Factors affecting the abundance of House Sparrows Passer domesticus in urban areas of southeast of Spain

Figures & data

Figure 1. Maps showing selected Valencian localities (Spain, Europe) for the study of factors affecting the abundance of House Sparrows in urban areas of southeast of Spain between 2014 and 2016. The sizes of the circles show how large the urban areas are in terms of their overall number of inhabitants.

Table 1. Geographical, demographical and climatic characteristics of the selected locations for the study of factors affecting the abundance of House Sparrows in urban areas of southeast of Spain between 2014 and 2016. Table devised with data from SigPac (2014), AVAMET (2016) and Instituto Nacional de Estadística (Spanish National Statistics Institute) (2016).

Location	Coordinates	Number of inhabitants 2015	Density (inhabitants/km^2)	Temperature 2015 (°C)			Rainfall 2015 (mm)	Altitude (m.a.s.l.)	Point counts^a	Studied urban surface (ha)
				Max.	Med.	Min.
Banyeres de Mariola	38°42′57″ N 0°39′26″ W	7155	143.65	39.6	15.4	−5.2	489.2	816	14 (3/3/8)	93.33
Muro de Alcoy	38°46′47″ N 0°26′10″ W	9167	297.91	42.3	17.0	−4.1	421.4	410	18 (3/3/12)	116.97
Cocentaina	38°44′42″ N 0°26′26″ W	11 406	218.93	42.8	16.9	−1.8	533.2	430	20 (5/5/10)	133.56
Alcoy	38°41′54″ N 0°28′25″ W	59 567	468.48	41.2	16.0	−3.3	548.4	562	60 (15/15/30)	401.41
Gandía^b	38°59′39″ N 0°10′56″ W	61 319	1258.17	43.3	20.1	3.5	677.1	22	31 (10/3/18)	248.25
Grao/Playa^b	38°58′00″ N 0°09′45″ W	13 895	–	–	–	–	466.6	0	38 (14/3/21)	278.44

^a Total point counts in each locality and their distribution among the three sampled environments (parks/schools/streets).

^b Sectors Gandía and Grao/Playa are separated by orange groves.

Figure 2. Distribution of the 18 point counts within the location of Muro de Alcoy (Valencia, Spain) as an example of their distribution in the locations for the study of factors affecting the abundance of House Sparrows in urban areas of southeast of Spain between 2014 and 2016. Symbols represent point count locations in parks (squares), on streets (circles) and in schools (crosses).

Table 2. Summary of the environmental variables used in the Hierarchical Partitioning Analyses for the study of factors affecting the abundance of House Sparrows in urban areas of southeast of Spain between 2014 and 2016. Note that there are two different main groups of studied variables, (A) urban landscape and (B) parks. The variable geography was included in every group to control overall location effects of the sampling points.

(A) URBAN LANDSCAPE
Resources	Urban structure	Human factors
(1) Presence/absence of park (2) Presence/absence of private gardens (3) Presence/absence of bar/cafeteria terrace (4) Presence/absence of rubbish bins^a (5) Presence/absence of vacant lot (6) Presence/absence of school building and yard (7) Presence/absence of lawn	(8) Presence/absence of old buildings (built before 1950) (9) Building height (mean number of floors of 8 buildings) (10) Street width (m) (11) Presence/absence of mature trees (12) Distance to the nearest urbanized limit (m) (13) Vegetation cover of the point count (7 854 m^2)^b	(14) Number of people per minute^c (15) Number of vehicles per minute^c (16) Socioeconomic status^d (17) Altitude above sea level
(B) PARKS
Vegetation and substratum	Location	Urban factors
(1) Vegetation cover of the park^e (2) Dominant vegetation^f (3) Average height of vegetation (4) Presence/absence of shrubs higher than 1 m (5) Presence/absence of exotic vegetation (6) Presence/absence of sand (7) Presence/absence of lawn (8) Dominant substratum^g	(9) Distance to the nearest urbanized limit (m) (10) Survey zone of the park (edge or centre) (11) Distance to the nearest park (m) (12) Area of the park (m^2) (13) Altitude above sea level (m) Resources (14) Presence/absence of rubbish bins (15) Presence/absence of bar/cafeteria terrace (16) Presence/absence of water body (17) Presence/absence of children’s play area	(18) Number of people per minute^e (19) Socioeconomic status^d (20) Presence/absence of dogs (21) Presence/absence of cats

^aRubbish bins refers to communal above-ground trash containers.

^bFour categories: 0–5%, 6–30%, 31–60% and >60%.

^cBoth were calculated by counting the number of pedestrians and vehicles entering the point count for 5 minutes and standardizing them to obtain the number per minute (Menon et al. 2013).

^dFive socioeconomic status areas based on type of buildings, height, age, density, presence of private gardens and cleanliness of streets (De Laet et al. 2011). (1) Deprived areas: low-rise old buildings, often with holes for nesting. (2) Average socioeconomic status: the commonest areas in towns and cities, dominated by the highest buildings with a high density of shops and businesses. They present a vast heterogeneity of buildings and very dense traffic. (3) Well-off areas: outside city centres, low-rise apartments or houses, recently built and associated with private gardens. (4) High socioeconomic status areas: away from city centres, with low-density buildings, usually houses of two levels associated with private gardens. (5) Industrial areas (reference level): located on the outskirts of towns and characterized by the presence of industrial buildings with a few green areas.

