Climate warming is also expected to shift insect body size via selection and plasticity. Warmer temperatures accelerate development, which can shorten the duration of development and reduce adult size temperature-size rule [ 30 ]. Warmer environments can also select for decreased size to decrease body temperatures [ 17 ]. Consequently, predictions and observations of insect responses to climate change generally indicate a decrease in body size [ 3 , 31 ]. However, spring warming can extend the time available for development and increase size [ 32 ]. We evaluate several factors expected to determine trait values via both phenotypic plasticity and selection.
We examine developmental temperatures, which determine phenotypic plasticity, and temperatures during the previous flight period, which determine the reproductive success of parents. Given the seasonal progression of temperatures, we also consider the interactions between developmental or pupal temperatures and collection date. Finally, we include collection year as an indicator of evolutionary shifts in phenotypes.
However, we are unable to control for other factors that vary over long time scales such as trends in temperature mean and variability omitted from our temperature measures; trends in habitat, host plant availability, wind speed, or cloud cover; and collection biases. Colias meadii occurs in subalpine and alpine meadows above 2. The subspecies C. It is genetically distinct from more northern populations of the species in Wyoming Basin [ 33 ]. In this study we focus on C. In this region, C. We processed specimens from museums in the United States with the largest holdings of C.
Because museum holdings of C. While females tend to have darker wings than males, elevation clines in melanism are similar between the sexes [ 21 ]. Model predictions for temporal trends in melanism are based on the temperature dependence of flight time and egg viability, which were translated into female reproduction [ 16 , 28 ]. The flight time constraints should influence male fitness similarly, so predicted temporal trends also apply to males.
The similar elevation clines between sexes suggest that they respond to climatic gradients similarly and our observations should be indicative of both sexes. All specimens for the C. Including these specimens increased the slope of our regressions and significance of our results. Pinned specimens were measured by removing labels with forceps, transcribing the locality data, and then placing the head of the pin in a lump of modeling clay to expose the ventral hindwing the wing region accounting for the majority of absorption for this ventral basking species.
Elevation was recorded from the locality tag in the collections if available; otherwise we used a digital elevation model to estimate elevation based on latitude and longitude. We used Google Earth to georeference locality descriptions when necessary. A digital micrometer was used to measure the forewing of the specimen from the thoracic insertion to the apex of the wing. Each image included a black and white standard. Because the height of the animal on the pin was variable, we used auto focusing to allow for the clearest image. We measured setal length on the ventral thorax with an ocular micrometer on a Wild M5 microscope as the longest setae between the first and second leg.
Specimens were distributed randomly throughout collection boxes and thus were measured randomly within each collection. We photographically assessed the degree of wing melanism on the posterior ventral hind-wing. First, we selected a triangulated region between the eyespot, hind wing insertion, and the wing margin [ 21 , 34 ]. Using a MatLab program T. Hedrick, unpublished , we then converted the RAW image to black and white to account for potential fading.
Black and white is appropriate because wing scales are pigmented by either melanin dark or pterin light. We digitized the region of interest and the black and white standards for each sample, and then used the standards to calculate a standardized grey-level value between 0 white and 1 black. The grey-level value should be robust to butterfly size because it represents the proportion of melanic wing scales. We estimated temperatures expected to influence each focal trait based on lab observations for the closely related Colias eriphyle.
We consider temperatures experienced by adults during the previous flight season, which determines reproductive success via flight time and overheating. We estimated temperatures during the previous flight season as the mean across Julian days spanning to The flight season was determined by taking the 25 th to 75 th quantiles of collection date. We used a constant flight season across years because we had little basis for predicting when in the flight season a parent flew.
We examined sensitivity to our selection of time windows for developmental and pupal temperatures and found the model results to be robust. We additionally considered substituting flight season temperatures from the previous year with temperatures during the current year. Temperatures from the previous year were stronger predictors, but including current year temperatures did not qualitatively alter our model. We focus on temperature, but note that shifts in cloudiness and radiation could also influence plasticity and evolution. Increases in cloudiness on the order of 1. However, shifts are regionally variable.
