A spatially explicit impact assessment of road characteristics, road-induced fragmentation and noise on birds species in Cyprus

Effects of road and river networks on sediment connectivity in mountainous watersheds

Breeding bird diversity in relation to environmental gradients in China

British Columbia (BC), Canada, has a diverse landscape that provides breeding habitat for > 300 avian species, and the recent development of the BC Breeding Bird Atlas data set presents key information for exploring the landscape conditions which lead to biological richness. We used the volunteer-collected raw breeding bird evidence data set to analyze the effects of sampling biases on spatial distribution of observed breeding bird species and implemented regression tree analysis (Random Forests) to examine the influence of productivity, ambient energy, and habitat heterogeneity on independently measured breeding bird richness. Results indicated that total breeding species richness is correlated with total survey effort (alpha < 0.001). By stratifying species richness by survey effort, we observed that ambient energy is the top-ranked environmental predictor of breeding bird richness across BC, which, when used in combination with a number of other environmental variables, explains -40% of the variation in richness. Using our modeled relationships, we predicted breeding bird species richness in the areas of BC not presently surveyed between three and six hours. The majority of the productive Boreal Plains, the southern portion of the Taiga Plains region, the lowlands of the Southern and Central Interior, along the Rocky Mountain Trench, and the coastal areas of the Georgia Depression are predicted to have the highest categories of breeding richness (35-57 unique species). Our results support ongoing species diversity gradient research, which identifies ambient energy as an important factor influencing species diversity distributions in the Northern Hemisphere. By linking breeding bird richness to environmental data derived from remotely sensed data and systematically collected climate data, we demonstrate the potential to monitor shifts in ambient energy as a surrogate for vertebrate habitat condition affecting population levels. By analyzing the influence of survey effort on species richness metrics, we also highlight the need to consider adding attributes to the raw breeding bird data set to describe observer experience, such as hours or seasons spent surveying, and provide survey dates to allow greater flexibility for removing survey bias. These additions can increase the utility of atlas data for species richness studies useful for conservation planning.

Summary1. The effects of roads on wildlife populations are widespread and well documented. Many studies have shown that bird abundance, occurrence and species richness are reduced near roads, with the largest reductions where traffic levels are high. Negative correlations have been reported between bird richness/abundance and traffic noise but the possible causes of road effects are inter‐correlated. It is important to disentangle the different effects so that appropriate mitigation measures can be implemented.2. We tested the hypothesis that traffic noise is a key negative effect by testing three predictions: (i) bird richness/abundance should reach a maximum at the same distance from roads that traffic noise reaches a minimum; (ii) the effect of traffic noise on bird richness/abundance should be stronger than the effect of distance from the road on bird richness/abundance; and (iii) sites with more traffic noise at a given distance from the road should show lower bird richness/abundance than sites with less traffic noise at the same distance.3. We collected breeding bird occurrence and traffic noise data along twenty 600‐m transects perpendicular to roads at 10 high‐traffic road sites.4. Traffic noise decreased and bird species richness increased with increasing distance from the roads. However, none of the predictions derived from the traffic noise hypothesis was supported.5. Synthesis and applications. Our results suggest that traffic noise is not the main cause of the negative relationship between bird species richness/abundance and proximity to roads. Instead, traffic mortality may be the main mechanism causing this relationship. We suggest that mitigation of road impacts on birds should focus mainly on reducing mortality rather than reducing traffic noise. In particular, engineering road surfaces, tyres and vehicle engines to reduce noise would not mitigate road effects; instead, structures to keep birds away from roads or force them to fly above the traffic would be more effective.

The road network has both positive and negative ecological effects, and understanding these helps identify environmentally preferable solutions for transportation policy and planning. We investigated the relationship between road density and habitat type richness of Greek protected areas. We used digital vector maps of 214 sites included in the Greek Natura 2000 network. We calculated road density for the terrestrial part of each site and correlated it with habitat type richness. Average road density of protected areas (0.377 km/ km2) was significantly lower than the national road density of Greece (0.446 km/km2). We identified 32 sites that were not intersected by roads. These roadless sites were located at mountain tops, at islets, or in remote coastal zones. Overall we found no significant correlation between road density and habitat type richness. We suggest that the effect of road networks on habitat type richness is less apparent at landscapes with long history of human presence, because the landscape (and its habitat diversity) has coevolved with human activities over the past millennia. Our analysis provides a step towards quantifying the effect of road density on the diversity of habitats and consequently on species of conservation interest in international networks of protected areas such as the European Natura 2000 network.