^e Three categories: 0–30%, 31–60% and >60%.

^f Four categories: lawn, shrubbery, trees and trees and lawn.

^gFour categories: sand, lawn, rubber and pavement.

Table 3. Presence during counts, percentage of occupied points and mean count of House Sparrows in the 181 point counts during five seasons in urban areas of southeast of Spain between 2014 and 2016.

Parameter			Season of census
	Autumn 2014	Winter 2014–15	Summer 2015	Autumn 2015	Winter 2015–16
Presence	162/181	153/181	170/181	160/181	151/181
Percentage	89.50	84.53	93.92	88.40	83.43
Mean count ± sd	9.39 ± 8.54	6.47 ± 5.06	9.08 ± 7.45	8.43 ± 6.98	7.06 ± 5.78

Table 4. Variables identified by the combined Hierarchical Partitioning (HP) Analyses as key factors affecting the abundance of House Sparrows in urban areas of southeast of Spain between 2014 and 2016.

Season	Group	Variable	I^a	J^b	I%	Z score	Sign
Autumn 2014	Resources	Urban park	0.0222	0.0165	8.87	2.19	+
		Vacant lot	0.0233	−0.0009	9.29	2.39	+
	Urban structure	Old buildings	0.0516	0.0010	20.55	5.90	+
		Building height	0.0318	0.0323	12.67	3.09	−
	Human factors	Socioeconomic status^c	0.0805	0.0089	32.07	3.35	+
		People/minute	0.0264	0.0147	10.53	2.11	−
Winter 2014–15	Resources	Urban park	0.0278	0.0266	13.20	2.80	+
		Rubbish bin	0.0411	0.0163	19.51	4.75	+
	Urban structure	Building height	0.0207	0.0239	9.80	1.80	−
	Human factors	People/minute	0.0287	−0.0022	13.62	3.10	−
		Vehicles/minute	0.0250	0.0315	11.85	2.56	−
		Geography	0.0537	0.0145	25.47	6.04	+
Summer 2015	Resources	Urban park	0.1162	0.1166	31.36	15.19	+
		Rubbish bin	0.0940	−0.0074	25.37	25.36	+
		Lawn	0.0236	0.0546	6.38	2.37	+
	Urban structure	Building height	0.0613	0.0853	16.55	6.71	−
		Street width	0.0209	0.0411	5.63	1.85	−
	Human factors	People/minute	0.0211	0.0049	5.70	2.07	−
Autumn 2015	Urban structure	Building height	0.0257	0.0268	16.37	2.43	−
	Human factors	People/minute	0.0293	0.0171	18.68	2.74	−
		Vehicles/minute	0.0219	0.0157	13.93	1.93	−
Winter 2015–16	Resources	Urban park	0.0804	0.0874	21.63	10.27	+
		Rubbish bin	0.0368	0.0338	9.89	3.76	+
	Urban structure	Building height	0.0264	0.0268	7.09	2.92	−
		Trees	0.0257	0.0480	6.91	2.80	+
	Human factors	Vehicles/minute	0.0376	−0.0118	10.11	4.41	−
		Geography	0.1311	0.0397	35.25	15.64	+

^a Independent effect of the variable

^b Joint effects caused with other variables

^c The reference level of the socioeconomic status was the industrial area, so all other categories were positive for the abundance of the species

Table 5. Variables identified by the combined Hierarchical Partitioning (HP) Analyses as key factors affecting the abundance of House Sparrows in urban parks of southeast of Spain between 2014 and 2016.

Season	Group	Variable	I^a	J^b	I%	Z score	Sign
Summer 2015	Location	Park’s area	0.0810	0.0059	56.49	2.23	+
		Dogs	0.0620	0.0058	43.22	1.69	−
Autumn 2015	Location	Distance to nearest park	0.0752	0.0004	99.31	1.97	−
Winter 2015–16	Resources	Rubbish bin	0.1461	0.0354	59.94	4.53	+
	Location	Distance to nearest park	0.0709	0.0177	29.04	1.71	−

^aIndependent effect of the variable.

^bJoint effects caused with other variables.

SigPac. 2014. Visor SigPac. Ministerio de Agricultura, Alimentación y Medio Ambiente. Gobierno de España, Madrid. Available from: http://sigpac.mapa.es/fega/visor [accessed September 2014].

 Google Scholar

AVAMET. 2016. Meteoxarxa, Estadístiques. Associació Valenciana de Meteorologia ‘Josep Peinado’. Buñol, Spain. Available from: http://www.avamet.org/ [accessed October 2016].

 Google Scholar

Instituto Nacional de Estadística. 2016. INEbase. Demografía y población. Padrón. Población por municipios. INE, Madrid. http://www.ine.es/dynt3/inebase/index.htm?padre=525 [accessed November 2016].

 Google Scholar

Menon, M., Devi, P. & Mohanraj, R. 2013. Habitat variability and spatial assemblages of House Sparrows (Passer domesticus) along a gradient of urbanization. IOSR-JESTFT. 4: 1–11. doi: 10.9790/2402-0460111

 Google Scholar

De Laet, J., Peach, W.J. & Summers-Smith, J.D. 2011. Protocol for censusing urban sparrows. Br. Birds. 104: 255–260.

 Google Scholar