Analysis of solar radiation data proximate to our specimens suggests that solar radiation has increased over our observation period [ 38 ], consistent with other observations for the Rockies [ 39 ]. However, all these estimates have very low confidence due to a shift in techniques for cloud observations which also influences solar radiation data derived from modeling [ 37 ]. The radiation trends are sufficiently uncertain and of a magnitude that justifies our focus on temperature.
Additionally, our focus does not include wind speed. While wind plays a role in the heat budget for these butterflies, there is little evidence beyond a weak change in mean at high elevation of a temporial trend at these sites [ 40 ]. We account for uneven collection intensities by restricting our analysis to 15 individuals per site per year. We then averaged the model output to perform model selection. We randomly sampled specimens each of the 50 times we repeated the analysis. Statistical model results were similar across iterations of the analysis, so we report results averaged across the 50 iterations.
We performed model selection and averaging using the R package MuMIn [ 41 ] commands: dredge and model. For each iteration of the analysis, we selected the top 20 sub-models according to AICc sample size corrected Akaike Information Criterion. We present the full results of the model-averaging in Additional file 1 : Table S1. We normalized the predictor variables using the scale function in R. We assessed collinearity using the variance inflation factor vif function from the R car package. To account for trait similarity due to geographic proximity, we used maximum-likelihood spatial autoregressive SAR models [ 42 ], R package spdep [ 43 ].
Neighbors were weighted using row standardization. We report log-likelihood tests comparing the SAR to a null model consisting only of an intercept along with Nagelkerke pseudo R 2 values. We compared the SAR model output to linear models and found no qualitative differences in the direction of the effects. We standardized both year and elevation to the mean.
Model selection identified elevation as an important predictor of phenology, despite its being omitted from the best models for trait values. Partial residuals residuals of regressing the response variable on the independent variables, but omitting the independent variable of interest for predictors of forewing length mm. While forewing length tends increase with increasing developmental temperatures non-significant correlation as well as collection date, developmental temperatures and collection date interact. Forewing length increases with year.
Partial residuals for predictors of wing melanism grey level. Wing melanism decreases with increasing pupal and flight season temperatures as well as collection date, but pupal temperatures and collection date interact. Wing melanism increases with year. Partial residuals for predictors of setae length mm.
Setae length increases with year and decreases with the date of collection. Setae length is influenced by pupal and flight season temperatures as well as the interaction of pupal temperatures with collection date. Influences of temperature and collection date on thermoregulatory traits suggest plastic responses to environmental temperatures. Non-significant tendencies for melanism to decrease with increases in pupal and flight season temperatures Fig. Melanism decreases significantly with collection date, such that lower melanism is found later in the season relative importance of 0.
An interaction between pupal temperatures and collection dates also receives moderate relative importance across models relative importance of 0. The interaction represents a correction accounting for the tendency for butterflies collected later in the season to have experienced warmer temperatures during pupation. Developmental temperatures and temperatures during the previous flight season received support as predictors of wing length relative importance 0. The interaction between developmental temperatures and collection date received some support as a predictor of forewing length relative importance of 0.
Neither pupal temperatures nor their interaction with collection date are significant predictors of setae length, but they receive support for model inclusion relative importance of 0. We also find evidence of a phenological shift, which depends on elevation. Collection date has shifted later over time, but there was a significant interaction such that low elevation individuals were collected earlier and high elevation individuals were collected later over time Fig.
Butterflies: Ecology and Evolution Taking Flight
Partial residual plot for normalized predictors of collection date J. Collection date advances with year and elevation. However, the predictors interact such that collection date has shifted earlier in the season at lower elevation and later in the season at higher elevations in later years. Phenotypic plasticity is increasingly viewed as a primary response to environmental change [ 2 , 44 , 27 ]. Plasticity is increasingly being incorporated in predictive models of phenotypic change and warming tolerance [ 45 ] and being explicitly tested for in empirical studies [ 2 ].
