Time filter

Source Type

Johnston A.,British Trust for Ornithology | Ausden M.,Royal Society for the Protection of Birds | Dodd A.M.,Royal Society for the Protection of Birds | Bradbury R.B.,Royal Society for the Protection of Birds | And 21 more authors.
Nature Climate Change | Year: 2013

The dynamic nature and diversity of species' responses to climate change poses significant difficulties for developing robust, long-term conservation strategies. One key question is whether existing protected area networks will remain effective in a changing climate. To test this, we developed statistical models that link climate to the abundance of internationally important bird populations in northwestern Europe. Spatial climate-abundance models were able to predict 56% of the variation in recent 30-year population trends. Using these models, future climate change resulting in 4.0C global warming was projected to cause declines of at least 25% for more than half of the internationally important populations considered. Nonetheless, most EU Special Protection Areas in the UK were projected to retain species in sufficient abundances to maintain their legal status, and generally sites that are important now were projected to be important in the future. The biological and legal resilience of this network of protected areas is derived from the capacity for turnover in the important species at each site as species' distributions and abundances alter in response to climate. Current protected areas are therefore predicted to remain important for future conservation in a changing climate. © 2013 Macmillan Publishers Limited. All rights reserved.

Kampichler C.,Netherlands Institute of Ecology | Kampichler C.,Juarez Autonomous University of Tabasco | Kampichler C.,Sovon Dutch Center for Field Ornithology | van der Jeugd H.P.,Netherlands Institute of Ecology
Environmental and Ecological Statistics | Year: 2013

All ecological communities experience change over time. One method to quantify temporal variation in the patterns of relative abundance of communities is time lag analysis (TLA). It uses a distance-based approach to study temporal community dynamics by regressing community dissimilarity over increasing time lags (one-unit lags, two-unit lags, three-unit lags). Here, we suggest some modifications to the method and revaluate its potential for detecting patterns of community change. We apply Hellinger distance based TLA to artificial data simulating communities with different levels of directional and stochastic dynamics and analyse their effects on the slope and its statistical significance. We conclude that statistical significance of the TLA slope (obtained by a Monte Carlo permutation procedure) is a valid criterion to discriminate between (i) communities with directional change in species composition, regardless whether it is caused by directional abundance change of the species or by stochastic change according to a Markov process, and (ii) communities that are composed of species with population sizes oscillating around a constant mean or communities whose species abundances are governed by a white noise process. TLA slopes range between 0.02 and 0.25, depending on the proportions of species with different dynamics; higher proportions of species with constant means imply shallower slopes; and higher proportions of species with stochastic dynamics or directional change imply steeper slopes. These values are broadly in line with TLA slopes from real world data. Caution must be exercised when TLA is used for the comparison of community time series with different lengths since the slope depends on time series length and tends to decrease non-linearly with it. © 2012 Springer Science+Business Media, LLC.

Shariatinajafabadi M.,University of Twente | Wang T.,University of Twente | Skidmore A.K.,University of Twente | Toxopeus A.G.,University of Twente | And 7 more authors.
PLoS ONE | Year: 2014

Many migrating herbivores rely on plant biomass to fuel their life cycles and have adapted to following changes in plant quality through time. The green wave hypothesis predicts that herbivorous waterfowl will follow the wave of food availability and quality during their spring migration. However, testing this hypothesis is hampered by the large geographical range these birds cover. The satellite-derived normalized difference vegetation index (NDVI) time series is an ideal proxy indicator for the development of plant biomass and quality across a broad spatial area. A derived index, the green wave index (GWI), has been successfully used to link altitudinal and latitudinal migration of mammals to spatiotemporal variations in food quality and quantity. To date, this index has not been used to test the green wave hypothesis for individual avian herbivores. Here, we use the satellite-derived GWI to examine the green wave hypothesis with respect to GPS-tracked individual barnacle geese from three flyway populations (Russian n = 12, Svalbard n = 8, and Greenland n = 7). Data were collected over three years (2008-2010). Our results showed that the Russian and Svalbard barnacle geese followed the middle stage of the green wave (GWI 40-60%), while the Greenland geese followed an earlier stage (GWI 20-40%). Despite these differences among geese populations, the phase of vegetation greenness encountered by the GPStracked geese was close to the 50% GWI (i.e. the assumed date of peak nitrogen concentration), thereby implying that barnacle geese track high quality food during their spring migration. To our knowledge, this is the first time that the migration of individual avian herbivores has been successfully studied with respect to vegetation phenology using the satellite-derived GWI. Our results offer further support for the green wave hypothesis applying to long-distance migrants on a larger scale. © 2014 Shariatinajafabadi et al.

Ens B.J.,Sovon Dutch Center for Field Ornithology | van de Pol M.,Australian National University | van de Pol M.,Netherlands Institute of Ecology | Goss-Custard J.D.,Bournemouth University
Advances in the Study of Behavior | Year: 2014

To understand the social organization of species, we propose that it is necessary to unify three partial descriptions of social systems based on competition for limiting resources: adaptive distribution theory, life-history theory, and mating systems theory. Here, we illustrate what insights can be gained by applying such a framework to the study of the various social positions that make up the social career of Eurasian Oystercatchers Haematopus ostralegus. During both the breeding and nonbreeding season, Oystercatchers are despotically distributed over limiting resources. We suggest that during the breeding season, nonbreeders delay reproduction by queuing for high-quality territories, and during the nonbreeding season, birds may queue for high dominance to enhance survival. The queue models potentially meet a key goal, namely, the ability to predict the mean and the variability in the age at which particular social positions are reached, as well as predicting the structure of the Oystercatcher society (i.e., the distribution of social positions) from the distribution of limiting resources. More work is needed to investigate whether the career decision where and when to start reproducing is also linked to the decision with whom to settle, or whether mate choice mainly operates after settlement via divorce. There are clear differences between the sexes in morphology, feeding specialization, and divorce strategy, but we are poorly informed on sex-specific differences in other career decisions. Furthermore, the difficulty in following individuals year-round means we still have relatively little knowledge how the career decisions in the nonbreeding and breeding seasons are linked through carry-over effects via an individual's state. © 2014 Elsevier Inc.

Huerta E.,Colegio de Mexico | Kampichler C.,Juarez Autonomous University of Tabasco | Kampichler C.,Sovon Dutch Center for Field Ornithology | Ochoa-Gaona S.,Colegio de Mexico | And 4 more authors.
PLoS ONE | Year: 2014

The aim of this study was to generate an easy to use index to evaluate the ecological state of agricultural land from a sustainability perspective. We selected environmental indicators, such as the use of organic soil amendments (green manure) versus chemical fertilizers, plant biodiversity (including crop associations), variables which characterize soil conservation of conventional agricultural systems, pesticide use, method and frequency of tillage. We monitored the ecological state of 52 agricultural plots to test the performance of the index. The variables were hierarchically aggregated with simple mathematical algorithms, if-then rules, and rule-based fuzzy models, yielding the final multi-criteria index with values from 0 (worst) to 1 (best conditions). We validated the model through independent evaluation by experts, and we obtained a linear regression with an r2 = 0.61 (p = 2.4e-06, d.f. = 49) between index output and the experts' evaluation. @copy;2014 Huerta et al.

Discover hidden collaborations