Environmental heterogeneity enhances species richness by creating niches and providing refugia. Spatial variation in climate has a particularly strong positive correlation with richness, but is often indirectly inferred from proxy variables, such as elevation and related topographic heterogeneity indices, or derived from interpolated coarse‐grain weather station data. Our aim was to develop new remotely sensed metrics of relative temperature and thermal heterogeneity, compare them with proxy measures, and evaluate their performance in predicting species richness patterns. We analyzed Landsat 8's Thermal Infrared Sensor data, calculated two thermal metrics during summer and winter, and compared their seasonal spatial patterns with those of elevation and topographic heterogeneity. We fit generalized least squares models to evaluate each variable's effect in predicting seasonal bird richness using data from the North American Breeding Bird Survey. Generally speaking, neither elevation nor topographic heterogeneity were good proxies for temperature or thermal heterogeneity, respectively. Relative temperature had a non‐linear relationship with elevation that was negatively quadratic in summer, but slightly positively quadratic in winter. Topographic heterogeneity had a stronger positive relationship with thermal heterogeneity in winter than in summer. The magnitude and direction of elevation–temperature and topographic heterogeneity–thermal heterogeneity relationships in each season also varied substantially across ecoregions. Remotely sensed metrics of relative temperature and thermal heterogeneity improved the predictive performance of species richness models, and both thermal variables had significant effects on bird richness that were independent of elevation and topographic heterogeneity. Thermal heterogeneity was positively related to total breeding bird richness, migrant breeding bird richness and resident bird richness, whereas topographic heterogeneity was negatively related to total breeding richness and unrelated to migrant or resident bird richness. Because thermal and topographic heterogeneity had contrasting seasonal patterns and effects on richness, they must be carefully contextualized when guiding conservation priorities.

Bird abundance trends have been correlated with habitat changes in urban developed areas but have seldom been associated with specific patterns of urban-related habitat changes. We examined breeding bird–habitat relationships in 334 random plots ranging from undisturbed natural to highly developed land in Tucson, Arizona. In each plot we quantified 19 variables describing three land cover patterns (habitat physiognomy, floristics, and spatial relationships of native habitat fragments) and correlated them with abundances of 21 bird species. Abundances of 17 bird species were associated with variables describing land cover pattern. In addition, we correlated abundance, species richness, and evenness for three bird guilds (non-natives, natives, and a native indicator guild) with land cover variables. Housing density best explained the variation in species richness for both the non-native (r2 = 0.79) and the indicator guilds (r2 = −0.69), whereas area of Upland Sonoran vegetative cover (r2 = 0.56) and distance from undisturbed washes (r2 = −0.56) correlated most strongly with the native-bird group. Finally, we developed and tested regression models predicting species richness for each bird guild. The following variables loaded into the predictive models: house density; percentage cover of paved areas; exotic, Upland Sonoran, and undisturbed riparian vegetation; and distance from undisturbed washes. The models explained 71% of the variation in non-native bird species richness, 56% of the variation in native bird species richness, and 60% of the variation in species richness for the indicator guild of birds. The correlations and regression models can be used to predict species richness responses to future residential development in the Tucson area.

The role of protected areas is for the long-term conservation of biodiversity. This study investigated the effectiveness of the Hadejia-Nguru Ramsar Wetlands Protected Areas in maintaining bird community. We assessed and compared species’ richness, relative abundance and conservation status of birds between Protected Areas (PAs) and Unprotected Areas (UPAs) of the wetland. The study was conducted from October to December, 2015. Point-count method was employed during the study. Forty-eight points of 100 m radius and 400 m intervals were surveyed in PAs and 51 points in the UPAs. A total of 42, 255 individual birds of 148 species’ belonging to 23 orders and 50 families were recorded. Uprotected Areas had 133 species and PAs 121 species (p = 0.4514), however, PAs had higher birds abundance than unprotected areas. The two areas shared a greater percentage of species composition by 85%. Two globally threatened species were also recorded, the European Turtle Dove Streptopelia turtur (Vulnerable) and Pallid Harrier Circus macrourus (Near Threatened). White-faced Whistling Duck Dendrocygna viduata, and Garganey Spatula querquedula were the dominant species in both areas. Results further revealed that PAs had slightly higher bird population with stable trend than UPAs, in contrast, though those with increasing population were more in UPAs. Overall, the population trend of birds in both habitats was found to be stable. Majority of resident species’ population trend were found to be on the increase, or stable, while intra- African and Palearctic migrants were found to be declining. This study highlights that not only PAs of the HNWs are important for bird conservation, but UPAs, too, are of great significance for the long-term conservation of the wetland bird community. Legal protection of certain wetland areas especially in the UPAs may help preserve larger bird species.Keywords: Bird conservation; Hadejia-Nguru Wetlands; protected and unprotected areas; threats.

Do unpaved, low-traffic roads affect bird communities?

