Detecting deterrence from patrol data

The threat posed to protected areas by the illegal killing of wildlife is countered principally by ranger patrols that aim to detect and deter potential offenders. Deterring poaching is a fundamental conservation objective, but its achievement is difficult to identify, especially when the prime source of information comes in the form of the patrols’ own records, which inevitably contain biases. The most common metric of deterrence is a plot of illegal activities detected per unit of patrol effort (CPUE) against patrol effort (CPUE-E). We devised a simple, mechanistic model of law breaking and law enforcement in which we simulated deterrence alongside exogenous changes in the frequency of offences under different temporal patterns of enforcement effort. The CPUE-E plots were not reliable indicators of deterrence. However, plots of change in CPUE over change in effort (ΔCPUE-ΔE) reliably identified deterrence, regardless of the temporal distribution of effort or any exogenous change in illegal activity levels as long as the time lag between patrol effort and subsequent behavioral change among offenders was approximately known. The ΔCPUE-ΔE plots offered a robust, simple metric for monitoring patrol effectiveness; were no more conceptually complicated than the basic CPUE-E plots; and required no specialist knowledge or software to produce. Our findings demonstrate the need to account for temporal autocorrelation in patrol data and to consider appropriate (and poaching-activity-specific) intervals for aggregation. They also reveal important gaps in understanding of deterrence in this context, especially the mechanisms by which it occurs. In practical applications, we recommend the use of ΔCPUE-ΔE plots in preference to other basic metrics and advise that deterrence should be suspected only if there is a clear negative slope. Distinct types of illegal activity should not be grouped together for analysis, especially if the signs of their occurrence have different persistence times in the environment.     

Bird conservation and the land sharing-sparing continuum in farmland-dominated landscapes of lowland England

Empirical evidence from many regions suggests that most species would be least negatively affected if human food demand were met through high-yield agricultural production and conservation of nonfarm ecosystems (land sparing), rather than through wildlife-friendly farming over a larger area (land sharing). However, repeated glaciation and a long history of agriculture may lead to different results in regions such as western Europe. We compared the consequences of land sparing and land sharing on breeding bird species in 2 lowland regions of England, The Fens, with 101 species, and Salisbury Plain, with 83. We derived density–yield responses for each species and then estimated regional population size under regional food production strategies, including land sharing and land sparing, a range of intermediate strategies, and a novel mixed strategy. In both regions, more species achieved maximum regional population size under land sparing than land sharing. In The Fens, the majority of birds were loser species (estimated to have smaller populations under all food production strategies than in the preagricultural baseline scenario), whereas in Salisbury Plain the majority were winners (smaller populations in the preagricultural baseline scenario). Loser species overwhelmingly achieved maximum regional population size under land sparing, whereas winner species achieved maximum regional population size under either land sharing or an intermediate strategy, highlighting the importance of defining which groups of species are the target of conservation. A novel 3-compartment strategy (combining high-yield farming, natural habitat, and low-yield farming) often performed better than either land sharing or land sparing. Our results support intermediate or 3-compartment land-sparing strategies to maximize bird populations across lowland agricultural landscapes. To deliver conservation outcomes, any shift toward land sparing must, however, ensure yield increases are sustainable in the long term, do not entail increased negative effects on surrounding areas, and are linked to allocation of land for nature.     

Incorporating evolutionary processes into population viability models

We examined how ecological and evolutionary (eco‐evo) processes in population dynamics could be better integrated into population viability analysis (PVA). Complementary advances in computation and population genomics can be combined into an eco‐evo PVA to offer powerful new approaches to understand the influence of evolutionary processes on population persistence. We developed the mechanistic basis of an eco‐evo PVA using individual‐based models with individual‐level genotype tracking and dynamic genotype–phenotype mapping to model emergent population‐level effects, such as local adaptation and genetic rescue. We then outline how genomics can allow or improve parameter estimation for PVA models by providing genotypic information at large numbers of loci for neutral and functional genome regions. As climate change and other threatening processes increase in rate and scale, eco‐evo PVAs will become essential research tools to evaluate the effects of adaptive potential, evolutionary rescue, and locally adapted traits on persistence.     

Amphibian Declines: Judging Stability, Persistence, and Susceptibility of Populations to Local and Global Extinctions

Extinctions are normal biological phenomena. Both mass extinctions in geological time and local extinctions in ecological time are well documented, but rates of extinction have increased in recent years—especially in vertebrates, including amphibians—as illustrated by recent reports of their population declines and range reductions. We suggest that long-term population data are necessary for rigorously evaluating the significance of the amphibian declines. Due to the physiological constraints, relatively low mobility, and site fidelity of amphibians, we suggest that many amphibian populations may be unable to recolonize areas after local extinction.     