The interaction between phenotypic plasticity and adaptive evolution in responding to environmental change remains unclear: does phenotypic plasticity tend to facilitate adaptive evolution by enabling persistence or does it tend to slow adaptive evolution by buffering selection [ 2 , 45 ]? One striking result from our studies is that mean forewing length, wing melanism, and setal length in C.
These historical shifts are inconsistent with simple expectations for evolutionary responses to climate warming. However, previous analyses suggested complex patterns of selection: increases in melanism are consistent with our expectations for high elevation populations that are flight limited [ 26 ]. Previous modeling of C. Such environmental variation generates fluctuations in the magnitude and direction of selection that strongly reduce the rate of adaptive evolution to directional environmental change [ 26 , 46 ].
Several lines of past and current evidence support the contribution of phenotypic plasticity to variation in wing melanism. Lab experiments show that lower temperatures experienced during pupal development increase adult wing melanism in montane Colias [ 29 , 36 , 47 ]. Our historical analyses indicate that greater wing melanism is associated with lower pupal temperatures, and with earlier collection dates during the flight season when temperatures are on average lower. These patterns are consistent with the idea that phenotypic plasticity in wing melanism in response to variation in pupal temperature is contributing to the historical pattern in this trait.
Whether such plasticity is adaptive depends on whether environmental cues during pupal development are good predictors of environmental conditions experienced by adults [ 48 — 50 ]. This interannual variability may be contributing to the observed increase in melanism and setae length by causing variation in the direction of selection and mismatching developmental and flight temperatures. Thermal extremes that cause overheating are relatively rare in our montane sites [ 16 ], their incidence may be mostly independent of mean active season temperatures, and variation in thermoregulatory traits may be relatively ineffective in avoiding overheating.
Thus, selection to increase flight time in cold years may be stronger and more consistent than selection to avoid overheating in warm years. Change in the distribution of collection dates of historic specimens can indicate shifts in phenology [ 51 ]. PIS-2 separated the Deschampsia -Bistort association lower values from the flower-rich areas higher values. For the B. BEU-2 represented a gradient of degradation i. BAQ-2 represents a gradient of humidity. We specifically extracted information on both juvenile and adult resources i. Additionally, we counted the number of grass tussocks, Sphagnum hummocks and P.
Table 1 lists the resources used for each species. Also, for the Pisserotte zones, we assessed 4 the percentage of perimeter edge surrounded by trees on a three value scale: 0 for no tree edge, 0. Resource configuration was estimated by two variables; resource distribution and resource organization. Resource distribution was assessed using a classical niche breadth measure Edwards et al. B ranges from 1 i. For the assessment of the juvenile resource distribution in B. Resource organization was quantified by the percentage of overlap spatial dimensions shared by juvenile and adult resources, estimated using Schoener's index of niche overlap:.
Some resource variables were highly correlated in a number of the datasets. To prevent multicollinearity issues, we excluded the following descriptors: 1 juvenile resource distribution correlated with host abundance and adult resource distribution correlated with nectar abundance in Pisserotte; 2 nectar abundance correlated with nectar distribution and micro-habitat structure abundance correlated with resource organization in the B.
In the Pisserotte reserve, area was computed as the total surface of each zone. In the B. A connectivity index was computed using all 53 known Belgian populations of B. We did not compute such a connectivity index for the B. We monitored butterfly populations using a Mark—Release—Recapture MRR approach and estimated adult abundance in each Pisserotte zone and the population size in each site separately.
Adriana D. Briscoe
The study zones and sites were visited every 2 days if weather permitted i. Adult butterflies were individually marked and released on the spot of capture. At each re capture, we recorded the marking code, species, sex, date and time, and location i. For the five species in Pisserotte, the classical approach to estimate population size see below was not suitable because demographic parameters are estimated at the whole population level; the frequent movements among zones within Pisserotte did not allow considering each zone as an independent population whose size can be estimated independently.
