Three-dimensional species distribution modelling reveals the realized spatial niche for coral recruitment on contemporary Caribbean reefs

The three-dimensional structure of habitats is a critical component of species' niches driving coexistence in species-rich ecosystems. However, its influence on structuring and partitioning recruitment niches has not been widely addressed. We developed a new method to combine species distribution modelling and structure from motion, and characterized three-dimensional recruitment niches of two ecosystem engineers on Caribbean coral reefs, scleractinian corals and gorgonians. Fine-scale roughness was the most important predictor of suitable habitat for both taxa, and their niches largely overlapped, primarily due to scleractinians' broader niche breadth. Crevices and holes at mm scales on calcareous rock with low coral cover were more suitable for octocorals than for scleractinian recruits, suggesting that the decline in scleractinian corals is facilitating the recruitment of octocorals on contemporary Caribbean reefs. However, the relative abundances of the taxa were independent of the amount of suitable habitat on the reef, emphasizing that niche processes alone do not predict recruitment rates.     

Calcification in aquatic plants

Abstract. The CaCO₃ deposits of aquatic plants may be intra-, inter- and extracellular. Calcification is mainly the result of photosynthetic CO₂ or HCO⁻₃ assimilation. This raises the local pH and CO²⁻₃ concentration resulting from shifts in the dissolved inorganic carbon equilibrium, due to either net CO₂ depletion as in Halimeda or localized OH⁻ efflux (or H⁺ influx) as in Chara. The plant cell wall may be important in CaCO₃ nucleation by acting as an epitaxial substratum or template, or by creating a microenvironment enriched in Ca²⁺ compared to Mg²⁺. Hypotheses on the reason for the lack of calcification in many aquatic plants are presented.     

Sustainable intensification of crop residue exploitation for bioenergy: Opportunities and challenges

Crop residue exploitation for bioenergy can play an important role in climate change mitigation without jeopardizing food security, but it may be constrained by impacts on soil organic carbon (SOC) stocks, and market, logistic and conversion challenges. We explore opportunities to increase bioenergy potentials from residues while reducing environmental impacts, in line with sustainable intensification. Using the case study of North Rhine‐Westphalia in Germany, we employ a spatiotemporally explicit approach combined with stakeholder interviews. First, the interviews identify agronomic and environmental impacts due to the potential reduction in SOC as the most critical challenge associated with enhanced crop residue exploitation. Market and technological challenges and competition with other residue uses are also identified as significant barriers. Second, with the use of agroecosystem modelling and estimations of bioenergy potentials and greenhouse gas emissions till mid‐century, we evaluate the ability of agricultural management to tackle the identified agronomic and environmental challenges. Integrated site‐specific management based on (a) humus balancing, (b) optimized fertilization and (c) winter soil cover performs better than our reference scenario with respect to all investigated variables. At the regional level, we estimate (a) a 5% increase in technical residue potentials and displaced emissions from substituting fossil fuels by bioethanol, (b) an 8% decrease in SOC losses and associated emissions, (c) an 18% decrease in nitrous oxide emissions, (d) a 37% decrease in mineral fertilizer requirements and emissions from their production and (e) a 16% decrease in nitrate leaching. Results are spatially variable and, despite improvements induced by management, limited amounts of crop residues are exploitable for bioenergy in areas prone to SOC decline. In order to sustainably intensify crop residue exploitation for bioenergy and reconcile climate change mitigation with other sustainability objectives, such as those on soil and water quality, residue management needs to be designed in an integrated and site‐specific manner.     

Strategic Habitat Conservation for Beach Mice: Estimating Management Scenario Efficiencies

The Perdido Key beach mouse (Peromyscus polionotus trissyllepsis), Choctawhatchee beach mouse (P. p. allophrys), and St. Andrew beach mouse (P. p. peninsularis) are 3 federally endangered subspecies that inhabit coastal dunes of Alabama and Florida, USA. Conservation opportunities for these subspecies are limited and costly. Consequently, well-targeted efforts are required to achieve their downlisting criteria. To aid the development of targeted management scenarios that are designed to achieve downlisting criteria, we developed a Bayesian network model that uses habitat characteristics to predict the probability of beach mouse presence at a 30-m resolution across a portion of the Florida Panhandle. We then designed alternative management scenarios for a variety of habitat conditions for coastal dunes. Finally, we estimated how much area is needed to achieve the established downlisting criterion (i.e., habitat objective) and the amount of effort needed to achieve the habitat objective (i.e., management efficiency). The results suggest that after 7 years of post-storm recolonization, habitat objectives were met for Perdido Key (within its Florida critical habitat) and Choctawhatchee beach mice. The St. Andrew beach mouse required 5.14 km² of additional critical habitat to be protected and occupied. The St. Andrew beach mouse habitat objective might be achieved by first restoring protected critical habitat to good dune conditions and then protecting or restoring the unprotected critical habitat with the highest predicted probability of beach mouse presence. This scenario provided a 28% increase in management efficiency compared to a scenario that randomly protected or restored undeveloped unprotected critical habitat. In total, when coupled with established downlisting criteria, these quantitative and spatial decision support tools could provide insight into how much habitat is available, how much more is needed, and targeted conservation or restoration efforts that might efficiently achieve habitat objectives. © 2020 The Wildlife Society.     