Factors affecting vigilance within wild mixed-species troops of saddleback (<Emphasis Type="Italic">Saguinus fuscicollis</Emphasis>) and moustached tamarins (<Emphasis Type="Italic">S. mystax</Emphasis>)

We examine vigilance within a mixed-species troop of saddleback (Saguinus fuscicollis) and moustached (S. mystax) tamarins over a complete year. Saddleback tamarins were consistently more vigilant than moustached tamarins. This may be linked to their preference for lower strata. In accordance with previous studies of other primates, vigilant tamarins of both species were significantly further away from their nearest neighbours, and were also at lower heights in the forest than non-vigilant individuals. There was no observed sex difference in the amount of time spent vigilant. In terms of modes of scanning, the saddleback tamarins looked up significantly more frequently than the moustached tamarins, whereas there was no difference between the species in the frequency of side sweeps. There were no differences between the sexes in the frequencies of either type of vigilant behaviour. The proportion of time spent vigilant was higher than average immediately prior to entering a sleeping site for saddleback tamarins, but not for moustached tamarins. Both species were more vigilant immediately after exiting a sleeping site than at other times of the day. There was significant variation in the amount of time devoted to vigilance over the course of the year. These findings are discussed with respect to the social structure, ecology and main predator threats facing these species.Communicated by D. Watts     

采矿业资金提供者重申他们的绿色信任

在联合国环境规划署、世界银行集团和采矿、矿产和可持续发展计划( MMSD)一起组织的关注金融机构在为采矿项目提供资金方面作用的研讨会之前,对采矿业投资过程中的关键决策者进行了采访.本文提供了给采矿业提供投资的金融机构对当前环境状态的印象.     

Seasonal variation of total dissolved arsenic and arsenic speciation in a polluted surface waterway

Seasonal differences in the dissolved arsenic concentration and speciation in a contaminated urban waterway in northwest England have been determined using a coupled ion chromatography-inductively coupled plasma-mass spectrometry (IC-ICP-MS) technique. Waters sampled in the vicinity of an industrial works during relatively dry conditions in April 2000 were found to contain total arsenic concentrations (As) of up to 132 g L^–1, more than an order magnitude greater than the 4 g L^–1 maximum found in December 2000. The difference in As between the April and December sampling periods is speculated to be largely due to the irregular anthropogenic supply of arsenic to the watercourse. For both sampling periods, the dissolved arsenic was exclusively inorganic in nature and had an As(V)/As ratio of between 0.6 and 0.8. Analysis of samples taken downstream of the industrial site, after the confluence with a relatively As-poor stream, revealed that As(III), As(V) and As concentrations were lower than would be expected from conservative mixing. The As(V)/As ratio was also observed to decrease markedly. The loss of arsenic from solution is thought to be due to adsorption on the iron oxyhydroxide-rich sediment observed to coat the riverbed downstream of the confluence. The reduction in the As(V)/As ratio is believed to be due to the more rapid adsorption of As(V) compared to that of As(III). Deviations from conservative behaviour were more marked during the relatively dry April 2000 sampling period and suggest the increased importance of adsorption processes controlling arsenic availability during this time.     

A statistical evaluation of non-ergodic variogram estimators

Geostatistics is a set of statistical techniques that is increasingly used to characterize spatial dependence in spatially referenced ecological data. A common feature of geostatistics is predicting values at unsampled locations from nearby samples using the kriging algorithm. Modeling spatial dependence in sampled data is necessary before kriging and is usually accomplished with the variogram and its traditional estimator. Other types of estimators, known as non-ergodic estimators, have been used in ecological applications. Non-ergodic estimators were originally suggested as a method of choice when sampled data are preferentially located and exhibit a skewed frequency distribution. Preferentially located samples can occur, for example, when areas with high values are sampled more intensely than other areas. In earlier studies the visual appearance of variograms from traditional and non-ergodic estimators were compared. Here we evaluate the estimators' relative performance in prediction. We also show algebraically that a non-ergodic version of the variogram is equivalent to the traditional variogram estimator. Simulations, designed to investigate the effects of data skewness and preferential sampling on variogram estimation and kriging, showed the traditional variogram estimator outperforms the non-ergodic estimators under these conditions. We also analyzed data on carabid beetle abundance, which exhibited large-scale spatial variability (trend) and a skewed frequency distribution. Detrending data followed by robust estimation of the residual variogram is demonstrated to be a successful alternative to the non-ergodic approach.