We therefore estimated the local abundance per species and sex in each of the 40 Pisserotte zones as the number of re capture events pooled for the 2 years of available MRR data. Frequency of re captures was then used as a proxy of the local butterfly abundance assuming the probability of capture was similar among the zones, which is a reasonable assumption Schtickzelle and Baguette, The total abundance of all local abundances captures and recaptures in the Pisserotte site was B.
For several populations of the B. In cases where the low number of captures prevented us from adopting such a modeling approach, we computed the population size using a conversion function from the number of marked individuals based on the strong relationships existing in the two species between the number of marked individuals and population size in the two species Turlure et al.
Niklas Janz on butterflies and plants
The mean yearly metapopulation size was estimated to B. In the Pisserotte reserve, we also recorded the abundance of juvenile stages caterpillars for the three Boloria species and eggs for the two Lycaena species. We surveyed Boloria caterpillars prior to the flying period of and in all the zones where the specific host plants were present Total searching time with one to three persons: 70 h for B.
The search effort was proportional to the host plant coverage in the zone Relation between searching time ST in min and host plant area HPA in m 2 : B. Recorded abundances per zone in both years were pooled for further analysis. In total, we found B. At the end of L. At the end of the L. Searching time by one to three persons was 37 h for L. We found L.
During the flight period of the two species in summer and , we took morphological measures in 10 different individuals per species, sex and site B. To do so, butterflies were captured and measured alive with calipers. We recorded thorax length TL along the center line and width TW at the widest part, abdomen length AL along the center line and width AW at widest part, and length of the upper edge of forewing FW.
From these measures, we estimated the volume of the abdomen AV and the volume of the thorax TV , both approximated as an ellipsoid volume with height equal to width as in Turlure et al. Since both Boloria species are legally protected, we could only apply non-invasive methods. This was done on freshly emerged individuals i. We used linear models to analyze variation in butterfly species abundance in the 40 Pisserotte zones adopting the three habitat definitions for each species, adult sex male and female and juvenile stage egg or caterpillar , separately.
We first fitted linear models implemented in SAS Genmod procedure, with a Poisson distribution and a log link function corresponding to all the combinations of the descriptors, i. Descriptors were standardized prior to analysis, so that slope estimates can be compared within each model to assess their relative effect size. For each population of the B.
This was done in order to buffer the variation among sites due to the non-negligible and asynchronous temporal variations in these butterfly populations Thomas, This was crucial to avoid that spatial variation, which we attempt to explain, are biased by asynchronous temporal variation. We then analyzed spatial variation in minimum and maximum population sizes among sites relative to all the combinations of the descriptors, i.
To test for the transferability of the habitat quality assessment, we used the models estimated on the 15 populations in the B. This was done for the three habitat definitions, the habitat based on vegetation type, vegetation composition and ecological resources.
We measured the accuracy of the predictions at two spatial levels: 1 in the metapopulation by cross-validation, where we predicted the minimum and the maximum population sizes for each site by removing it from the dataset used to fit the model for each of these response variable; 2 in 13 additional Belgian populations i. Finally, we analyzed the quality of a sample of adult individuals, using morphological descriptors as proxies.
For each species and sex separately, we tested the effects of habitat descriptors functional area, resource abundance, distribution and organization, and connectivity for B. Variation in local abundance among the 40 Pisserotte zones was best explained by a combination of resource variables for juvenile stages of the five species and the adult stages of the two more specialized species B.
It was best explained by the vegetation composition for B.
The vegetation type presented a very weak explanatory power in all cases. Table 2. Relationship between local species abundance and habitat descriptors represented by slope estimates of linear models. Caterpillars and both adult males and females of B. Tree edges had a positive effect on caterpillar and male abundance only. For L. Adults were also more abundant in zones with a greater overlap between adult and juvenile resources, in larger zones with more host plants and in zones surrounded by trees; the latter effect was more pronounced in males.
Caterpillars of B. Contrary to caterpillars, adult local abundance was best described by the vegetation composition: males and females were more abundant in larger flower-rich zones higher values of VEG-2 and in bog vegetation zones where the host plant was more abundant lower VEG-1 values, especially for females.