Do species population parameters and landscape characteristics affect the relationship between local population abundance and surrounding habitat amount?

In landscape ecology, correlational approaches are typically used to analyse links between local population abundance, and the surrounding habitat amount to estimate biologically-relevant landscape size (extent) for managing endangered or pest populations. The direction, strength, and spatial extent of the correlations are then sometimes interpreted in terms of species population parameters. Here we simulated the population dynamics of generalized species across spatially explicit landscapes that included two distinct habitat types. We investigated how characteristics of a landscape (structure), including the variation in habitat quality and spatial aggregation of the habitat, and the precise population-dynamic properties of the simulated species (dispersal and growth rates) affect the correlation between population abundance and amount of surrounding favourable habitat in the landscape. To evaluate these spatial extents of correlation, proportions of favourable habitat were calculated within several circles of increasing diameter centred on sampling patches of favourable habitat where population abundance was recorded.We found that the value of the correlation coefficients between population abundance and amount of surrounding favourable habitat depended on both population dynamic parameters and landscape characteristics. Coefficients of correlation increased with the variation in habitat quality and the aggregation of favourable habitat in the landscape, but decreased with the dispersal distance. The distance at which the correlation was maximized was sensitive to an interaction between the level of aggregation of the habitat and the dispersal distance; whereas the greatest distance at which a significant correlation occurred was more sensitive to the variation in habitat quality. Our results corroborate the view that correlational analyses do provide information on the local population dynamics of a species in a given habitat type and on its dispersal rate parameters. However, even in simplified, model frameworks, direct relationships are often difficult to disentangle and global landscape characteristics should be reported in any studies intended to derive population-dynamic parameters from correlations. Where possible, replicated landscapes should be examined in order to control for the interaction between population dynamics and landscape structure. Finally, we recommend using species-specific, population-dynamic modelling in order to interpret correctly the observed patterns of correlation in the landscape.     

Dynamic occupancy models for analyzing species' range dynamics across large geographic scales

Large‐scale biodiversity data are needed to predict species' responses to global change and to address basic questions in macroecology. While such data are increasingly becoming available, their analysis is challenging because of the typically large heterogeneity in spatial sampling intensity and the need to account for observation processes. Two further challenges are accounting for spatial effects that are not explained by covariates, and drawing inference on dynamics at these large spatial scales. We developed dynamic occupancy models to analyze large‐scale atlas data. In addition to occupancy, these models estimate local colonization and persistence probabilities. We accounted for spatial autocorrelation using conditional autoregressive models and autologistic models. We fitted the models to detection/nondetection data collected on a quarter‐degree grid across southern Africa during two atlas projects, using the hadeda ibis (Bostrychia hagedash) as an example. The model accurately reproduced the range expansion between the first (SABAP1: 1987–1992) and second (SABAP2: 2007–2012) Southern African Bird Atlas Project into the drier parts of interior South Africa. Grid cells occupied during SABAP1 generally remained occupied, but colonization of unoccupied grid cells was strongly dependent on the number of occupied grid cells in the neighborhood. The detection probability strongly varied across space due to variation in effort, observer identity, seasonality, and unexplained spatial effects. We present a flexible hierarchical approach for analyzing grid‐based atlas data using dynamical occupancy models. Our model is similar to a species' distribution model obtained using generalized additive models but has a number of advantages. Our model accounts for the heterogeneous sampling process, spatial correlation, and perhaps most importantly, allows us to examine dynamic aspects of species ranges.     

Negative effects of density on space use of small mammals differ with the phase of the masting‐induced population cycle

Home range size generally decreases with increasing population density, but testing how this relationship is influenced by other factors (e.g., food availability, kin structure) is a difficult task. We used spatially explicit capture–recapture models to examine how home range size varies with population density in the yellow‐necked mouse (Apodemus flavicollis). The relationship between population density and home range size was studied at two distinct phases of population fluctuations induced by beech (Fagus sylvatica) masting: post‐mast peak in abundance (first summer after mast, n = 2) and subsequent crash (second summer after mast, n = 2). We live‐trapped mice from June to September to avoid the confounding effects of autumn seedfall on home range size. In accordance with general predictions, we found that home range size was negatively associated with population density. However, after controlling for the effect of density, home ranges of mice were larger in post‐mast years than during the crash phase. This indicates a higher spatial overlap among neighbors in post‐mast years. We suggest that the increased spatial overlap is caused by negative density‐dependent dispersal that leads to high relatedness of individuals within population in the peak phase of the cycle.     

