: one to detect fence regions and the other to fill the missing part. For over a decade, various methods have been proposed for video-based de-fencing. However, only a few single-image-based methods are proposed. In this paper, we focus on single-image fence removal. Conventional approaches suffer from inaccurate and non-robust fence detection and inpainting due to less content information. To solve these problems, we combine novel methods based on a deep convolutional neural network (CNN) and classical domain knowledge in image processing. In the training process, we are required to obtain both fence images and corresponding non-fence ground truth images. Therefore, we synthesize natural fence images from real images. Moreover, spacial filtering processing (e.g. a Laplacian filter and a Gaussian filter) improves the performance of the CNN for detection and inpainting. Our proposed method can automatically detect a fence and generate a clean image without any user input. Experimental results demonstrate that our method is effective for a broad range of fence images.

Removing fences from sweep motion videos using global 3D reconstruction and fence-aware light field rendering

Diminishing the appearance of a fence in an image is a challenging research area due to the characteristics of fences (thinness, lack of texture, etc.) and the need for occluded background restoration. In this paper, we describe a fence removal method for an image sequence captured by a user making a sweep motion, in which occluded background is potentially observed. To make use of geometric and appearance information such as consecutive images, we use two well-known approaches: structure from motion and light field rendering. Results using real image sequences show that our method can stably segment fences and preserve background details for various fence and background combinations. A new video without the fence, with frame coherence, can be successfully provided.

Comparing Habitat Suitability and Connectivity Modeling Methods for Conserving Pronghorn Migrations

Terrestrial long-distance migrations are declining globally: in North America, nearly 75% have been lost. Yet there has been limited research comparing habitat suitability and connectivity models to identify migration corridors across increasingly fragmented landscapes. Here we use pronghorn (Antilocapra americana) migrations in prairie habitat to compare two types of models that identify habitat suitability: maximum entropy (Maxent) and expert-based (Analytic Hierarchy Process). We used distance to wells, distance to water, NDVI, land cover, distance to roads, terrain shape and fence presence to parameterize the models. We then used the output of these models as cost surfaces to compare two common connectivity models, least-cost modeling (LCM) and circuit theory. Using pronghorn movement data from spring and fall migrations, we identified potential migration corridors by combining each habitat suitability model with each connectivity model. The best performing model combination was Maxent with LCM corridors across both seasons. Maxent out-performed expert-based habitat suitability models for both spring and fall migrations. However, expert-based corridors can perform relatively well and are a cost-effective alternative if species location data are unavailable. Corridors created using LCM out-performed circuit theory, as measured by the number of pronghorn GPS locations present within the corridors. We suggest the use of a tiered approach using different corridor widths for prioritizing conservation and mitigation actions, such as fence removal or conservation easements.

Appeasing Pheromone Inhibits Cortisol Augmentation and Agonistic Behaviors During Social Stress in Adult Miniature Pigs

Pairing and physical confrontation In adult sows causes social stress reactions and aggressive behaviors. Recently, maternal pig skin secretions were Isolated and a mixture containing several fatty acids, now called pig appeasing pheromone (PAP), was synthesized. In this study, we Investigated the effects of PAP on social and Immune stress response In adult female miniature pigs. PAP or vehicle solvents were sprayed Into the pens of Individually housed adult sows. A two-week exposure to the pheromone did not alter basal salivary Cortisol levels or clrcadlan rhythms. Following this treatment, the animals were paired and placed In a new pen that was divided with a wire-mesh fence. Although salivary cortisol Increased markedly In the vehicle-treated group, the PAP-treated group exhibited a drastic Inhibition of cortisol secretion. This effect was sustained even after they were allowed to physically Interact following fence removal. Moreover, the latency time of agonistic behaviors, such as escaping or biting, was significantly extended after PAP exposure. When lipopolysaccharide was Injected Intramuscularly, Cortisol levels, rectal temperatures, and lying time lengths Increased substantially. No differences were observed between the pheromone-treated and untreated groups. These results suggest that this synthetic pheromone alleviates social stress In adult pigs, although It does not affect Immune stress responses. Our findings demonstrate the potential benefit of this pheromone In field applications and clinical disciplines relating to adult female pigs.