Eggs of L. Variation in adult local abundance was best described by the vegetation composition. Males were more abundant in meadows, flower-rich zones and when the host plant was abundant higher values of VEG-1 and VEG It was also the case for females, although with a predominant effect of resource organization; females being more abundant in zones with a greater overlap between adult and juvenile resources. Adult local abundance was best described by the vegetation composition: abundance of males and females increased with increasing values of VEG-1 i.
Variation in minimum and maximum population sizes in the sites of the B. The explanatory power of vegetation composition and of vegetation type was clearly inferior. Table 3. Relationship between minimum and maximum population sizes for B. Maximum population size was greater in larger sites with a higher abundance of the host plant. The effect of the distribution of adult resources was much larger, whereas the effect of juvenile resource distribution and resource organization was limited.
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Greater connectivity and a heterogeneous distribution of nectar resources for adults also had a positive effect. The abundance of Sphagnum hummocks had a positive effect on minimum population size only. The predictive power of the resource-based habitat quality model estimated at the metapopulation level for B. A stronger test consisted in performing the same predictive power test on independent data, i. The rate of correct prediction i. Also, relative prediction error was not related to population size, whatever the habitat model use, although there is a trend of larger errors in smaller populations Figure 3D.
Figure 3. Predictive power of the three habitat quality models. In panels A—C are shown the predicted minimum and predicted maximum population sizes black ticks using the models based on vegetation type panel A , vegetation composition panel B and ecological resources panel C fitted on the original metapopulation data, as well as the observed population sizes —, dots. Plain dots indicate the observed population sizes that did not fall between the predicted minimum and maximum population sizes. Predictions were incorrect for 14 couples of population and year when using the vegetation type habitat model, for 21 couples when using the vegetation composition habitat model and for 10 couples when using the resource based habitat model.
D Relative error in the predictions according to the mean population size for the three habitat type models. Errors are lower for predictions made with the resource based habitat model. There is no relationship between the error and the mean population size, whatever the model considered, although relative errors are larger for smaller population sizes.
We did not find any significant effect of the resource variables on the other morphological traits in B. Table 4. Relationship between habitat quality and adult morphology in males and females of both B. Their abdomen was also bigger in sites with a more homogeneous distribution of the juvenile resources and a more heterogeneous distribution of the adult nectar resources. Effects on B. As predicted, differences are most pronounced at the juvenile stages eggs or caterpillars compared to adults whatever the degree of ecological specialism of the species. In the case of the most specialized species, we have also shown significant effects at the adult stage.
At the metapopulation scale, it was also the case for the adults of the two species, B. A vegetation-based habitat approach could work in cases where all the resources needed by the species are encompassed in a particular vegetation type, but such conditions are rather the exception than the rule. In our study, it was only the case for adults of the less specialized species B. However, we draw attention to the fact that there is a discrepancy in the results obtained at local and larger spatial scales for adults of B.
So, although the vegetation-based habitat approach can be suitable under singular conditions or for specific sites, our study supports the broader and default use of the resource-based habitat approach to establish the functional habitat of a species for the purpose of conservation and habitat restoration. Therefore, we conclude that the resource-based habitat approach should be preferred over a vegetation-based habitat approach to properly define the habitat of a species.
Also we argue that fieldwork should be conducted on several life stages Radchuk et al. As certain amounts of host plant are needed to feed a population at any site i. Although host abundance was present in most of our selected regression models, it was not sufficient to predict local butterfly abundance or population size.
Knowledge on the use of specific or different nectar resources and their significance for species distribution is much less complete compared to host plant use, because butterflies have long been considered opportunistic nectar feeders. However, Tudor et al. Loertscher et al. Our multi-species study showed that both host and nectar resources do play a role in defining a species' functional habitat.
