The potential distribution of the Red Kite in Germany

Heuck, Christian; Brandl, Roland; Albrecht, Jörg; Gottschalk, Thomas K.

doi:10.1007/s10336-013-0955-2

Cited by 21 publications

(40 citation statements)

References 32 publications

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“…Positive response of these species to landscape heterogeneity is well documented in the literature (Buckingham et al ., ; Cornulier & Bretagnolle, ; Brambilla et al ., , ; Sirami et al ., ). The loss of grassland following the extension of maize was predicted to negatively affect Corn Bunting, Red Kite and Whinchat, which are typically associated with grassland habitats (Perkins et al ., ; Hoffmann et al ., ; Heuck et al ., ). Generally, maize management is intensive and includes more fertilizer and pesticides than other crops (Hötker et al ., ), which in turn reduces invertebrate abundance as a feeding source for farmland bird populations (Benton et al ., ; Boatman et al ., ).…”

Section: Discussionmentioning

confidence: 98%

Increased energy maize production reduces farmland bird diversity

et al. 2013

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Producing energy crops as an alternative to fossil fuels in order to reduce CO 2 emissions will lead to large-scale changes in agricultural landscapes. Here, we quantify the potential impact of an increase in maize fields on the diversity of farmland birds by means of high resolution (25 9 25 m) land-use scenarios. We generated scenarios in which the area of maize production in Germany increases from presently 2.6 to 2.9, 3.6 and 4.3 million ha, corresponding to the energy crop production targets of the German Renewable Energy Act for the years 2020, 2035 and 2050. To test the mitigating potential of conservation measures, each scenario was generated in a standard version and a landscape protection version, with the latter excluding valuable farmland areas from being converted into maize fields. Nine species of farmland birds belonging to the governmental indicator scheme for sustainable land-use in Germany were modelled for the six nation-wide scenarios. The models predicted that only the Northern Lapwing and the Little Owl might profit from extended maize production. Despite this, the total number of breeding pairs of the indicator species was predicted to decline by about 0.4 million breeding pairs in the most intensive scenario. Protection of valuable farmland did not mitigate these negative effects in the models. Our findings suggest that increased production of energy crops conflicts with conservation of biological diversity.

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Section: Discussionmentioning

confidence: 98%

Increased energy maize production reduces farmland bird diversity

et al. 2013

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“…for foraging or nesting; Brambilla and Saporetti 2014) or to benchmark established conservation concepts (such as the umbrella species concept, Fourcade et al 2017). More explicitly, the increasing availability of fine-scale information has helped conservationists to evaluate species-specific human impacts (Braunisch et al 2011, Coppes et al 2017 or to identify (potential) nest sites (Kassara et al 2011, Brambilla et al 2013, Heuck et al 2013. However, when such fine-scaled information is not available, downscaling information from coarser scales (such as from atlas data) could offer possible alternatives (but also poses new challenges; see Niamir et al 2011, Bombi and D'Amen 2012, Keil et al 2013Keil et al , 2014 for Figure 2.…”

Section: Identifying Priority Areas or Habitats For Conservationmentioning

confidence: 99%

Avian SDMs: current state, challenges, and opportunities

Engler

Stiels

Schidelko

et al. 2017

Journal of Avian Biology

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Quantifying species distributions using species distribution models (SDMs) has emerged as a central method in modern biogeography. These empirical models link species occurrence data with spatial environmental information. Since their emergence in the 1990s, thousands of scientific papers have used SDMs to study organisms across the entire tree of life, with birds commanding considerable attention. Here, we review the current state of avian SDMs and point to challenges and future opportunities for specific applications, ranging from conservation biology, invasive species and predicting seabird distributions, to more general topics such as modeling avian diversity, niche evolution and seasonal distributions at a biogeographic scale. While SDMs have been criticized for being phenomenological in nature, and for their inability to explicitly account for a variety of processes affecting populations, we conclude that they remain a powerful tool to learn about past, current, and future species distributions -at least when their limitations and assumptions are recognized and addressed. We close our review by providing an outlook on prospects and synergies with other disciplines in which avian SDMs can play an important role.

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“…BRTs is a machine-learning technique and builds on the concepts of decision trees and gradient boosting [39,48,49]. BRTs have recently gained popularity due to several advantages over traditional, frequentist statistical methods [50]. They offer high predictive accuracies and good interpretability of results, do not tend to overfit [51], are robust against missing data and collinearity of predictors, and are able to handle non-linearity and interaction effects [39,48,49].…”

Section: Boosted Regression Treesmentioning

confidence: 99%

“…The learning rate reduces the contribution of each single tree to the entire model and can be interpreted as a penalizing parameter. The number of trees determines the number of single decision trees included in the model and represents the model complexity [50,52].…”

Section: Boosted Regression Treesmentioning

confidence: 99%

Predicting strike susceptibility and collision patterns of the common buzzard at wind turbine structures in the federal state of Brandenburg, Germany

et al. 2020

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With the increase in wind turbines, bird collisions have developed as a potential hazard. In the federal state of Brandenburg, Germany, despite the ongoing mitigation efforts of increasing the distances of wind turbines from the breeding areas of the more severely affected populations of red kites (Milvus milvus), the additional detrimental influences on the buzzard populations (Buteo buteo) have added to the challenges for wind power expansion. Using data on the regional distribution of the buzzards, along with their carcass detections around the wind turbines (WTs), we aimed to better understand their collision distribution patterns in relation to their habitat use patterns to predict their exposure to collision risk using boosted regression trees (BRTs). Additionally, we integrated the developed collision potential map with the regional density map of buzzards to identify areas of increased strike susceptibility in turbine installations. Our study showed that the buzzard collisions were primarily concentrated at the turbines situated at sensitive distances from the edges of watercourses (>1000 metres), as well as those along the edges of grasslands (>750 metres), in the green open areas around/areas with minimal settlements (750 metres-1750 metres), and along the edges of bushlands (>1500 metres), together explaining 58% of the variance in their collision distribution. Conclusively, our study is applicable to conservation because it demonstrates the identification of potential collision areas along with the causes of the collisions, in addition to demonstrating the benefits of incorporating a species collision dataset as a proxy for species presence into species distribution models to make informed management decisions to eventually combat biodiversity loss.

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The potential distribution of the Red Kite in Germany

Cited by 21 publications

References 32 publications

Increased energy maize production reduces farmland bird diversity

Increased energy maize production reduces farmland bird diversity

Avian SDMs: current state, challenges, and opportunities

Predicting strike susceptibility and collision patterns of the common buzzard at wind turbine structures in the federal state of Brandenburg, Germany

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