The response of an elephant population to conservation area expansion: Phinda Private Game Reserve, South Africa

Continuous human population expansion pressure on conservation ecosystems restricts wildlife areas, and necessitates active management. In areas of changing land-use and increasing human–animal conflict, responses of wildlife to direct human interventions can inform managers and planners. During August 2004, the boundary fences between Phinda Private Game Reserve and two neighbouring reserves were removed. This study examined behavioural responses of the resident elephants. Older, recently introduced bulls moved into the new area during the first month after fence removal, while younger resident bulls and family groups took between five and eight months. Initially family groups only moved into the new area at night and spent minimal time there, while older bulls spent longer periods of time, regardless of time of day. One year after fence removal, most of the elephants had only expanded their home ranges slightly into the new area. One of the findings of this study is that elephants appear to act cautiously in exploring new areas and responded by moving into the area slowly and over a relatively long time period. This cautious behaviour reduced through time as animals became more familiar with the area. The spatial scale of response of the elephants was relatively small, while the temporal scale of response was relatively large.

Sediment and phosphorus removal from simulated storm runoff with compost filter socks and silt fence

In 2005, the US Environmental Protection Agency National Menu of Stormwater Best Management Practices, National Pollutant Discharge Elimination System Phase II for Construction Sites, listed compost filter socks as an approved best management practice for controlling storm runoff and sediment on construction sites. Like most new technologies used to control sediment on construction sites, little has been done to evaluate their performance relative to conventional sediment control barriers, such as silt fences. The objectives of this study were (1) to determine and compare the sediment removal efficiency of silt fence and compost filter socks, (2) to determine if the addition of polymers to compost filter socks could reduce sediment and phosphorus loads, (3) to determine relationships between compost filter media particle size distribution and pollutant removal efficiency and hydraulic flow rate. Simulated rainfall was applied to soil chambers packed with Hatboro silt loam on a 10% slope. All runoff was collected and analyzed for hydraulic flow rate, volume, total suspended solids (TSS) concentration and load, turbidity, and total and soluble P concentration and load. Based on 7.45 cm h^-1 (2.9 in hr^-1) of simulated rainfall-runoff for 30 minutes duration, bare soil (control) runoff TSS concentrations were between 48,820 and 70,400 mg L^-1 (6.5 oz gal^-1 and 9.4 oz gal^-1), and turbidity was between 19343 and 36688 Nephelometric Turbidity Units. Compost filter sock and silt fence removal efficiencies for TSS concentration (62% to 87% and 71% to 87%), TSS load (68% to 90% and 72% to 89%), and turbidity (53% to 78% and 54% to 76%) were nearly identical; however with the addition of polymers to the compost filter socks sediment removal efficiencies ranged from 91% to 99%. Single event support practice factors (P factor) for silt fence were between 0.11 and 0.29, for compost filter socks between 0.10 and 0.32, and for compost filter socks + polymer between 0.02 and 0.06. Total and soluble P concentration and load removal efficiencies were similar for compost filter socks (59% to 65% and 14% to 27%) and silt fence (63% and 23%). Although when polymers were added to the filter socks and installed on phosphorus fertilized soils, removal efficiencies increased to 92% to 99%. Compost filter socks restricted hydraulic flow rate between 2% and 22%, while the silt fence restricted between 5% and 29%. Significant correlations (<i>p</i> &lt; 0.05) were found between middle range particle sizes of compost filter media used in the filter socks and reduction of turbidity in runoff; however, hydraulic flow rate was a better indicator (stronger correlation) of total pollutant removal efficiency performance for compost filter socks and should be considered as a new parameter for federal and state standard specifications for this pollution prevention technology.