Structural resources are often neglected although they are of high functional significance as they generally relate to micro-climatic conditions. In line with our previous work Turlure et al. The presence of grass tussocks was also recognized as an important element in the composition of the larval habitat of Coenonympha tullia as these structures favor caterpillar survival during periods of flooding Dennis and Eales, ; Joy and Pullin, Adult butterflies make use of trees and shrubs to shelter, to roost or to mate Dover et al.
We demonstrated the significance of the presence of edges with trees as they provide shelter for L. The significance of such structural elements may also vary with local weather conditions as has been shown in Plebejus argus : adults were more abundant near scrub under wind exposed conditions Dennis and Sparks, Adopting the resource-based habitat approach, the functional habitat of a butterfly consists of 1 nectar feeding resources, mate location sites, roosting sites and egg-laying sites for adults, 2 a substrate and appropriate microclimate for eggs, 3 host plants providing larval feeding resources that occur in an appropriate structure and microclimate for caterpillar growth, and 4 appropriate structure and microclimate for the pupal stage and hibernation aestivation see more details in Dennis et al.
The number of resources involved in habitat composition may vary, with generalist species likely using a wider range of more numerous resources, while more exigent species likely needing less but more specific resources. Not all ecological resources were included in our study and certainly we still lack knowledge on habitat resource composition for our study species.
Vegetation type and composition may indeed have additional explanatory power. But even with incomplete ecological information, we have demonstrated the suitability of the resource-based approach of the species' habitat and argue for its standard use in conservation. Although the terminology used to describe a species habitat seems to be taxonomic-specific, many examples of key resource elements whose distribution does not coincide with a unique vegetation type can be found in the literature for a wide range of organisms other than butterflies.
For example, the seasonal use of different vegetation types providing suitable food resources has been illustrated in the lilac-crowned parrot Amazona finschi Katherine, and in the wildebeest Connochaetes taurinus Yoganand and Owen-Smith, Not only the species' needs in terms of food resources were investigated. Long ago, Magnuson et al. In the same way, light conditions have been identified as an important ecological resource for the damselfly Megalagrion nigrohamatum nigrolineatum , whose individuals use dark locations to perch Henry et al.
Structural elements can also be considered as resources, as they may serve as roosts Weber et al. Even time used for foraging the same food resources could be considered as a resource, as exemplified with sympatric cormorants species Mahendiran, In some cases, however, vegetation type or composition may be an efficient proxy for a part of species habitat, with some resources being encompassed in this given vegetation type or composition.
This seems the case for some butterfly species such as Lopinga achine , a forest species for which canopy closure limits the availability of host plants Konvicka et al. Nevertheless, a resource-based approach describing a species habitat may theoretically suit any organism and requires detailed auto-ecological study to assess species resource needs in details. Its use may help to guide conservation programs Parentoni Martins, and to understand the pattern of species coexistence in relation to the effects of inter-specific competition Cloyed and Eason, ; Estevo et al.
At the individual level, variation in availability and quality of host plant resources stored nutrients and nectar resources incoming nutrients were shown to affect adult morphology, longevity, reproduction and, ultimately, butterfly fitness Hill, ; Boggs and Freeman, ; Jervis and Boggs, In our study, populations of B. Variation in availability and quality of host plant and nectar resources also had an effect at the population level.
Population size has been suggested to be strongly linked with the abundance of host plant and nectar resources Schultz and Dlugosch, Several studies on different butterfly species have illustrated such a relationship. Population density of Polyommatus coridon was, for example, largely explained by its larval food plant quantity Krauss et al. Here, we have also demonstrated that the availability of larval resources is significantly related to adult population size in two species i. Resource organization is likely to affect habitat exploitation, and hence individual distribution and movements.
For example, the configuration of host and nectar resources used by Parnassius apollo impacted on adult distribution as females are more abundant in host plant patches close to nectar resources, independently of the host plant abundance Fred et al. Here, we observed our study species to be locally more abundant in zones with a greater overlap between juvenile and adult resources. In Coenonympha tullia , the most suitable conditions for population persistence were defined as the overlap contiguity of larval host plant and nectar resources Dennis and Eales, Similarly, higher minimum population sizes were observed in the case of a greater overlap between juvenile and adult resources in B.