Integrated spatial planning for biodiversity conservation and food production

Aim The partition of the geographical variation in Argentinian terrestrial mammal species richness (SR) into environmentally, human and spatially induced variation.Location Argentina, using the twenty‐three administrative provinces as the geographical units.Methods We recorded the number of terrestrial mammal species in each Argentinian province, and the number of species belonging to particular groups (Marsupialia, Placentaria, and among the latter, Xenarthra, Carnivora, Ungulates and Rodentia). We performed multiple regressions of each group's SR on environmental, human and spatial variables, to determine the amounts of variation explained by these factors. We then used a variance partitioning procedure to specify which proportion of the variation in SR is explained by each of the three factors exclusively and which proportions are attributable to interactions between factors.Results For marsupials, human activity explains the greatest part of the variation in SR. The purely environmental and purely human influences on all mammal SR explain a similarly high proportion of the variation in SR, whereas the purely spatial influence accounts for a smaller proportion of it. The exclusive interaction between human activity and space is negative in carnivores and rodents. For rodents, the interaction between environment and spatial situation is also negative. In the remaining placental groups, pure spatial autocorrelation explains a small proportion of the variation in SR.Main conclusions Environmental factors explain most of the variation in placental SR, while Marsupials seem to be mainly affected by human activity. However, for edentates, carnivores, and ungulates the pure human influence is more important than the pure spatial and environmental influences. Besides, human activity disrupts the spatial structure caused by the history and population dynamics of rodents and, to a lesser extent, of carnivores. The historical events and population dynamics on the one hand, and the environment on the other, cause rodent SR to vary in divergent directions. In the remaining placental groups the autocorrelation in SR is mainly the result of autocorrelation in the environmental and human variables.

Anthropogenic pressure in Czech protected areas over the last 60 years: A concerning increase

Protected areas' chief conservation objectives are to include species within their boundaries and protect them from negative external pressures. Many protected areas are not achieving these goals, perhaps in part due to land development inside and outside protected areas. We conducted spatial analyses to evaluate the ability of Canadian protected areas to mitigate the effects of nearby land development. We investigated correlations of national patterns of land development in and around protected areas and then examined national patterns of roads, urban area, and croplands in protected areas. We calculated the amount of developed land in protected areas and within 25-100 km of protected-area borders, the density of roads, and extent of urban and cropland area in protected areas. We constructed logistic-regression models to test whether development in a protected area was associated with landscape and protected-area characteristics. Land development was far less extensive inside than outside protected areas. However, several protected areas, particularly small southern areas near small urban centers had substantial development inside their boundaries, and nearly half of protected areas had roads. The cumulative extent of development within 50 km of protected areas was the best predictor of the probability of land development in protected areas. Canadian First Nations, industries, government, and nongovernmental organizations are currently planning an unprecedented number of new protected areas. Careful management of areas beyond protected-area boundaries may prove critical to meeting their long-term conservation objectives.

AimIt is challenging to disentangle how local habitat structure, climate, and human disturbance interplay to determine broad‐scale variation of species richness. Here, we separated various measures of local forest structure and composition, abiotic factors, and human land cover that constrain species richness of bird guilds in the boreal forest.LocationBoreal forest, western Canada.MethodsData on breeding birds, habitat structure, climate and human footprints in 206 sites were sampled, with each site centred on an area of 1 ha in size. The 206 sites cover a large geographical extent with a distance of c. 1000 km between the most distant sites. We modelled bird guild species richness in relation to forest structure and composition (woody plant richness, forest biomass, number of vegetation layers, canopy openness), abiotic environment (temperature, precipitation, elevation), and percentage area of human land cover. We classified bird species into different guilds based on dietary preference, habitat specialization and migratory status, and used structural equations to quantify effect strengths of predictor variables.ResultsWe found that temperature, low levels of human land cover, woody plant richness and number of vegetation layers had strong positive correlations with overall bird species richness in the boreal forest. Moreover, local forest structure and composition showed a pronounced variation in their relationships with species richness of different guilds. Insectivores, old‐growth forest specialists, forest generalists, long‐distance migrants and winter residents showed strong positive correlations with woody plant richness, whereas old‐growth forest specialists and winter residents were strongly related to forest biomass as well. The number of vegetation layers was positively related to species richness of most guilds, whereas the response to canopy openness was most pronounced for old‐growth forest specialists and winter residents (being negatively correlated).Main conclusionsIn addition to climate and human disturbance, local forest structure and composition are important determinants of broad‐scale variation of bird species richness in boreal forest. However, the strength and direction (positive/negative) of determinants is guild‐specific, suggesting a strong functional component to community structure.

Protected areas are a key instrument for conservation. Despite this, they are vulnerable to risks associated with weak governance, land-use intensification, and climate change. We used a novel hierarchical optimization approach to identify priority areas for expanding the global protected area system that explicitly accounted for such risks while maximizing protection of all known terrestrial vertebrate species. To incorporate risk categories, we built on the minimum set problem, where the objective is to reach species distribution protection targets while accounting for 1 constraint, such as land cost or area. We expanded this approach to include multiple objectives accounting for risk in the problem formulation by treating each risk layer as a separate objective in the problem formulation. Reducing exposure to these risks required expanding the area of the global protected area system by 1.6% while still meeting conservation targets. Incorporating risks from weak governance drove the greatest changes in spatial priorities for protection, and incorporating risks from climate change required the largest increase (2.52%) in global protected area. Conserving wide-ranging species required countries with relatively strong governance to protect more land when they bordered nations with comparatively weak governance. Our results underscore the need for cross-jurisdictional coordination and demonstrate how risk can be efficiently incorporated into conservation planning. Planeación de las áreas protegidas para conservar la biodiversidad en un futuro incierto.