Local contagion and regional compression: habitat selection drives spatially explicit,multiscale dynamics of colonisation in experimental metacommunities

Habitat selection, including oviposition site choice, is an important driver of community assembly in freshwater systems. Factors determining patch quality are assessed by many colonising organisms and affect colonisation rates, spatial distribution and community structure. For many species, the presence/absence of predators is the most important factor affecting female oviposition decisions. However, individual habitat patches exist in complex landscapes linked by processes of dispersal and colonisation, and spatial distribution of factors such as predators has potential effects beyond individual patches. Perceived patch quality and resulting colonisation rates depend both on risk conditions within a given patch and on spatial context. Here we experimentally confirm the role of one context‐dependent processes, spatial contagion, functioning at the local scale, and provide the first example of another context‐dependent process, habitat compression, functioning at the regional scale. Both processes affect colonisation rates and patterns of spatial distribution in naturally colonised experimental metacommunities.     

Parallel effects of the inversion In(3R)Payne on body size across the North American and Australian clines in Drosophila melanogaster

Chromosomal inversions are thought to play a major role in climatic adaptation. In D. melanogaster, the cosmopolitan inversion In(3R)Payne exhibits latitudinal clines on multiple continents. As many fitness traits show similar clines, it is tempting to hypothesize that In(3R)P underlies observed clinal patterns for some of these traits. In support of this idea, previous work in Australian populations has demonstrated that In(3R)P affects body size but not development time or cold resistance. However, similar data from other clines of this inversion are largely lacking; finding parallel effects of In(3R)P across multiple clines would considerably strengthen the case for clinal selection. Here, we have analysed the phenotypic effects of In(3R)P in populations originating from the endpoints of the latitudinal cline along the North American east coast. We measured development time, egg‐to‐adult survival, several size‐related traits (femur and tibia length, wing area and shape), chill coma recovery, oxidative stress resistance and triglyceride content in homokaryon lines carrying In(3R)P or the standard arrangement. Our central finding is that the effects of In(3R)P along the North American cline match those observed in Australia: standard arrangement lines were larger than inverted lines, but the inversion did not influence development time or cold resistance. Similarly, In(3R)P did not affect egg‐to‐adult survival, oxidative stress resistance and lipid content. In(3R)P thus seems to specifically affect size traits in populations from both continents. This parallelism strongly suggests an adaptive pattern, whereby the inversion has captured alleles associated with growth regulation and clinal selection acts on size across both continents.     

Assessing lignocellulosic biomass production from crop residues in the European Union: Modelling,analysis of the current scenario and drivers of interannual variability

This study assesses crop residues in the EU from major crops using empirical models to predict crop residues from yield statistics; furthermore it analyses the inter‐annual variability of those estimates over the period 1998‐2015, identifying its main drivers across Europe. The models were constructed based on an exhaustive collection of experimental data from scientific papers for the crops: wheat, barley, rye, oats, triticale, rice, maize, sorghum, rapeseed, sunflower, soybean, potato and sugarbeet. We discuss the assumptions on the relationship between yield and the harvest index, adopted by previous studies, to interpret the experimental data, quantify the uncertainties of these models, and establish the premises to implement them at regional scale –i.e., NUTS level 3– within the EU. To cope this, we created a consolidated sub‐national statistical data along with an algorithm able to aggregate (figures are provided at country level) and disaggregate (production at 25 km grid is provided assupplementary material) estimates. The total lignocellulosic biomass production in the EU28 over the review period, according to our models, is 419 Mt, from which wheat is the major contributor (155 Mt). Our results show that maize and rapeseed are the two crops with the highest residue yield, respectively 8.9 and 8.6 t ha‐1. The spatial analysis revealed that these three crops, which, according to our results, are feedstocks highly suitable a priori for second generation biofuels in the EU and are unevenly distributed across Europe. Weather fluctuation was identified as the major driver in residue production from cereals, while, in the case of starch crops and oilseeds – which are predominant in northern Europe – corresponded to the marked production trend likely influenced by the agricultural policies and agro‐management over the review period. Our results, among others, could help to understand and quantify the ecological boundaries of the bioeconomy from agriculture.