Organization of host plant in patches of homogeneous abundance had a positive influence on minimum population size in B. A conflict of interest may occur for females when host and nectar resources do not overlap spatially: they have to choose between meeting their own requirements and those of their offspring. Hence, this represents a case of the concept known as the parent-offspring conflict Trivers, Females of some species were observed to prefer staying at nectar rich zones Grossmueller and Lederhouse, ; Brommer and Fred, while others avoid feeding at the cost of longevity e.
Here, we only observed females of B. The open zones probably offer more constant sun exposure and warmer microclimates needed to mature eggs. Baguette and Van Dyck and Dennis and Hardy proposed that in the process of resource finding, resource grain may affect the types of movement i. When resources are spatially separated, the associated cost of exploitation may lead to either more sedentary individuals through selection against high mobility Komonen et al.
Here, we have demonstrated that the grain and organization of resources were associated with morphology in several ways. Adult males of B. Our analysis has allowed us to assess the relative importance of each ecological resource in terms of both availability and organization relative to the species' abundance, demography and individual fitness. As predicted, resource availability, and especially host plant abundance, does not necessarily play the predominant role in defining habitat quality.
Although the host plant is a necessary resource whose presence is required for an area to qualify as habitat, it is in most cases overruled by the resource organization to define habitat quality. More generally, this shows that understanding behavior relative to resource distribution can be of key significance to define species-specific habitat. Similar conclusions can be drawn for other taxonomic groups. Habitat quality has previously been defined as the ability of the environment to provide conditions appropriate for individual and population persistence Hall et al.
In their review paper, Mortelliti et al. However, numerous papers exist reporting links between pattern of occupancy, population growth rate, population size or individual fitness and resource availability. For examples, 1 optimal vs. Habitat quality from resource composition and availability predicted density or population size in the Great Crested Newt Triturus cristatus Unglaub et al. In the Cap mountain zebra Equus zebra zebra , lower resource availability influenced individual physiology, in turn affecting population growth rate Lea et al.
In the mud crab Panopeus herbstii , habitat quality reef height, in the field and the diet in the lab impacted on the reproductive performance of females Griffen and Norelli, Although the influence of habitat patch distribution in the landscape on population dynamics and persistence has received support from several studies e. However, resource distribution has been theoretically and experimentally shown to influence resource utilization, feeding behaviors, social organization and mating systems in many organisms e.
The list of examples quoted here is obviously not exhaustive, but illustrates that habitat quality using the resource-based approach may provide a functional basis for assessing the population status of any species from different taxonomic groups. Finally, we have confirmed the between-population transferability of the habitat definition and habitat quality estimates by adopting a resource-based habitat approach.
Although performed on a single species, this demonstration provides a strong argument in favor of detailed autecological studies to identify 1 key resources defining the functional habitat, and 2 how resource availability and organization influence habitat quality. Many species conservation plans need to quantify habitat quality at more or less large spatial scales. A resource-based approach is likely to prove an efficient way to do so from the presence and abundance of a series of key resources. Using a vegetation type based definition of the habitat fails in such a situation because of its habitat vs.
Note that the transferability has been investigated here at a rather small geographical scale i. If applied at much larger scales, like continental scales, changes in resources used by a species, as well as local adaptations, may hamper the transferability. However, conservation plans are rarely designed at such large scales. Given the number of variables included in the resource-based definition such as previously described, it is not a restrictive definition. Or preferably, consult this volume of recent contributions on the biology of butterflies.
It stems from the Third International Butterfly Ecology and Evolution Symposium at Crested Butte, Colorado, in August , and contains invited presentations plus expansions of selected contributed talks and posters from the meeting: a total of 26 chapters. Butterfly researchers first met as a group at an International Symposium on butterfly biology, held in London in Vane-Wright and Ackery, , thereby establishing a tradition that has led, through a second meeting at Stockholm in , to the Colorado meeting.
This volume is presented in five sections: behavior, ecology, Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide.
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