The role of scale in designing protected area systems to conserve poorly known species

Systematic conservation planning has a substantial theoretical underpinning that allows optimization of tradeoffs between biodiversity conservation and other socioeconomic goals. However, this theory assumes perfect spatial information about the locations of biodiversity features (e.g., species distributions). In practice, planners represent well-known taxa and other biodiversity “surrogates” in protected area systems, hoping that unmapped species will also be conserved. However, empirical research finds that surrogates predict species presence imperfectly, and sometimes rather poorly, at scales relevant to planning, and existing theory provides no further guidance. We developed new theory, explicitly incorporating aspects of spatial scale, for the representation problem when the locations of species distributions are unknown. Using probability theory and simulated and real species distributions, we found that the probability of adequately representing an unmapped species in a protected area system will be low unless the total fraction of the region being protected is larger than the species representation target. Furthermore, successful conservation depended critically on the relative sizes of the species distribution and of the individual protected areas; fewer, larger protected areas allowed the entire species distribution to fall into an unprotected gap. This scale-dependence varied with the configuration of the protected area system, with the conservation objective most likely to be attained if the individual protected areas were hyperdispersed (evenly spaced across the planning region). Using these results, we developed three design principles for representing unmapped species in protected areas: (1) The fraction of the region placed in protected areas should be substantially larger than the species-level representation target; (2) Individual protected areas must be at least one to two orders of magnitude smaller than the unmapped species' distribution; and (3) Protected areas should be evenly dispersed over geographic space. We also performed preliminary investigations of the effects of surrogates and socio-economic cost data on the probability of adequately representing unmapped species, finding that the primary effect of surrogates may simply be to promote hyperdispersion of protected areas across the planning region, and that seeking to minimize opportunity costs gives poorer conservation results than random protected area placement

Landscape effects on wild Bombus terrestris (Hymenoptera: Apidae) queens visiting highbush blueberry fields in south-central Chile

International audienceAbstractIn this study pollinators visiting highbush blueberry fields set in landscapes with differing land use pattern in south-central Chile were investigated. Effects of spatial buffers from 0.5 to 8 km around each blueberry field on the abundance of the main wild pollinator, Bombus terrestris queens, were tested. Wild B. terrestris abundances were positively affected by natural forest area and negatively affected by high-food resource area, and these effects were strongest at a buffer radius of 1 and 3.5 km, respectively. Possibly, continuous food resources provided by natural forest areas favor colony establishment and growth, and/or increase overwintering survival of bumblebee queens. Also, pollinator dependent crop area can generate a “transient dilution effect” by decreasing the density of bumblebees in simultaneously flowering crops. Management strategies might increase crop pollination services by considering the importance of nesting and overwintering habitat quality/amount and area of simultaneously flowering crops requiring insect pollination

Turbulent dispersal promotes species coexistence

Several recent advances in coexistence theory emphasize the importance of space and dispersal, but focus on average dispersal rates and require spatial heterogeneity, spatio-temporal variability or dispersal-competition tradeoffs to allow coexistence. We analyse a model with stochastic juvenile dispersal (driven by turbulent flow in the coastal ocean) and show that a low-productivity species can coexist with a high-productivity species by having dispersal patterns sufficiently uncorrelated from those of its competitor, even though, on average, dispersal statistics are identical and subsequent demography and competition is spatially homogeneous. This produces a spatial storage effect, with an ephemeral partitioning of a ‘spatial niche’, and is the first demonstration of a physical mechanism for a pure spatiotemporal environmental response. ‘Turbulent coexistence’ is widely applicable to marine species with pelagic larval dispersal and relatively sessile adult life stages (and perhaps some wind-dispersed species) and complements other spatial and temporal storage effects previously documented for such species

Modeling adaptive and non-adaptive responses to environmental change

Understanding how the natural world will be impacted by environmental change over the coming decades is one of the most pressing challenges facing humanity. Addressing this challenge is difficult because environmental change can generate both population level plastic and evolutionary responses, with plastic responses being either adaptive or non-adaptive. We develop an approach that links quantitative genetic theory with data-driven structured models to allow prediction of population responses to environmental change via plasticity and adaptive evolution. After introducing general new theory, we construct a number of example models to demonstrate that evolutionary responses to environmental change over the short-term will be considerably slower than plastic responses, and that the rate of adaptive evolution to a new environment depends upon whether plastic responses are adaptive or non-adaptive. Parameterization of the models we develop requires information on genetic and phenotypic variation and demography that will not always be available, meaning that simpler models will often be required to predict responses to environmental change. We consequently develop a method to examine whether the full machinery of the evolutionarily explicit models we develop will be needed to predict responses to environmental change, or whether simpler non-evolutionary models that are now widely constructed may be sufficient

Within reach? Habitat availability as a function of individual mobility and spatial structuring

Organisms need access to particular habitats for their survival and reproduction. However, even if all necessary habitats are available within the broader environment, they may not all be easily reachable from the position of a single individual. Many species distribution models consider populations in environmental (or niche) space, hence overlooking this fundamental aspect of geographical accessibility. Here, we develop a formal way of thinking about habitat availability in environmental spaces by describing how limitations in accessibility can cause animals to experience a more limited or simply different mixture of habitats than those more broadly available. We develop an analytical framework for characterizing constrained habitat availability based on the statistical properties of movement and environmental autocorrelation. Using simulation experiments, we show that our general statistical representation of constrained availability is a good approximation of habitat availability for particular realizations of landscape-organism interactions. We present two applications of our approach, one to the statistical analysis of habitat preference (using step-selection functions to analyze harbor seal telemetry data) and a second that derives theoretical insights about population viability from knowledge of the underlying environment. Analytical expressions for habitat availability, such as those we develop here, can yield gains in analytical speed, biological realism, and conceptual generality by allowing us to formulate models that are habitat sensitive without needing to be spatially explicit